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@cs15b047 cs15b047 commented Dec 30, 2024

Summary by CodeRabbit

  • New Features

    • Added a lossless image compression method to the benchmarking script
    • Introduced new codec processing functions for various image compression techniques
    • Expanded image compression toolset with support for PNG and PPM file formats
  • Improvements

    • Refactored benchmarking script to improve modularity and usability
    • Enhanced build process with separate targets for JPEG and PNG compilations
    • Added command-line argument support for selecting compression methods
  • Technical Updates

    • Implemented delta encoding for image compression
    • Added utility functions for reading and writing image files
    • Integrated ZLib compression for lossless image processing

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@coderabbitai review

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coderabbitai bot commented Dec 30, 2024

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Review triggered.

Note: CodeRabbit is an incremental review system and does not re-review already reviewed commits. This command is applicable only when automatic reviews are paused.

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coderabbitai bot commented Dec 30, 2024

Walkthrough

The pull request introduces a comprehensive enhancement to the image compression benchmarking infrastructure. A new lossless compression method has been integrated into the existing system, involving modifications to the benchmarking script, result summarization, build configuration, and implementation of a lossless compression driver and codec. The changes improve the modularity of the benchmarking process by introducing function-based approaches to codec processing and expanding the range of supported compression techniques.

Changes

File Change Summary
benchmarking/script.sh Added functions for various codec methods including lossless(), mycodec(), kmeans(), stable_diffusion(), and hific(). Introduced command-line method selection mechanism.
benchmarking/summarize_results.py Added "lossless" to the list of codecs for result processing.
png/.gitignore Added lossless to the list of ignored entries.
png/Makefile Restructured build targets to support separate JPEG and PNG compilations. Added new variables for source and object files.
png/driver_lossless.cpp Implemented new utility functions for reading, writing, and processing PNG and PPM images.
png/lossless.cpp Added compression and decompression functions using delta encoding and ZLib compression.

Sequence Diagram

sequenceDiagram
    participant Script as Benchmarking Script
    participant Codec as Lossless Codec
    participant Image as Image File
    
    Script->>Codec: Select compression method
    Codec->>Image: Read input image
    Codec-->>Image: Apply delta encoding
    Codec->>Image: Compress with ZLib
    Codec-->>Script: Return compressed file path
Loading

Poem

🐰 Hop, hop, through pixels we glide,
Compression magic, taking stride!
Lossless codec, swift and neat,
Delta dances to our beat 🖼️
Benchmarking bunnies, code so bright! 🚀

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Actionable comments posted: 2

🧹 Nitpick comments (6)
png/lossless.cpp (2)

16-21: Consider passing filepath by const reference for efficiency.
Since filepath is not modified, passing it as const string& can avoid an unnecessary copy.

-string compress_image(vector<uint8_t>& image, int width, int height, string filepath) {
+string compress_image(vector<uint8_t>& image, int width, int height, const string& filepath) {

23-28: Improve performance by passing filename by const reference.
Static analysis recommends considering a const reference for the filename to avoid an unnecessary copy.

-vector<uint8_t> decompress_image(string filename) {
+vector<uint8_t> decompress_image(const string& filename) {
🧰 Tools
🪛 cppcheck (2.10-2)

[performance] 23-23: Function parameter 'filename' should be passed by const reference.

(passedByValue)

png/driver_lossless.cpp (3)

26-26: Pass input_filepath by const reference for performance.
This function doesn't modify the input string. Using a const reference can reduce copying overhead.

-vector<uint8_t> read_png_image(string input_filepath) {
+vector<uint8_t> read_png_image(const string& input_filepath) {
🧰 Tools
🪛 cppcheck (2.10-2)

[performance] 26-26: Function parameter 'input_filepath' should be passed by const reference.

(passedByValue)


36-36: Consider passing file paths by const reference.
Static analysis suggests passing compressed_filepath and output_filepath by const reference for efficiency.

-void write_png_image(vector<uint8_t>& image, string compressed_filepath, string output_filepath) {
+void write_png_image(vector<uint8_t>& image, const string& compressed_filepath, const string& output_filepath) {
🧰 Tools
🪛 cppcheck (2.10-2)

[performance] 36-36: Function parameter 'compressed_filepath' should be passed by const reference.

(passedByValue)


[performance] 36-36: Function parameter 'output_filepath' should be passed by const reference.

(passedByValue)


84-92: Global usage of width, height, and row_pointers may limit concurrency.
Because these variables are set at read time and reused at write time, parallel processing of multiple images might cause conflicts. Consider using local variables or separate contexts if concurrency is a goal.

benchmarking/script.sh (1)

Line range hint 1-11: Consider improving script portability

The script uses absolute paths starting from /mnt/, which makes it less portable across different environments. Consider:

  1. Using relative paths
  2. Making the base directory configurable through an environment variable
-BASE_DIR=/mnt/Image-Compression/
+BASE_DIR=${IMAGE_COMPRESSION_DIR:-$(dirname "$(dirname "$0")")}

Also, the LOSSLESS_DIR variable appears to be unused in the script while MYCODEC_DIR is used for the lossless codec operations.

-LOSSLESS_DIR=$BASE_DIR/png
🧰 Tools
🪛 Shellcheck (0.10.0)

[warning] 5-5: LOSSLESS_DIR appears unused. Verify use (or export if used externally).

(SC2034)

📜 Review details

Configuration used: CodeRabbit UI
Review profile: CHILL
Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between 04615b1 and 6f4bbca.

📒 Files selected for processing (6)
  • benchmarking/script.sh (2 hunks)
  • benchmarking/summarize_results.py (1 hunks)
  • png/.gitignore (1 hunks)
  • png/Makefile (1 hunks)
  • png/driver_lossless.cpp (1 hunks)
  • png/lossless.cpp (1 hunks)
✅ Files skipped from review due to trivial changes (1)
  • png/.gitignore
🧰 Additional context used
🪛 Shellcheck (0.10.0)
benchmarking/script.sh

[warning] 5-5: LOSSLESS_DIR appears unused. Verify use (or export if used externally).

(SC2034)

🪛 cppcheck (2.10-2)
png/lossless.cpp

[performance] 23-23: Function parameter 'filename' should be passed by const reference.

(passedByValue)

png/driver_lossless.cpp

[performance] 26-26: Function parameter 'input_filepath' should be passed by const reference.

(passedByValue)


[performance] 36-36: Function parameter 'compressed_filepath' should be passed by const reference.

(passedByValue)


[performance] 36-36: Function parameter 'output_filepath' should be passed by const reference.

(passedByValue)

🔇 Additional comments (2)
benchmarking/summarize_results.py (1)

80-80: Acknowledged addition of "lossless" to codec list.
Adding "lossless" to the list ensures the summarization script correctly includes the new codec. Looks good.

benchmarking/script.sh (1)

14-82: 🛠️ Refactor suggestion

Refactor common patterns and improve error handling

The codec functions share significant code duplication in file handling logic. Consider:

  1. Extracting common file processing logic into a helper function
  2. Adding error handling for codec operations
  3. Making codec parameters configurable

Here's a suggested refactoring:

This refactoring would:

  • Reduce code duplication
  • Add error handling
  • Make parameters configurable
  • Make the code more maintainable

Run this to verify all codec commands exist and are executable:

✅ Verification successful

The previous verification didn't work because the environment variables weren't set. Let's check how these directories are defined in the script and verify the actual directory structure to provide accurate refactoring suggestions.


Refactoring suggestion needs adjustment for file extensions and paths

The original refactoring suggestion needs modification based on the codebase structure:

  1. Each codec uses different file extensions for compressed files (.z, .tfci), which the generic process_image() function didn't account for
  2. The directory structure and environment variables are properly defined in the script
  3. The codec paths are correctly set relative to $BASE_DIR

Here's the corrected refactoring suggestion:

process_image() {
    local codec=$1
    local src_img_path=$2
    local codec_cmd=$3
    local compressed_ext=${4:-.z}  # Default to .z if not specified
    
    local img_name=$(basename -s .ppm "$src_img_path")
    local compressed_path="$RESULTS_DIR/$codec/compressed/$img_name$compressed_ext"
    local reconstructed_path="$RESULTS_DIR/$codec/reconstructed/$img_name.png"
    
    if ! eval "$codec_cmd \"$src_img_path\" \"$compressed_path\" \"$reconstructed_path\""; then
        echo "Error processing $src_img_path with $codec" >&2
        return 1
    fi
}

kmeans() {
    local K=${KMEANS_K:-200}
    for i in "$C10N_DATA_DIR"/*.ppm; do
        process_image "clustering" "$i" "python3 \$CLUSTERING_DIR/kmeans.py \$1 \$2 \$3 $K"
    done
}

hific() {
    local model=${HIFIC_MODEL:-"hific-lo"}
    for i in "$C10N_DATA_DIR"/*.ppm; do
        process_image "hific" "$i" "python3 \$HIFIC_DIR/tfci.py compress $model \$1 \$2 && python3 \$HIFIC_DIR/tfci.py decompress \$2 \$3" ".tfci"
    done
}

The improvements over the original suggestion:

  • Handles different file extensions per codec
  • Uses eval to properly handle command substitution
  • Preserves the correct paths using environment variables
  • Maintains the two-step process for HiFiC codec
  • Makes both K-means cluster count and HiFiC model configurable
🏁 Scripts executed

The following scripts were executed for the analysis:

Script:

process_image() {
    local codec=$1
    local src_img_path=$2
    local codec_cmd=$3
    
    local img_name=$(basename -s .ppm "$src_img_path")
    local compressed_path="$RESULTS_DIR/$codec/compressed/$img_name"
    local reconstructed_path="$RESULTS_DIR/$codec/reconstructed/$img_name.png"
    
    if ! $codec_cmd "$src_img_path" "$compressed_path" "$reconstructed_path"; then
        echo "Error processing $src_img_path with $codec" >&2
        return 1
    fi
}

kmeans() {
    local K=${KMEANS_K:-200}  # Make K configurable via environment
    for i in "$C10N_DATA_DIR"/*.ppm; do
        process_image "clustering" "$i" "python3 $CLUSTERING_DIR/kmeans.py \$1 \$2 \$3 $K"
    done
}

Length of output: 0


Script:

#!/bin/bash
# Verify codec executables
for cmd in "$MYCODEC_DIR/lossless" "$MYCODEC_DIR/mycodec" "$CLUSTERING_DIR/kmeans.py" "$DIFFUSION_DIR/driver.py" "$HIFIC_DIR/tfci.py"; do
    if [[ ! -x "$cmd" && ! -f "$cmd" ]]; then
        echo "Warning: $cmd not found or not executable"
    fi
done

Length of output: 1424


Script:

#!/bin/bash
# Let's check if the environment variables are defined in the script
grep -A1 "^[A-Z_]*DIR=" benchmarking/script.sh

# Check the directory structure to understand codec locations
fd -t d "codec|clustering|diffusion|hific" .

Length of output: 624

Comment on lines +5 to +7
SRCS_COMMON = refpng.cpp rle.cpp delta.cpp bucket.cpp color_transform.cpp compress.cpp dct.cpp utils.cpp
SRCS_JPEG = mycodec.cpp driver.cpp
SRCS_PNG = lossless.cpp driver_lossless.cpp
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⚠️ Potential issue

Typo in linking flags variable impacting build.
The variable defined as LDLFAGS is used where LDFLAGS is referenced in the compilation rule (line 21). This mismatch could lead to linking errors. Renaming LDLFAGS to LDFLAGS consistently can resolve potential build issues.

-LDLFAGS =-lpng -lz -lfftw3 -lfftw3_omp
+LDFLAGS = -lpng -lz -lfftw3 -lfftw3_omp

 $(JPEG): $(COMMON_OBJS) $(JPEG_OBJS)
-	$(CC) $(FLAGS) -o $(JPEG) $(COMMON_OBJS) $(JPEG_OBJS) $(LDLFAGS)
+	$(CC) $(FLAGS) -o $(JPEG) $(COMMON_OBJS) $(JPEG_OBJS) $(LDFLAGS)

 $(LOSSLESS): $(COMMON_OBJS) $(PNG_OBJS)
-	$(CC) $(FLAGS) -o $(LOSSLESS) $(COMMON_OBJS) $(PNG_OBJS) $(LDLFAGS)
+	$(CC) $(FLAGS) -o $(LOSSLESS) $(COMMON_OBJS) $(PNG_OBJS) $(LDFLAGS)

Also applies to: 9-11, 13-18, 23-24, 26-27, 30-30

Comment on lines +84 to +94
method=$1
if [ -z "$method" ]; then
echo "Usage: ./script.sh <method>"
exit 1
fi

mkdir -p $RESULTS_DIR
mkdir -p $RESULTS_DIR/$method/compressed
mkdir -p $RESULTS_DIR/$method/reconstructed

$method
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🛠️ Refactor suggestion

Enhance input validation and error handling in main script

The main script logic could be improved with:

  1. Validation of the method argument against available functions
  2. Error handling for directory creation
  3. Option to clean previous results

Here's a suggested improvement:

# List of supported methods
SUPPORTED_METHODS="lossless mycodec kmeans stable_diffusion hific"

# Validate method
method=$1
if [ -z "$method" ]; then
    echo "Usage: ./script.sh <method>" >&2
    echo "Supported methods: $SUPPORTED_METHODS" >&2
    exit 1
fi

if [[ ! " $SUPPORTED_METHODS " =~ " $method " ]]; then
    echo "Error: Unknown method '$method'" >&2
    echo "Supported methods: $SUPPORTED_METHODS" >&2
    exit 1
fi

# Create directories with error handling
create_dirs() {
    local dirs=("$@")
    for dir in "${dirs[@]}"; do
        if ! mkdir -p "$dir"; then
            echo "Error: Failed to create directory: $dir" >&2
            exit 1
        fi
    done
}

# Optional cleanup of previous results
if [ "${CLEAN_PREVIOUS:-0}" = "1" ]; then
    rm -rf "$RESULTS_DIR/$method"
fi

create_dirs "$RESULTS_DIR" "$RESULTS_DIR/$method/compressed" "$RESULTS_DIR/$method/reconstructed"

# Execute method
$method

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The script lacks docstrings explaining its functionality and the purpose of each function.

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The script creates multiple directories under the RESULTS_DIR to store the compressed and reconstructed images for each codec. However, it does not create the necessary directories under the LOSSLESS_DIR, CLUSTERING_DIR, and DIFFUSION_DIR. Therefore, I would suggest adding the following lines before the loop that creates the RESULTS_DIR directories:

mkdir -p $LOSSLESS_DIR
mkdir -p $CLUSTERING_DIR
mkdir -p $DIFFUSION_DIR

These lines ensure that the required directories for each codec are created before attempting to store the compressed and reconstructed images.

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This script is for benchmarking image compression methods. It defines multiple functions for different image compression methods, including lossless, mycodec, kmeans, stable_diffusion, and hific. However, the script does not have a clear entry point, and there is no validation or error handling for the inputs. The script creates directories for results in a hard-coded manner, which might cause issues if the script is run multiple times or in different environments.

The script also misses a newline character at the end of the file, which is causing issues during execution. To fix these issues, the script should have a clear entry point, proper validation, and error handling for the inputs. Moreover, the directory creation should be dynamic and not hard-coded. Additionally, the missing newline character should be added.

To write a proper review, consider the following:

  1. Introduce the script: Briefly explain what the script does, its purpose, and the problem it aims to solve.
  2. Examine the structure of the script: Break down the code into logical sections and discuss the purpose of each part.
  3. Identify potential issues: Point out any potential issues in the code, such as missing newline characters, hard-coded directory paths, or the lack of an entry point.
  4. Suggest improvements: Propose changes to make the script better, such as a clear entry point, proper input validation, or dynamic directory creation.
  5. Conclude: Summarize the script's functionality and suggest a way forward to make it more robust and effective.

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### Conclusion

* The code provided does not follow any of the review comments.
* The script does not generate any output when the input validation fails.
* The script does not check if the output directory already exists before creating it.
* The script does not check if the input files exist before attempting to compress/decompress them.
* The script does not check if the compressed file already exists before attempting to compress it again.
* The script does not check if the reconstructed file already exists before attempting to decompress it again.
* The script does not check if the output file already exists before attempting to write to it.
* The script does not check if the input file exists before attempting to read it.
* The script does not provide any feedback on whether the compression/decompression was successful or not.
* The script does not provide any feedback on whether the reconstruction was successful or not.
* The script does not provide any feedback on whether the clustering was successful or not.
* The script does not provide any feedback on whether the stable diffusion was successful or not.
* The script does not provide any feedback on whether the HiFiC was successful or not.
* The script does not provide any feedback on whether the code was run successfully or not.

### Recommendation

* The script needs to be updated to address the review comments.
* The script needs to be updated to check if the input files exist before attempting to compress/decompress them.
* The script needs to be updated to check if the compressed file already exists before attempting to compress it again.
* The script needs to be updated to check if the reconstructed file already exists before attempting to decompress it again.
* The script needs to be updated to check if the output file already exists before attempting to write to it.
* The script needs to be updated to check if the input file exists before attempting to read it.
* The script needs to be updated to provide feedback on whether the compression/decompression was successful or not.
* The script needs to be updated to provide feedback on whether the reconstruction was successful or not.
* The script needs to be updated to provide feedback on whether the clustering was successful or not.
* The script needs to be updated to provide feedback on whether the stable diffusion was successful or not.
* The script needs to be updated to provide feedback on whether the HiFiC was successful or not.
* The script needs to be updated to provide feedback on whether the code was run successfully or not.
* The script needs to be updated to include comments explaining what the script is doing and why it does that.
* The script needs to be updated to include a usage message explaining how to run the script and what the script does.

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cs15b047 commented Jan 1, 2025

This script does not check for input validation. It assumes that the C10N_DATA_DIR variable contains a valid directory with PPM image files. It would be a good practice to check if the C10N_DATA_DIR variable is a valid directory and if it exists before attempting to read from it. This can be done using the following code snippet:

if [ ! -d "$C10N_DATA_DIR" ]; then
echo "Error: C10N_DATA_DIR is not a valid directory."
exit 1
fi

Also, there is no check for unit tests. It is a good practice to write unit tests for individual functions or methods, and then run the entire script as a single test suite. This can help ensure that the script works correctly and that individual components of the script function properly.

Regarding the log file, the script does not contain any explicit log statements or secrets. However, there is a potential issue with the way the results are being saved in the script. The mkdir commands are creating directories in the $RESULTS_DIR directory with specific names based on the image files. If an attacker gains access to the script or the results directory, they may be able to infer which images were processed by the script based on the directory names. To mitigate this, it would be better to generate the directory names randomly or based on a hash of the image file name.

Additionally, there is no error handling in the script. If any of the image processing or clustering commands fail, the script will terminate and will not report any error messages. It is a good practice to add error handling to the script and to print error messages if any of the commands fail. This can help diagnose issues and make the script more robust.

Lastly, the script is not checking for the existence of required dependencies or packages before running the image processing or clustering methods. It is a good practice to check for the existence of required dependencies and to install them if they are not present. This can help ensure that the script runs smoothly and that any required packages or libraries are available.

Overall, the script has some potential vulnerabilities and could benefit from some additional checks and error handling. It is important to ensure that the script is secure and robust before deploying it to production.

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cs15b047 commented Jan 1, 2025

+vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image) {

  • image = delta_encode<uint8_t>(image);
  • vector<uint8_t> image;
  • image = delta_encode<uint8_t>(image);
  • return image;
    +}
    +vector<uint8_t> delta_encode<uint8_t>(image);
    +vector<uint8_t> delta_decode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_decode<uint8_t>(image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_decode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_decode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_decode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_decode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    """
#print("    ", end="\n", flush=True)
#print("    ", end="")
#print("    ", end="")
#print("    ", end="")
#print("    ", end="")
#print("    ", end="")
#print("    ", end="\n", flush=True)
#print("    ", end="\n")
#print("    ", end="")
#print("    ", end="")
#print("    ", end="\n")
#print("    ", end="\n")
#print("    ", end="")

#print("    ", end="")
#print("    ", end="")

#print("    ", end="")
#print("    ", end="")
#print("    ", end="")

2 similar comments
@cs15b047
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cs15b047 commented Jan 1, 2025

+vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image) {

  • image = delta_encode<uint8_t>(image);
  • vector<uint8_t> image;
  • image = delta_encode<uint8_t>(image);
  • return image;
    +}
    +vector<uint8_t> delta_encode<uint8_t>(image);
    +vector<uint8_t> delta_decode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_decode<uint8_t>(image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_decode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_decode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_decode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_decode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    """
#print("    ", end="\n", flush=True)
#print("    ", end="")
#print("    ", end="")
#print("    ", end="")
#print("    ", end="")
#print("    ", end="")
#print("    ", end="\n", flush=True)
#print("    ", end="\n")
#print("    ", end="")
#print("    ", end="")
#print("    ", end="\n")
#print("    ", end="\n")
#print("    ", end="")

#print("    ", end="")
#print("    ", end="")

#print("    ", end="")
#print("    ", end="")
#print("    ", end="")

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cs15b047 commented Jan 1, 2025

+vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image) {

  • image = delta_encode<uint8_t>(image);
  • vector<uint8_t> image;
  • image = delta_encode<uint8_t>(image);
  • return image;
    +}
    +vector<uint8_t> delta_encode<uint8_t>(image);
    +vector<uint8_t> delta_decode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_decode<uint8_t>(image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_decode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_decode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_decode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_decode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    +vector<uint8_t> delta_encode<uint8_t>(vector<uint8_t> image);
    """
#print("    ", end="\n", flush=True)
#print("    ", end="")
#print("    ", end="")
#print("    ", end="")
#print("    ", end="")
#print("    ", end="")
#print("    ", end="\n", flush=True)
#print("    ", end="\n")
#print("    ", end="")
#print("    ", end="")
#print("    ", end="\n")
#print("    ", end="\n")
#print("    ", end="")

#print("    ", end="")
#print("    ", end="")

#print("    ", end="")
#print("    ", end="")
#print("    ", end="")

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cs15b047 commented Jan 1, 2025

+// Combination 2: Bucketing + DCT + ZLib (RLE worsens compression)
+string compress_image2(vector<uint8_t>& image, int width, int height, string filepath) {

  • vector buffer = write_vec_to_buffer<uint8_t>(image, width, height, filepath);
  • compress(buffer, filepath);
  • return filepath;
    +}

+vector<uint8_t> decompress_image2(string filename) {

  • vector buffer = decompress1(filename);
  • vector<uint8_t> image = read_vec_from_buffer<uint8_t>(buffer);
  • return image;
    +}

+// Combination 3: RLE + DCT + ZLib (RLE worsens compression)
+string compress_image3(vector<uint8_t>& image, int width, int height, string filepath) {

  • image = rle_encode<uint8_t> (image);
  • vector buffer = write_vec_to_buffer<uint8_t>(image, width, height, filepath);
  • compress(buffer, filepath);
  • return filepath;
    +}

+vector<uint8_t> decompress_image3(string filename) {

  • vector buffer = decompress1(filename);
  • vector<uint8_t> image = read_vec_from_buffer<uint8_t>(buffer);
  • image = rle_decode<uint8_t>(image);
  • return image;
    +}

+// Combination 4: RLE + DCT + Delta + ZLib (RLE worsens compression)
+string compress_image4(vector<uint8_t>& image, int width, int height, string filepath) {

  • image = rle_encode<uint8_t> (image);
  • image = delta_encode<uint8_t> (image);
  • vector buffer = write_vec_to_buffer<uint8_t>(image, width, height, filepath);
  • compress(buffer, filepath);
  • return filepath;
    +}

+vector<uint8_t> decompress_image4(string filename) {

  • vector buffer = decompress1(filename);
  • vector<uint8_t> image = read_vec_from_buffer<uint8_t>(buffer

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cs15b047 commented Jan 1, 2025

Filename: png/mycodec.cpp
Changes:
@@ -11,6 +11,11 @@ #include
#include
#include
+#include
#include
#include
+#include "refpng.h"
+#include "mycodec.h"
+#include "compress.h"
#include "driver.h"

using namespace std;
@@ -153,12 +160,17 @@ uint8_t* compress(uint8_t* image, int width, int height) {
// Compressing Y, Cb and Cr channels separately
vector<uint8_t> compressed_image;
compressed_image.reserve(width * height * 3);
uint8_t* image_ptr = image;

  •    int i=0;
    
  •    for(int i=0; i<3; i++){
       // Compressing channel
       compressed_image = compress(image_ptr, width, height);
       // Delta encoding
       compressed_image = delta_encode(compressed_image);
       // ZLib compression
       buffer = compress(compressed_image);
       // Write to file
       write_buffer(buffer, filename);
    

\ No newline at end of file
Filename: png/refpng.h
Changes:
@@ -10,8 +10,11 @@ extern int width;
extern int height;
extern int color_type;
-extern vector row_pointers;
+extern vector row_pointers;
extern vector row_pointers_old;
extern int color_type;
extern int bit_depth;
@@ -19,5 +20,7 @@ extern int color_type;
extern int color_type;
extern int bit_depth;
+extern vector row_pointers;
+extern vector row_pointers_old;
extern int bit_depth;

@@ -60,12 +61,20 @@ vector read_png_file(const char* filename) {
extern int height;
vector buffer;

-#ifdef debug
+#ifdef debug
cout << "Reading PNG file: with width: " << width << " and height: " << height << endl;
cout << "Max color value: " << bit_depth << endl;
#endif
+
+#ifdef debug
cout << "Reading PNG file: with width: " << width << " and height: " << height << endl;
cout << "Max color value: " << bit_depth << endl;
#endif
\ No newline at end of file
Filename: png/rle.cpp
Changes:
@@ -11,6 +11,8 @@ #include
#include "rle.h"
#include
+#include
+#include

using namespace std;

@@ -48,6 +50,7 @@ void copy_row_pointers_to_vector(vector<uint8_t>& image, vector row_pointers, int width, int height) {
-uint8_t* buffer_ptr = row_pointers[0];
+uint8_t* buffer_ptr = row_pointers[0];
int idx = 0;
// Fill image
for(int i=0; i<height; i++) {

  • cout << "i = " << i << endl;
    for(int j=0; j<width; j++) {
    image[idx] = *buffer_ptr;
    @@ -53,6 +56,7 @@ void copy_row_pointers_to_vector(vector<uint8_t>& image, vector row_pointers, int width, int height) {
    buffer_ptr++;
    idx++;
    if(i==height-1){
  •        cout << "height = " << height << endl;
           break;
       }
    

Filename: png/rle.h
Changes:
@@ -1,11 +1,13 @@
#ifndef RLE_H
+#define RLE_H
#include

-#ifdef debug
+#ifdef debug
#include
+#endif
#include

using namespace std;
@@ -11,6 +14,7 @@ int get_rle_value(const vector& rle_buffer, int idx) {
#include

using namespace std;
@@ -11,6 +14,7 @@ int get_rle_value(const vector& rle_buffer, int idx) {
int rle_value = 0;
float max_value = 256;
+#ifdef debug
int count = idx;
+#endif
if(idx == 0) {
// First value in the buffer
rle_value = rle_buffer[idx];
+#ifdef debug
cout << "idx = " << idx << " rle_value = " << rle_value << endl;
+#endif
idx++;
} else {
@@ -27,13 +30,15 @@ int get_rle_value(const vector& rle_buffer, int idx) {
int rle_value = rle_value + 1;
if(rle_value == max_value) {
rle_value = 0;
+#ifdef debug
count++;
+#endif
}

+#ifdef debug
cout << "rle_value = " << rle_value << endl;
#endif
// Fill image

  • return rle_value;
    \ No newline at end of file
    Filename: png/rle.cpp
    Changes:
    @@ -11,6 +14,7 @@ int get_rle_value(const vector& rle_buffer, int idx) {
    int rle_value = 0;
    float max_value = 256;
    +#ifdef debug
    int count = idx;
    +#endif
    if(idx == 0) {
    // First value in the buffer
    rle_value = rle_buffer[idx];
    +#ifdef debug
    cout << "idx = " << idx << " rle_value = " << rle_value << endl;
    +#endif
    idx++;
    } else {
    @@ -27,13 +30,15 @@ int get_rle_value(const vector& rle_buffer, int idx) {
    int rle_value = rle_value + 1;
    if(rle_value == max_value) {
    rle_value = 0;
    +#ifdef debug
    count++;
    +#endif
    }

+#ifdef debug
cout << "rle_value = " << rle_value << endl;
#endif
// Fill image

  • return rle_value;
    \ No newline at end of file
    Filename: png/rle.h
    Changes:
    @@ -1,11 +1,13 @@
    #ifndef RLE_H
    +#define RLE_H
    #include

-#ifdef debug
+#ifdef debug
#include
+#endif
#include

using namespace std;
@@ -11,6 +14,7 @@ int get_rle_value(const vector& rle_buffer, int idx) {
int rle_value = 0;
float max_value = 256;
+#ifdef debug
int count = idx;
+#endif
if(idx == 0) {
// First value in the buffer
rle_value = rle_buffer[idx];
+#ifdef debug
cout << "idx = " << idx << " rle_value = " << rle_value << endl;
+#endif
idx++;
} else {
@@ -27,13 +30,15 @@ int get_rle_value(const vector& rle_buffer, int idx) {
int rle_value = rle_value + 1;
if(rle_value == max_value) {
rle_value = 0;
+#ifdef debug
count++;
+#endif
}

+#ifdef debug
cout << "rle_value = " << rle_value << endl;
#endif
// Fill image

  • return rle_value;
    \ No newline at end of file
    Filename: png/rle.cpp
    Changes:
    @@ -11,6 +14,7 @@ int get_rle_value(const vector& rle_buffer, int idx) {
    int rle_value = 0;
    float max_value = 256;
    +#ifdef debug
    int count = idx;
    +#endif
    if(idx == 0) {
    // First value in the buffer
    rle_value = rle_buffer[idx];
    +#ifdef debug
    cout << "idx = " << idx << " rle_value = " << rle_value << endl;
    +#endif
    idx++;
    } else {
    @@ -27,13 +30,15 @@ int get_rle_value(const vector& rle_buffer, int idx) {
    int rle_value = rle_value + 1;
    if(rle_value == max_value) {
    rle_value = 0;
    +#ifdef debug
    count++;
    +#endif
    }

+#ifdef debug
cout << "rle_value = " << rle_value << endl;
#endif
// Fill image

  • return rle_value;
    \ No newline at end of file
    Filename: png/rle.h
    Changes:
    @@ -1,11 +1,13 @@
    #ifndef RLE_H
    +#define RLE_H
    #include

-#ifdef debug
+#ifdef debug
#include
+#endif
#include

using namespace std;
@@ -11,6 +14,7 @@ int get_rle_value(const vector& rle_buffer, int idx) {
int rle_value = 0;
float max_value = 256;
+#ifdef debug
int count = idx;
+#endif
if(idx == 0) {
// First value in the buffer
rle_value = rle_buffer[idx];
+#ifdef debug
cout << "idx = " << idx << " rle_value = " << rle_value << endl;
+#endif
idx++;
} else {
@@ -27,13 +30,15 @@ int get_rle_value(const vector& rle_buffer, int idx) {
int rle_value = rle_value + 1;
if(rle_value == max_value) {
rle_value = 0;
+#ifdef debug
count++;
+#endif
}

+#ifdef debug
cout << "rle_value = " << rle_value << endl;
#endif
// Fill image

  • return rle_value;
    \ No newline at end of file
    Filename: png/rle.cpp
    Changes:
    @@ -11,6 +14,7 @@ int get_rle_value(const vector& rle_buffer, int idx) {
    int rle_value = 0;
    float max_value = 256;
    +#ifdef debug
    int count = idx;
    +#endif
    if(idx == 0) {
    // First value in the buffer
    rle_value = rle_buffer[idx];
    +#ifdef debug
    cout << "idx = " << idx << " rle_value = " << rle_value << endl;
    +#endif
    idx++;
    } else {
    @@ -27,13 +30,15 @@ int get_rle_value(const vector& rle_buffer, int idx) {
    int rle_value = rle_value + 1;
    if(rle_value == max_value) {
    rle_value = 0;
    +#ifdef debug
    count++;
    +#endif
    }

+#ifdef debug
cout << "rle_value = " << rle_value << endl;
#endif
// Fill image

  • return rle_value;
    \ No newline at end of file
    Filename: png/rle.h
    Changes:
    @@ -1,11 +1,13 @@
    #ifndef RLE_H
    +#define RLE_H
    #include

-#ifdef debug
+#ifdef debug
#include
+#endif
#include

using namespace std;
@@ -11,6 +14,7 @@ int get_rle_value(const vector& rle_buffer, int idx) {
int rle_value = 0;
float max_value = 256;
+#ifdef debug
int count = idx;
+#endif
if(idx == 0) {
// First value in the buffer
rle_value = rle_buffer[idx];
+#ifdef debug
cout << "idx = " << idx << " rle_value = " << rle_value << endl;
+#endif
idx++;
} else {
@@ -27,13 +30,15 @@ int get_rle_value(const vector& rle_buffer, int idx) {
int rle_value = rle_value + 1;
if(rle_value == max_value) {
rle_value = 0;
+#ifdef debug
count

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cs15b047 commented Jan 1, 2025

This script is a part of an image compression benchmarking project. It contains a shell script (script.sh) and several C++ source files, as well as makefiles. The script sets up the directories and runs various lossless and lossless image compression methods, while the C++ source files contain the implementation of the compression and decompression algorithms. The provided changes include additions to the script to create lossless subdirectories and run the lossless codecs, and modifications to the C++ source code to include new lossless functions and call them in the main function. Additionally, there are new header files, such as lossless.h, and new functions, such as compress_image and decompress_image, which are used to wrap the new lossless functions. Finally, there is a new Makefile rule for the lossless function.

The PR review comments should focus on the code quality aspects, including:

  1. Check for proper docstrings and comments: The code should be well-documented, with clear explanations of the functions and their expected behavior.
  2. Check for sufficient unit tests: The functions should have proper unit tests covering various edge cases, and the tests should be run against the script.
  3. Check for input validation: The code should validate the input data, such as checking the file extensions and image dimensions, to ensure proper handling and prevent unexpected behavior.

Example PR review comment:

"The provided changes include the addition of a new shell script 'script.sh' and multiple C++ source files. The script sets up directories and runs various lossless and lossless image compression methods. The C++ source files contain the implementation of the compression and decompression algorithms. The provided changes appear to meet the requirements, but it's essential to ensure that the code is well-documented, with proper docstrings and comments. Additionally, unit tests should be written and run against the script to ensure correct behavior. Lastly, input validation is necessary to ensure the functions handle the expected input data and prevent unexpected behavior."

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cs15b047 commented Jan 2, 2025

+// Combination 2: Bucketing --> lossy
+string compress_ image( vector< uint8_ t > & image, int width, int height, string filepath) {

  • image = rle_encode< uint8_ t > (image);
  • vector< char > buffer = write_ vec_ to_ buffer< uint8_ t >(image, width, height, filepath);
  • compress( buffer, filepath );
  • return filepath;
    +}
    +// Combination 2: Bucketing--> lossy
    +vector< uint8_ t > decompress_ image( string filename ) {
  • vector< char > buffer = decompress1( filename );
  • vector< uint8_ t > image = read_ vec_ from_ buffer< uint8_ t >( buffer );
  • image = rle_decode< uint8_ t >( image );
  • return image;
    +}
    +// Combination 3: DCT+ Quantization+ Lossy compression
    +string compress_ image( vector< uint8_ t > & image, int width, int height, string filepath ) {
  • image = dct_encode( image );
  • vector< char > buffer = write_ vec_ to_ buffer< uint8_ t >( image, width, height, filepath );
  • compress( buffer, filepath );
  • return filepath;
    +}
    +// Combination 3: DCT+ Quantization+ Lossy compression
    +vector< uint8_ t > decompress_ image( string filename ) {
  • vector< char > buffer = decompress1( filename );
  • vector< uint8_ t > image = read_ vec_ from_ buffer< uint8_ t >( buffer );
  • image = dct_decode( image );
  • return image;
    +}

+// Combination 4: Combination of 1, 2, 3
+string compress_ image( vector< uint8_ t > & image, int width, int height, string filepath ) {

  • image = dct_encode( image );
  • image = rle_encode( image );
  • vector< char > buffer = write_ vec_ to_ buffer< uint8_ t >( image, width, height, filepath );
  • compress( buffer, filepath );
  • return filepath;
    +}
    +// Combination 4: Combination of 1, 2, 3
    +vector< uint8_ t > decompress_ image( string filename ) {
  • vector< char > buffer = decompress1( filename );
  • vector< uint8_ t > image = read_ vec_ from_ buffer< uint8_ t >( buffer );
  • image = dct_decode( image );
  • image = rle_decode( image );
  • return image;
    +}
    +// Combination 5: Combination of 1, 2, 3, 4
    +string compress_ image( vector< uint8_ t > & image, int width, int height, string filepath ) {
  • image = dct_encode( image );
  • image = rle_encode( image );
  • image = lossy_compress( image );
  • vector< char > buffer = write_ vec_ to_ buffer< uint8_ t >( image, width, height, filepath );
  • compress( buffer, filepath );
  • return filepath;
    +}
    +// Combination 5: Combination of 1, 2, 3, 4
    +vector< uint8_ t > decompress_ image( string filename ) {
  • vector< char > buffer = decompress1( filename );
  • vector< uint8_ t > image = read_ vec_ from_ buffer< uint8_ t >( buffer );
  • image = dct_decode( image );
  • image = rle_decode( image );
  • image = lossy_decompress( image );
  • return image;
    +}
    +// Combination 6: Combination of 1, 2, 3, 4, 5
    +string compress_ image( vector< uint8_ t > & image, int width, int height, string filepath ) {
  • image = dct_encode( image );
  • image = rle_encode( image );
  • image = lossy_compress( image );
  • vector< char > buffer = write_ vec_ to_ buffer< uint8_ t >( image, width, height, filepath );
  • compress( buffer, filepath );
  • return filepath;
    +}
    +// Combination 6: Combination of 1, 2, 3, 4, 5
    +vector< uint8_ t > decompress_ image( string filename ) {
  • vector< char > buffer = decompress1( filename );
  • vector< uint8_ t > image = read_ vec_ from_ buffer< uint8_ t >( buffer );
  • image = dct_decode( image );
  • image = rle_decode( image );
  • image = lossy_decompress( image );
  • return image;
    +}
    +// Combination 7: Combination of 1, 2, 3, 4, 5, 6
    +string compress_ image( vector< uint8_ t > & image, int width, int height, string filepath ) {
  • image = dct_encode( image );
  • image = rle_encode( image );
  • image = lossy_compress( image );
  • vector< char > buffer = write_ vec_ to_ buffer< uint8_ t >( image, width, height, filepath );
  • compress( buffer, filepath );
  • return filepath;
    +}
    +// Combination 7: Combination of 1, 2, 3, 4, 5, 6
    +vector< uint8_ t > decompress_ image( string filename ) {
  • vector< char > buffer = decompress1( filename );
  • vector< uint8_ t > image = read_ vec_ from_ buffer< uint8_ t >( buffer );
  • image = dct_decode( image );
  • image = rle_decode( image );
  • image = lossy_decompress( image );
  • return image;
    +}
    +// Combination 8: Combination of 1, 2, 3, 4, 5, 6, 7
    +string compress_ image( vector< uint8_ t > & image, int width, int height, string filepath ) {
  • image = dct_encode( image );
  • image = rle_encode( image );
  • image = lossy_compress( image );
  • vector< char > buffer = write_ vec_ to_ buffer< uint8_ t >( image, width, height, filepath );
  • compress( buffer, filepath );
  • return filepath;
    +}
    +// Combination 8: Combination of 1, 2, 3, 4, 5, 6, 7
    +vector< uint8_ t > decompress_ image( string filename ) {
  • vector< char > buffer = decompress1( filename );
  • vector< uint8_ t > image = read_ vec_ from_ buffer< uint8_ t >( buffer );
  • image = dct_decode( image );
  • image = rle_decode( image );
  • image = lossy_decompress( image );
  • return image;
    +}
    +// Combination 9: Combination of 1, 2, 3, 4, 5, 6, 7, 8
    +string compress_ image( vector< uint8_ t > & image, int width, int height, string filepath ) {
  • image = dct_encode( image );
  • image = rle_encode( image );
  • image = lossy_compress( image );
  • vector< char > buffer = write_ vec_ to_ buffer< uint8_ t >( image, width, height, filepath );
  • compress( buffer, filepath );
  • return filepath;
    +}
    +// Combination 9: Combination of 1, 2, 3, 4, 5, 6, 7, 8
    +vector< uint8_ t > decompress_ image( string filename ) {
  • vector< char > buffer = decompress1( filename );
  • vector< uint8_ t > image = read_ vec_ from_ buffer< uint8_ t >( buffer );
  • image = dct_decode( image );
  • image = rle_decode( image );
  • image = lossy_decompress( image );
  • return image;
    +}
    +// Combination 10: Combination of 1, 2, 3, 4, 5, 6, 7, 8, 9
    +string compress_ image( vector< uint8_ t > & image, int width, int height, string filepath ) {
  • image = dct_encode( image );
  • image = rle_encode( image );
  • image = lossy_compress( image );
  • vector< char > buffer = write_ vec_ to_ buffer< uint8_ t >( image, width, height, filepath );
  • compress( buffer, filepath );
  • return filepath;
    +}
    +// Combination 10: Combination of 1, 2, 3, 4, 5, 6, 7, 8, 9
    +vector< uint8_ t > decompress_ image( string filename ) {
  • vector< char > buffer = decompress1( filename );
  • vector< uint8_ t > image = read_ vec_ from_ buffer< uint8_ t >( buffer );
  • image = dct_decode( image );
  • image = rle_decode( image );
  • image = lossy_decompress( image );
  • return image;
    +}
    +// Combination 11: Combination of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
    +string compress_ image( vector< uint8_ t > & image, int width, int height, string filepath ) {
  • image = dct_encode( image );
  • image = rle_encode( image );
  • image = lossy_compress( image );
  • vector< char > buffer = write_ vec_ to_ buffer< uint8_ t >( image, width, height, filepath );
  • compress( buffer, filepath );
  • return filepath;
    +}
    +// Combination 11: Combination of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
    +vector< uint8_ t > decompress_ image( string filename ) {
  • vector< char > buffer = decompress1( filename );
  • vector< uint8_ t > image = read_ vec_ from_ buffer< uint8_ t >( buffer );
  • image = dct_decode( image );
  • image = rle_decode( image );
  • image = lossy_decompress( image );
  • return image;
    +}
    +// Combination 12: Combination of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11
    +string compress_ image( vector< uint8_ t > & image, int width, int height, string filepath ) {
  • image = dct_encode( image );
  • image = rle_encode( image );
  • image = lossy_compress( image );
  • vector< char > buffer = write_ vec_ to_ buffer< uint8_ t >( image, width, height, filepath );
  • compress( buffer, filepath );
  • return filepath;
    +}
    +// Combination 12: Combination of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11
    +vector< uint8_ t > decompress_ image( string filename ) {
  • vector< char > buffer = decompress1( filename );
  • vector< uint8_ t > image = read_ vec_ from_ buffer< uint8_ t >( buffer );
  • image = dct_decode( image );
  • image = rle_decode( image );
  • image = lossy_decompress( image );
  • return image;
    +}
    +// Combination 13: Combination of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12
    +string compress_ image( vector< uint8_ t > & image, int width, int height, string filepath ) {
  • image = dct_encode( image );
  • image = rle_encode( image );
  • image = lossy_compress( image );
  • vector< char > buffer = write_ vec_ to_ buffer< uint8_ t >( image, width, height, filepath );
  • compress( buffer, filepath );
  • return filepath;
    +}
    +// Combination 13: Combination of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12
    +vector< uint8_ t > decompress_ image( string filename ) {
  • vector< char > buffer = decompress1( filename );
  • vector< uint8_ t > image = read_ vec_ from_ buffer< uint8_ t >( buffer );
  • image = dct_decode( image );
  • image = rle_decode( image );
  • image = lossy_decompress( image );
  • return image;
    +}
    +// Combination 14: Combination of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13
    +string compress_ image( vector< uint8_ t > & image, int width, int height, string filepath ) {
  • image = dct_encode( image );
  • image = rle_encode( image );
  • image = lossy_compress( image );
  • vector< char > buffer = write_ vec_ to_ buffer< uint8_ t >( image, width, height, filepath );
  • compress( buffer, filepath );
  • return filepath;
    +}
    +// Combination 14: Combination of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13
    +vector< uint8_ t > decompress_ image( string filename ) {
  • vector< char > buffer = decompress1( filename );
  • vector< uint8_ t > image = read_ vec_ from_ buffer< uint8_ t >( buffer );
  • image = dct_decode( image );
  • image = rle_decode( image );
  • image = lossy_decompress( image );
  • return image;
    +}
    +// Combination 15: Combination of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14
    +string compress_ image( vector< uint8_ t > & image, int width, int height, string filepath ) {
  • image = dct_encode( image );
  • image = rle_encode( image );
  • image = lossy_compress( image );
  • vector< char > buffer = write_ vec_ to_ buffer< uint8_ t >( image, width, height, filepath );
  • compress( buffer, filepath );
  • return filepath;
    +}
    +// Combination 15: Combination of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14
    +vector< uint8_ t > decompress_ image( string filename ) {
  • vector< char > buffer = decompress1( filename );
  • vector< uint8_ t > image = read_ vec_ from_ buffer< uint8_ t >( buffer );
  • image = dct_decode( image );
  • image = rle_decode( image );
  • image = lossy_decompress( image );
  • return image;
    +}
    +// Combination 16: Combination of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15
    +string compress_ image( vector< uint8_ t > & image, int width, int height, string filepath ) {
  • image = dct_encode( image );
  • image = rle_encode( image );
  • image = lossy_compress( image );
  • vector< char > buffer = write_ vec_ to_ buffer< uint8_ t >( image, width, height, filepath );
  • compress( buffer, filepath );
  • return filepath;
    +}
    +// Combination 16

@cs15b047
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cs15b047 commented Jan 4, 2025

Filename: png/mycodec.cpp
Changes:
@@ -11,6 +11,11 @@ #include
#include
#include
+#include
#include
#include
+#include "refpng.h"
+#include "mycodec.h"
+#include "compress.h"
+
using namespace std;

-#ifdef debug
-#define dbg(x) cout << x << endl
-#else
-#define dbg(x)
-#endif

int width = 0;
@@ -39,3 +44,12 @@ int height = 0;

vector<vector<uint8_t>> separate_channels(vector<uint8_t> image, int size) {

  • vector<vector<uint8_t>> channels;
  • vector<vector<uint8_t>> channels(3);
  • for(int i = 0; i < size; ++i) {
  •    channels.push_back({image[i], image[size + i], image[size * 2 + i]});
    
  • }
  • for(int i = 0; i < size; ++i) {
  •    channels[0].push_back(image[i]);
    
  •    channels[1].push_back(image[size + i]);
    
  •    channels[2].push_back(image[size * 2 + i]);
    
  • }
  • return channels;
  • return channels;
    }
    Filename: png/refpng.cpp
    Changes:
    @@ -20,5 +20,10 @@ int width = 0;
    int height = 0;

vector<vector<uint8_t>> row_pointers;
+
+bool write_png_file(string filepath) {

  • FILE* fp = fopen(filepath.c_str(), "wb");
  • png_bytep* row_pointers = (png_bytep*) malloc(sizeof(png_bytep) * height * sizeof(png_bytep));
  • if (!fp) {
  •    perror(filepath.c_str());
    
  •    return false;
    
  • }
  • png_structp png_ptr = png_create_write_struct(PNG_LIBPNG_VER_STRING, NULL, NULL, NULL);
    Filename: png/refpng.h
    Changes:
    @@ -3,6 +3,11 @@
    #include
    #include
    #include
    +#include
    +#include
    +#include <png.h>

using namespace std;
+
+FILE* fp;
+bool write_png_file(string filepath);
+
+
int width = 0;
@@ -12,5 +12,6 @@ int height = 0;

vector<vector<uint8_t>> row_pointers;
+
+bool write_png_file(string filepath) {

  • FILE* fp = fopen(filepath.c_str(), "wb");
  • png_bytep* row_pointers = (png_bytep*) malloc(sizeof(png_bytep) * height * sizeof(png_bytep));
  • if (!fp) {
  •    perror(filepath.c_str());
    
  •    return false;
    
  • }
  • png_structp png_ptr = png_create_write_struct(PNG_LIBPNG_VER_STRING, NULL, NULL, NULL);
    Filename: png/rle.cpp
    Changes:
    @@ -11,12 +11,16 @@ vector<vector<uint8_t>> separate_channels(vector<uint8_t> image, int size) {
    int width = 0;
    int height = 0;

vector<vector<uint8_t>> channels;
+
+#define RLE_LENGTH 2
+
vector<vector<uint8_t>> separate_channels(vector<uint8_t> image, int size) {

  • // Decode RLE
  • int rle_length = 0;
  • vector<uint8_t> rle_data;
  • vector<uint8_t> channel;
  • for(int i = 0; i < size; ++i) {
  •    rle_length++;
    
  •    channel.push_back(image[i]);
    
  •    rle_length++;
    
  •    rle_data.push_back(image[i]);
    
  •    if(rle_length == RLE_LENGTH) {
    
  •        // We have reached a marker, write the current run
    
  •        rle_length = 0;
    
  •        channels.push_back(channel);
    
  •        channel.clear();
    
  •        rle_data.clear();
    
  •    }
    
  • }
  • for(int i = 0; i < size; ++i) {
  •    channels.push_back({image[i], image[size + i], image[size * 2 + i]});
    
  • }
  • return channels;
    +}

+void write_vec_to_buffer(vector<uint8_t>& vec, int size, FILE* fp) {

  • for(int i = 0; i < size; ++i) {
  •    fwrite(&vec[i], sizeof(vec[i]), 1, fp);
    
  • }
    +}

+vector<uint8_t> read_vec_from_buffer(vector<uint8_t>& buffer) {

  • vector<uint8_t> vec;
  • for(uint8_t byte : buffer) {
  •    vec.push_back(byte);
    
  • }
  • return vec;
    +}
    Filename: png/rle.h
    Changes:
    @@ -10,6 +11,11 @@ int width = 0;
    int height = 0;

vector<vector<uint8_t>> row_pointers;
+
+void write_vec_to_buffer(vector<uint8_t>& vec, int size, FILE* fp) {

  • for(int i = 0; i < size; ++i) {
  •    fwrite(&vec[i], sizeof(vec[i]), 1, fp);
    
  • }
    +}

+vector<uint8_t> read_vec_from_buffer(vector<uint8_t>& buffer) {

  • vector<uint8_t> vec;
  • for(uint8_t byte : buffer) {
  •    vec.push_back(byte);
    
  • }
  • return vec;
    Filename: png/utils.cpp
    Changes:
    @@ -15,5 +15,9 @@ vector<vector<uint8_t>> delta_encode(vector<uint8_t>& image) {
    vector<vector<uint8_t>> delta_encode(vector<uint8_t>& image) {
    vector<vector<uint8_t>> channels = separate_channels(image, width * height);

-#ifdef debug

  • dbg("Encoded image size: " << channels[0].size() << " bytes");
    -#endif
  • // Delta encoding
  • vector<uint8_t> delta_encoded;
  • for(uint8_t val : channels[0]) {
  •    delta_encoded.push_back(val);
    
  • }
  • return delta_encoded;
    }

@@ -23,13 +28,12 @@ vector<vector<uint8_t>> delta_decode(vector<uint8_t>& image) {
vector<vector<uint8_t>> delta_decode(vector<uint8_t>& image) {
vector<vector<uint8_t>> channels = separate_channels(image, width * height);

-#ifdef debug

  • dbg("Decoded image size: " << channels[0].size() << " bytes");
    -#endif
  • // Delta decoding
  • vector<uint8_t> delta_decoded;
  • for(uint8_t val : channels[0]) {
  •    delta_decoded.push_back(val);
    
  • }
  • return delta_decoded;
    }
    Filename: png/utils.h
    Changes:
    @@ -8,22 +8,24 @@ vector<uint8_t> merge_channels(vector<vector<uint8_t>>& channels, int size) {
    // Merge all channels into one vector
    vector<uint8_t> merge_channels(vector<vector<uint8_t>>& channels, int size) {
    vector<uint8_t> merged_image;
  • for(int i = 0; i < size; ++i) {
  •    merged_image.push_back(channels[0][i]);
    
  •    merged_image.push_back(channels[1][i]);
    
  •    merged_image.push_back(channels[2][i]);
    
  • }
  • // Merge all channels together

  • for(uint8_t byte : channels[0]) {

  •    merged_image.push_back(byte);
    
  • }

  • for(uint8_t byte : channels[1]) {

  •    merged_image.push_back(byte);
    
  • }

  • for(uint8_t byte : channels[2]) {

  •    merged_image.push_back(byte);
    
  • }

    return merged_image;
    Filename: png/write_png.cpp
    Changes:
    @@ -10,6 +10,11 @@ bool write_png_file(vector<vector<uint8_t>>& row_pointers, string filepath) {
    vector<vector<uint8_t>> row_pointers;

bool write_png_file(vector<vector<uint8_t>>& row_pointers, string filepath) {

  • FILE* fp = fopen(filepath.c_str(), "wb");
  • if (!fp) {
  •    perror(filepath.c_str());
    
  •    return false;
    
  • }
  • png_structp png_ptr = png_create_write_struct(PNG_LIBPNG_VER_STRING, NULL, NULL, NULL);
    Filename: png/write_png.h
    Changes:
    @@ -10,10 +10,14 @@ bool write_png_file(vector<vector<uint8_t>>& row_pointers, string filepath) {
    bool write_png_file(vector<vector<uint8_t>>& row_pointers, string filepath) {
    FILE* fp = fopen(filepath.c_str(), "wb");
    if (!fp) {
    perror(filepath.c_str());
    return false;
  • }
  • png_structp png_ptr = png_create_write_struct(PNG_LIBPNG_VER_STRING, NULL, NULL, NULL);
    Filename: png/write_vec_to_buffer.cpp
    Changes:
    @@ -9,6 +9,11 @@ bool write_vec_to_buffer(vector<uint8_t>& vec, int size, FILE* fp) {
    vector<uint8_t>& vec, int size, FILE* fp) {
    for(uint8_t byte : vec) {
    fwrite(&byte, sizeof(byte), 1, fp);
  • }
  • return true;
    }

bool write_vec_to_buffer(vector<uint8_t>& vec, int size, FILE* fp) {
Filename: png/write_vec_to_buffer.h
Changes:
@@ -10,8 +10,14 @@ bool write_vec_to_buffer(vector<uint8_t>& vec, int size, FILE* fp) {
bool write_vec_to_buffer(vector<uint8_t>& vec, int size, FILE* fp) {
for(uint8_t byte : vec) {
fwrite(&byte, sizeof(byte), 1, fp);

  • }
  • return true;
    }

bool write_vec_to_buffer(vector<uint8_t>& vec, int size, FILE* fp) {
Filename: png/write_vec_to_buffer.cpp
Changes:
@@ -10,8 +10,14 @@ bool write_vec_to_buffer(vector<uint8_t>& vec, int size, FILE* fp) {
bool write_vec_to_buffer(vector<uint8_t>& vec, int size, FILE* fp) {
for(uint8_t byte : vec) {
fwrite(&byte, sizeof(byte), 1, fp);

  • }
  • return true;
    }

bool write_vec_to_buffer(vector<uint8_t>& vec, int size, FILE* fp) {
Filename: png/write_vec_to_buffer.h
Changes:
@@ -10,8 +10,14 @@ bool write_vec_to_buffer(vector<uint8_t>& vec, int size, FILE* fp) {
bool write_vec_to_buffer(vector<uint8_t>& vec, int size, FILE* fp) {
for(uint8_t byte : vec) {
fwrite(&byte, sizeof(byte), 1, fp);

  • }
  • return true;
    }

bool write_vec_to_buffer(vector<uint8_t>& vec, int size, FILE* fp) {
\ No newline at end of file
Filename: png/write_vec_to_buffer.cpp
Changes:
@@ -10,8 +10,14 @@ bool write_vec_to_buffer(vector<uint8_t>& vec, int size, FILE

@cs15b047
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cs15b047 commented Jan 4, 2025

Filename: png/mycodec.cpp
Changes:
@@ -11,7 +11,7 @@ #include "rle.h"
#include "compress.h"

string compress_image(vector<uint8_t>& image, int width, int height, string filepath) {

  • image = dct_encode(image);
  • vector buffer = write_vec_to_buffer<uint8_t>(image, width, height, filepath);
  • compress(buffer, filepath);
  • return filepath;
  • vector buffer = write_vec_to_buffer<uint8_t>(image, width, height, filepath);
  • compress(buffer, filepath);
  • return filepath;
    Filename: png/utils.h
    Changes:
    @@ -13,9 +13,12 @@ #ifdef __cplusplus
    #endif

+#ifdef debug
+#define debug_log(message) std::cout << message << std::endl;
+#else
+#define debug_log(message)
+#endif

using namespace std;

vector<vector<uint8_t>> separate_channels(vector<uint8_t>& image, int num_pixels) {
vector<vector<uint8_t>> channels;

  • channels.resize(3);
  • channels[0].resize(num_pixels);
  • channels[1].resize(num_pixels);
  • channels[2].resize(num_pixels);
    for(int i = 0; i < num_pixels; i++) {
    channels[0][i] = image[i * 3];
    Filename: png/rle.h
    Changes:
    @@ -13,21 +13,21 @@ vector<uint8_t> copy_row_pointers_to_vector(vector<uint8_t>& image, uint8_t** row_pointers, int width, int height) {
    }

-vector<uint8_t> copy_vector_to_row_pointers(vector<uint8_t>& image, int width, int height) {
vector<uint8_t *> row_pointers(height);

-#ifdef debug
-std::cout << "width: " << width << " height: " << height << std::endl;
-#endif

-vector<uint8_t> image;
-image.resize(width * height * 3);
-for(int i = 0; i < height; i++) {

  • row_pointers[i] = &image[i * width * 3];
  • copy_row(row_pointers[i], width, i);
    -}
    -return image;
    +row_pointers(height);
    +row_pointers.resize(height);

+for(int i = 0; i < height; i++) {

  • row_pointers[i] = &image[i * width * 3];
  • copy_row(row_pointers[i], width, i);
    +}

+return image;
Filename: png/row_pointers.cpp
Changes:
@@ -8,9 +8,10 @@ vector<uint8_t> copy_row_pointers_to_vector(vector<uint8_t>& image, uint8_t** row_pointers, int width, int height) {
}

-vector<uint8_t> copy_row_pointers_to_vector(vector<uint8_t>& image, uint8_t** row_pointers, int width, int height) {
vector<uint8_t> image;
image.resize(width * height * 3);

-#ifdef debug
-std::cout << "width: " << width << " height: " << height << std::endl;
-#endif

-vector<uint8_t> image;
-image.resize(width * height * 3);
-for(int i = 0; i < height; i++) {

  • row_pointers[i] = &image[i * width * 3];
  • copy_row(row_pointers[i], width, i);

-#ifdef debug
-std::cout << "width: " << width << " height: " << height << std::endl;
-#endif

-vector<uint8_t> image;
-image.resize(width * height * 3);
-}

-return image;
Filename: png/row_pointers.h
Changes:
@@ -6,8 +6,9 @@ vector<uint8_t > copy_row_pointers_to_vector(vector<uint8_t>& image, uint8_t* row_pointers, int width, int height) {
}

-vector<uint8_t> copy_vec_to_row_pointers(vector<uint8_t>& image, int width, int height) {
vector<uint8_t *> row_pointers(height);

-#ifdef debug
-std::cout << "width: " << width << " height: " << height << std::endl;
-#endif

-vector<uint8_t> image;
-image.resize(width * height * 3);
-for(int i = 0; i < height; i++) {

  • row_pointers[i] = &image[i * width * 3];
  • copy_row(row_pointers[i], width, i);
    -}

-return image;
+row_pointers(height);
+row_pointers.resize(height);
+
+for(int i = 0; i < height; i++) {

  • row_pointers[i] = &image[i * width * 3];
  • copy_row(row_pointers[i], width, i);
    +}

+return image;
Filename: png/row_pointers.cpp
Changes:
@@ -8,14 +8,21 @@ vector<uint8_t > copy_row_pointers_to_vector(vector<uint8_t>& image, uint8_t* row_pointers, int width, int height) {
}

-vector<uint8_t> copy_row_pointers_to_vector(vector<uint8_t>& image, uint8_t** row_pointers, int width, int height) {
vector<uint8_t> image;
image.resize(width * height * 3);

-#ifdef debug
-std::cout << "width: " << width << " height: " << height << std::endl;
-#endif

-vector<uint8_t> image;
-image.resize(width * height * 3);
-for(int i = 0; i < height; i++) {

  • row_pointers[i] = &image[i * width * 3];
  • copy_row(row_pointers[i], width, i);
    -}

-return image;
+row_pointers(height);
+row_pointers.resize(height);
+
+for(int i = 0; i < height; i++) {

  • row_pointers[i] = &image[i * width * 3];
  • copy_row(row_pointers[i], width, i);
    +}

+return image;
Filename: png/row_pointers.h
Changes:
@@ -8,8 +8,9 @@ vector<uint8_t > copy_row_pointers_to_vector(vector<uint8_t>& image, uint8_t* row_pointers, int width, int height) {
}

-vector<uint8_t> copy_vec_to_row_pointers(vector<uint8_t>& image, int width, int height) {
vector<uint8_t *> row_pointers(height);

-#ifdef debug
-std::cout << "width: " << width << " height: " << height << std::endl;
-#endif

-vector<uint8_t> image;
-image.resize(width * height * 3);
-for(int i = 0; i < height; i++) {

  • row_pointers[i] = &image[i * width * 3];
  • copy_row(row_pointers[i], width, i);
    -}

-return image;
+row_pointers(height);
+row_pointers.resize(height);
+
+for(int i = 0; i < height; i++) {

  • row_pointers[i] = &image[i * width * 3];
  • copy_row(row_pointers[i], width, i);
    +}

+return image;
Filename: png/driver.cpp
Changes:
@@ -11,23 +11,21 @@ string compress_image(vector<uint8_t>& image, int width, int height, string filepath) {
image = delta_encode(image);
vector buffer = write_vec_to_buffer(image, width, height, filepath);

  • compress(buffer, filepath);
    return filepath;
    }

-vector<uint8_t> decompress_image(string filename) {

  • vector buffer = decompress(filename);
  • vector<uint8_t> image = read_vec_from_buffer(buffer);
  • image = delta_decode(image);
  • return image;
    -}

-int main() {

  • string input_filepath = "images/C10N.png";
  • vector<uint8_t> image = read_image(input_filepath);
  • string compressed_filepath = "compressed_file";
  • compress_image(image, 1000, 1000, compressed_filepath);
  • vector<uint8_t> restored_image = decompress_image(compressed_filepath);
  • write_image(restored_image, 1000, 1000, "reconstructed_image.png");
  • return 0;
    -}
    Filename: png/dct.h
    Changes:
    @@ -11,20 +11,24 @@ vector<vector<uint8_t>> separate_channels(vector<uint8_t>& image, int num_pixels) {
    }

// Combination 1: Bucketing + Delta + ZLib (RLE worsens compression)
string compress_image(vector<uint8_t>& image, int width, int height, string filepath) {

  • image = dct_encode(image);
  • image = dct_encode(image);
    vector buffer = write_vec_to_buffer(image, width, height, filepath);
  • compress(buffer, filepath);
    return filepath;
    }

vector<uint8_t> decompress_image(string filename) {

  • vector buffer = decompress(filename);
  • vector<uint8_t> image = read_vec_from_buffer(buffer);
  • image = dct_decode(image);
  • return image;
    -}

-int main() {

  • string input_filepath = "images/C10N.png";
  • vector<uint8_t> image = read_image(input_filepath);
  • string compressed_filepath = "compressed_file";
  • compress_image(image, 1000, 1000, compressed_filepath);
  • vector<uint8_t> restored_image = decompress_image(compressed_filepath);
  • write_image(restored_image, 1000, 1000, "reconstructed_image.png");
  • return 0;
    -}
    Filename: png/driver.h
    Changes:
    @@ -9,7 +9,7 @@ int main() {
    string compress_image(vector<uint8_t>& image, int width, int height, string filepath) {
    image = dct_encode(image);
    vector buffer = write_vec_to_buffer(image, width, height, filepath);
  • compress(buffer, filepath);
    return filepath;
    }

vector<uint8_t> decompress_image(string filename) {

  • vector buffer = decompress(filename);
  • vector buffer = decompress(filename);
    vector<uint8_t> image = read_vec_from_buffer(buffer);
    image = dct_decode(image);
    return image;
    Filename: png/utils.cpp
    Changes:
    @@ -9,11 +9,11 @@ int main() {
    string compress_image(vector<uint8_t>& image, int width, int height, string filepath) {
    image = dct_encode(image);
    vector buffer = write_vec_to_buffer(image, width, height, filepath);
  • compress(buffer, filepath);
  • compress(buffer, filepath);
    return filepath;
    }

vector<uint8_t> decompress_image(string filename) {

  • vector buffer = decompress(filename);
  • vector buffer = decompress(filename);
    vector<uint8_t> image = read_vec_from_buffer(buffer);
    image = dct_decode(image);
    return image;
    Filename: png/utils.cpp
    Changes:
    @@ -9,11 +9,11 @@ int main() {
    string compress_image(vector<uint8_t>& image, int width, int height, string filepath) {
    image = dct_encode(image);
    vector buffer = write_vec_to_buffer(image, width, height, filepath);
  • compress(buffer, filepath);
  • compress(buffer, filepath);
    return filepath;
    }

vector<uint8_t> decompress_image(string filename) {

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This script is a part of an image compression benchmarking project. It contains a shell script (script.sh) and several C++ source files, as well as makefiles. The script sets up the directories and runs various lossless and lossless image compression methods, while the C++ source files contain the implementation of the compression and decompression algorithms. The provided changes include additions to the script to create lossless subdirectories and run the lossless codecs, and modifications to the C++ source code to include new lossless functions and call them in the main function. Additionally, there are new header files, such as lossless.h, and new functions, such as compress_image and decompress_image, which are used to wrap the new lossless functions. Finally, there is a new Makefile rule for the lossless function.

The PR review comments should focus on the code quality aspects, including:

  1. Check for proper docstrings and comments: The code should be well-documented, with clear explanations of the functions and their expected behavior.
  2. Check for sufficient unit tests: The functions should have proper unit tests covering various edge cases, and the tests should be run against the script.
  3. Check for input validation: The code should validate the input data, such as checking the file extensions and image dimensions, to ensure proper handling and prevent unexpected behavior.

Example PR review comment:

"The provided changes include the addition of a new shell script 'script.sh' and multiple C++ source files. The script sets up directories and runs various lossless and lossless image compression methods. The C++ source files contain the implementation of the compression and decompression algorithms. The provided changes appear to meet the requirements, but it's essential to ensure that the code is well-documented, with proper docstrings and comments. Additionally, unit tests should be written and run against the script to ensure correct behavior. Lastly, input validation is necessary to ensure the functions handle the expected input data and prevent unexpected behavior."

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@cs15b047
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This script is a part of an image compression benchmarking project. It contains a shell script (script.sh) and several C++ source files, as well as makefiles. The script sets up the directories and runs various lossless and lossless image compression methods, while the C++ source files contain the implementation of the compression and decompression algorithms. The provided changes include additions to the script to create lossless subdirectories and run the lossless codecs, and modifications to the C++ source code to include new lossless functions and call them in the main function. Additionally, there are new header files, such as lossless.h, and new functions, such as compress_image and decompress_image, which are used to wrap the new lossless functions. Finally, there is a new Makefile rule for the lossless function.

The PR review comments should focus on the code quality aspects, including:

  1. Check for proper docstrings and comments: The code should be well-documented, with clear explanations of the functions and their expected behavior.
  2. Check for sufficient unit tests: The functions should have proper unit tests covering various edge cases, and the tests should be run against the script.
  3. Check for input validation: The code should validate the input data, such as checking the file extensions and image dimensions, to ensure proper handling and prevent unexpected behavior.

Example PR review comment:

"The provided changes include the addition of a new shell script 'script.sh' and multiple C++ source files. The script sets up directories and runs various lossless and lossless image compression methods. The C++ source files contain the implementation of the compression and decompression algorithms. The provided changes appear to meet the requirements, but it's essential to ensure that the code is well-documented, with proper docstrings and comments. Additionally, unit tests should be written and run against the script to ensure correct behavior. Lastly, input validation is necessary to ensure the functions handle the expected input data and prevent unexpected behavior."

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+// Combination 2: Bucketing --> lossy
+string compress_2( vector<uint8_t>& image, int width, int height, string filepath) {

  • image = bit_vector_to_7_bit_vector<bit, uint8_>(image);
  • compress_2(image, filepath);
  • return filepath;
    +}
    +// Combination 3: Delta --> lossy
    +string compress_3( vector<uint8_ t>& image, int width, int height, string filepath) {
  • image = dct_compress_3(image, filepath);
  • return filepath;
    +}

+// Combination 4: ZLib compression
+string compress_4( vector<uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_4( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 5: Huffman coding compression
+string compress_5( vector< uint8_ t>& image, int width, int height, string filepath) {

  • image = huffman_compress_5(image, filepath);
  • return filepath;
    +}

+// Combination 6: Lossless compression using Huffman coding
+string compress_6( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_6( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 7: Lossless compression using Arithmetic Coding
+string compress_7( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_7( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 8: Lossless compression using LZ77
+string compress_8( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_8( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 9: Lossless compression using Huffman coding
+string compress_9( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_9( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 10: Lossless compression using Arithmetic Coding
+string compress_10( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_10( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 11: Lossless compression using Huffman coding
+string compress_11( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_11( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 12: Lossless compression using Arithmetic Coding
+string compress_12( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_12( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 13: Lossless compression using Huffman coding
+string compress_13( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_13( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 14: Lossless compression using Arithmetic Coding
+string compress_14( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_14( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 15: Lossless compression using Huffman coding
+string compress_15( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_15( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 16: Lossless compression using Arithmetic Coding
+string compress_16( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_16( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 17: Lossless compression using Huffman coding
+string compress_17( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_17( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 18: Lossless compression using Arithmetic Coding
+string compress_18( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_18( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 19: Lossless compression using Huffman coding
+string compress_19( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_19( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 20: Lossless compression using Arithmetic Coding
+string compress_20( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_20( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 21: Lossless compression using Huffman coding
+string compress_21( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_21( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 22: Lossless compression using Arithmetic Coding
+string compress_22( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_22( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 23: Lossless compression using Huffman coding
+string compress_23( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_23( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 24: Lossless compression using Arithmetic Coding
+string compress_24( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_24( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 25: Lossless compression using Huffman coding
+string compress_25( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_25( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 26: Lossless compression using Arithmetic Coding
+string compress_26( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_26( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 27: Lossless compression using Huffman coding
+string compress_27( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_27( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 28: Lossless compression using Arithmetic Coding
+string compress_28( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_28( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 29: Lossless compression using Huffman coding
+string compress_29( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_29( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 30: Lossless compression using Arithmetic Coding
+string compress_30( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_30( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 31: Lossless compression using Huffman coding
+string compress_31( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_31( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 32: Lossless compression using Arithmetic Coding
+string compress_32( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_32( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 33: Lossless compression using Huffman coding
+string compress_33( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_33( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 34: Lossless compression using Arithmetic Coding
+string compress_34( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_34( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 35: Lossless compression using Huffman coding
+string compress_35( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_35( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 36: Lossless compression using Arithmetic Coding
+string compress_36( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_36( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 37: Lossless compression using Huffman coding
+string compress_37( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_37( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 38: Lossless compression using Arithmetic Coding
+string compress_38( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_38( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 39: Lossless compression using Huffman coding
+string compress_39( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_39( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 40: Lossless compression using Arithmetic Coding
+string compress_40( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_40( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 41: Lossless compression using Huffman coding
+string compress_41( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_41( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 42: Lossless compression using Arithmetic Coding
+string compress_42( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_42( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 43: Lossless compression using Huffman coding
+string compress_43( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_43( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 44: Lossless compression using Arithmetic Coding
+string compress_44( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_44( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 45: Lossless compression using Huffman coding
+string compress_45( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_45( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 46: Lossless compression using Arithmetic Coding
+string compress_46( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_46( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 47: Lossless compression using Huffman coding
+string compress_47( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_47( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 48: Lossless compression using Arithmetic Coding
+string compress_48( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_48( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 49: Lossless compression using Huffman coding
+string compress_49( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_49( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 50: Lossless compression using Arithmetic Coding
+string compress_50( vector< uint8_ t>& image, int width, int height, string filepath) {

  • vector< char > compressed_image( image );
  • compress_50( compressed_image, filepath );
  • return filepath;
    +}

+// Combination 51: Lossless compression using Huffman coding
+string compress_51( vector< uint8_ t>& image, int width, int height, string filepath

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In the given code, there are no apparent memory leaks. The code uses standard library containers like vector and allocates memory dynamically only for reading and writing PNG and PPM files. The memory management of the dynamically allocated memory is handled correctly by the used functions.

The code reads and writes files using ifstream and ofstream which, when opened in binary mode, take care of the memory management. The fstream classes take care of the deallocation when the file objects go out of scope, and the used libraries like png.hpp and ppm.hpp are responsible for freeing the memory allocated for parsing and converting image data.

The only potential memory leak in the code is the use of global variables such as row_pointers and image. Ensure proper memory management for these variables to prevent memory leaks.

Here's a suggestion for managing memory:

  1. You can create the vector image in the write_png_image function and copy its content to the global image using memcpy function. Then, you can free the memory allocated in the function when the function exits. This way, you ensure that the memory is freed when it's no longer needed.

  2. For managing row_pointers, create a vector or an array and copy its content to the global variable, and free the memory when the function exits.

Here is a suggestion for managing memory when reading and writing PNG files:

void write_png_image(vector<uint8_t>& image, string output_filepath) {
    row_pointers = copy_vector_to_row_pointers(image, width, height);
    write_png_file(output_filepath.c_str(), row_pointers, width, height);
    free(row_pointers);
}

vector<uint8_t> read_png_image(string input_filepath) {
    read_png_file(input_filepath.c_str());
    vector<uint8_t> image = get_image_from_png_data();
    return image;
}

In this example, the write_png_image and read_png_image functions handle the memory management of the row_pointers variable, ensuring that the memory is freed when the function exits. You can adopt a similar approach for managing the memory of the image vector.

Here is a suggestion for managing memory when reading and writing PPM files:

void write_ppm_image(vector<uint8_t>& image, string output_filepath) {
    write_ppm_file(output_filepath.c_str(), image.size(), image.data());
    free(image.data());
}

vector<uint8_t> read_ppm_image(string input_filepath) {
    vector<uint8_t> image = read_ppm_file(input_filepath.c_str());
    return image;
}

In this example, the write_ppm_image and read_ppm_image functions handle the memory management of the image vector's data, ensuring that the memory is freed when the function exits.

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+int main(int argc, char* argv[]) {

  • // ... (rest of the code)
    +}

Let's break down the potential memory leaks in this code.

Understanding the Risks

Memory leaks occur when a program allocates memory dynamically (using new, malloc, vector, etc.) but fails to release it when it's no longer needed. This leads to a gradual increase in memory consumption, eventually causing crashes or instability.

Potential Memory Leak Areas

  1. Global Variables:

    • width and height: These variables are declared globally (outside any function). If they're used to manage memory allocated for image data, and if this memory isn't properly deallocated, you have a leak.
  2. read_png_image and write_png_image:

    • row_pointers: This variable appears to manage pointers to image rows. If read_png_file allocates memory, and you don't explicitly free it before returning from read_png_image, you'll have a leak. Similarly, in write_png_file, you need to ensure that any memory allocated for row_pointers is released.
  3. read_ppm_image:

    • image: You allocate a vector<uint8_t> to store the image data. Make sure image is properly cleared (or its contents are freed) if it's no longer needed.
  4. compress_image and decompress_image:

    • delta_encode and delta_decode: These functions modify the input vector<uint8_t>. While they might not directly allocate memory, ensure they don't introduce unintended side effects that lead to memory leaks.

    • buffer: You create a vector<char> to store compressed data. Make sure this buffer is cleared or released when no longer needed.

  5. compress and decompress1:

    • These functions likely interact with external compression libraries. Carefully review their documentation to understand their memory management practices. You might need to explicitly manage allocated memory in these functions.

Recommendations

  1. Explicit Memory Management: Whenever possible, use delete or free to release dynamically allocated memory.

  2. RAII (Resource Acquisition Is Initialization): Use smart pointers like unique_ptr and shared_ptr to automatically manage memory when objects go out of scope.

  3. Review Library Documentation: Carefully study the documentation of any external libraries used for image processing or compression. Understand their memory management conventions and ensure your code interacts with them correctly.

  4. Memory Leak Detectors: Use tools like Valgrind or AddressSanitizer to detect memory leaks during development. These tools can help pinpoint the exact locations of leaks in your code.

Let me know if you have any more questions.

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+int main(int argc, char* argv[]) {

  • // ... (rest of the code)
    +}

Top 3 Memory Leaks:

  1. row_pointers Variable: This global variable is allocated and used for storing image data pointers. It's not clear if it's properly deallocated after use. Memory leak potential: High.

    • Fix: Ensure row_pointers is deallocated or made dynamic to avoid memory leak.
    • Line: Declaration and potential leak points throughout the code where row_pointers is used.
  2. Unclear Deallocation of image:

    • In read_png_image and read_ppm_image: the image vector is allocated, but it's not clear if it's properly deallocated before exiting the function. If it's not, this could lead to memory leaks.
    • Fix: Explicitly deallocate image using image.clear() in the function.
    • Line: Memory allocation and potential leak points within read_png_image and read_ppm_image.
  3. Global Variables: The use of global variables like width and height without explicit initialization or deallocation can lead to memory leaks. It's best practice to avoid global variables, especially when dealing with resource allocation.

    • Fix: Pass width and height as function parameters.
    • Line: Declaration and potential leak points where width and height are used.

Additional Considerations:

  • Dynamic Memory Allocation: If the image vector's size changes dynamically, ensure that it's resized or reallocated correctly to avoid memory fragmentation and leaks.

  • File Handling: Ensure that files opened using ifstream and ofstream are properly closed after use to avoid file handle leaks.

  • FFTW Cleanup: You've included fftw_cleanup_threads() which is good practice to release FFTW resources.

Let me know if you want more detailed analysis or have any other questions!

@cs15b047
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\ No newline at end of file
+#include "mycodec.h"
+#include "compress.h"
+
+using namespace std;
+
+/*
+Ideas:
+1. RLE encoding: <intensity[0,255], count>: a) directly including all channels --> image blows up to 4MB, b) for each channel separately
+2. RGB to YCbCr conversion
+3. Bucketing CbCr values into 128 buckets and representing each intensity in 7 bits using bitsets --> lossy
+4. ZLib compression
+5. DCT + Quantization
+*/
+
+// Combination 1: Bucketing + Delta + ZLib (RLE worsens compression)
+string compress_image(vector<uint8_t>& image, int width, int height, string filepath) {

  • image = delta_encode<uint8_t> (image);
  • vector buffer = write_vec_to_buffer<uint8_t>(image, width, height, filepath);
  • compress(buffer, filepath);
  • return filepath;
    +}

+vector<uint8_t> decompress_image(string filename) {

  • vector buffer = decompress1(filename);
  • vector<uint8_t> image = read_vec_from_buffer<uint8_t>(buffer);
  • image = delta_decode<uint8_t>(image);
  • return image;
    +}

@cs15b047
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+template
+vector write_vec_to_buffer(vector& vec, int width, int height, string filename) {

  • ofstream outfile(filename, ios::out | ios::binary);
  • // ... write data to file ...
  • outfile.close();
  • ifstream infile(filename, ios::in | ios::binary);
  • vector buffer((istreambuf_iterator(infile)),
  •                     (istreambuf_iterator<char>()));
    
  • infile.close();
  • return buffer;
    +}

+template
+vector read_vec_from_buffer(vector& buffer) {

  • // ... read data from buffer ...
    +}
Here are the top 3 potential memory leaks with fixes:

**1. `read_png_image` function**

*   **Problem:**  `copy_row_pointers_to_vector`  likely allocates memory for a new vector based on `row_pointers`, which is potentially not freed later. If `row_pointers` itself is dynamically allocated, it could also leak.
*   **Fix:** Ensure that `copy_row_pointers_to_vector` does not allocate memory that isn't explicitly freed. If it modifies existing data, it needs to ensure the original data is not overwritten.

**2.  `write_png_image` function**

*   **Problem:** `row_pointers = copy_vector_to_row_pointers(image, width, height)`  allocates memory for `row_pointers` based on `image`, which might not be freed later. 

*   **Fix:** Similar to `read_png_image`, ensure that `copy_vector_to_row_pointers` doesn't create unintended memory allocations that require freeing.

**3. Global variables:**

*   **Problem:** Global variables `width` and `height` are set inside `read_ppm_image` and might not be explicitly released. If these are allocated dynamically (e.g., using `new`), this would be a leak.

*   **Fix:** If `width` and `height` are allocated dynamically, ensure they are deallocated using `delete` when no longer needed.

**General Tips:**

*   **Use Smart Pointers:** Consider replacing raw pointers with smart pointers (`std::unique_ptr` or `std::shared_ptr`) to automatically manage memory deallocation.
*   **RAII (Resource Acquisition Is Initialization):** Encapsulate resources (like file handles, memory allocations) within objects' constructors and destructors. This ensures resources are properly released when objects go out of scope.

*   **Memory Leak Detection Tools:** Use tools like Valgrind or AddressSanitizer to detect memory leaks during development.



Let me know if you have any more questions.

@cs15b047
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@cs15b047
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Also, consider adding error handling and logging for better script readability and maintainability.

#!/bin/bash

DATA_DIR=./data
RESULTS_DIR=./results

Set up paths

LOSSLESS_DIR=./png
MYCODEC_DIR=./mycodec
CLUSTERING_DIR=./clustering
DIFFUSION_DIR=./stable-diffusion-compressor
CLIC_DATA_DIR=$DATA_DIR/clic
C10N_DATA_DIR=$DATA_DIR/c10n_benchmark

mkdir -p $RESULTS_DIR/lossless
mkdir -p $RESULTS_DIR/lossless/compressed
mkdir -p $RESULTS_DIR/lossless/reconstructed
mkdir -p $RESULTS_DIR/mycodec
mkdir -p $RESULTS_DIR/mycodec/compressed
mkdir -p $RESULTS_DIR/mycodec/reconstructed
mkdir -p $RESULTS_DIR/clustering
mkdir -p $RESULTS_DIR/clustering/compressed
mkdir -p $RESULTS_DIR/clustering/reconstructed
mkdir -p $RESULTS_DIR/stable_diffusion
mkdir -p $RESULTS_DIR/stable_diffusion/compressed
mkdir -p $RESULTS_DIR/stable_diffusion/reconstructed
mkdir -p $RESULTS_DIR/hific
mkdir -p $RESULTS_DIR/hific/compressed
mkdir -p $RESULTS_DIR/hific/reconstructed

Run lossless compression on C10N dataset

function lossless() {
for i in $C10N_DATA_DIR/*.ppm; do
img_name=$(basename -s .ppm $i)
src_img_path=$i

    compressed_img_path=$RESULTS_DIR/lossless/compressed/$img_name.z
    reconstructed_img_path=$RESULTS_DIR/lossless/reconstructed/$img_name.png

    # Run custom lossless codec
    $MYCODEC_DIR/mycodec $src_img_path $compressed_img_path $reconstructed_img_path
    echo $img_name "Lossless Compression: " $(du -h $compressed_img_path | cut -f1) " " $(du -h $reconstructed_img_path | cut -f1) >> $RESULTS_DIR/stats.txt
done

}

Run mycodec on C10N dataset

function mycodec() {
for i in $C10N_DATA_DIR/*.ppm; do
img_name=$(basename -s .ppm $i)
src_img_path=$i

    compressed_img_path=$RESULTS_DIR/mycodec/compressed/$img_name.z
    reconstructed_img_path=$RESULTS_DIR/mycodec/reconstructed/$img_name.png

    # Run custom codec
    $MYCODEC_DIR/mycodec $src_img_path $compressed_img_path $reconstructed_img_path
    echo $img_name "Mycodec: " $(du -h $compressed_img_path | cut -f1) " " $(du -h $reconstructed_img_path | cut -f1) >> $RESULTS_DIR/stats.txt
done

}

Run clustering (k-means) compression on C10N dataset

function clustering() {
K=200
for i in $C10N_DATA_DIR/*.ppm; do
img_name=$(basename -s .ppm $i)
src_img_path=$i

    compressed_img_path=$RESULTS_DIR/clustering/compressed/$img_name.z
    reconstructed_img_path=$RESULTS_DIR/clustering/reconstructed/$img_name.png

    # Run k-means clustering codec
    python3 $CLUSTERING_DIR/kmeans.py $src_img_path $compressed_img_path $reconstructed_img_path $K
    echo $img_name "Clustering Compression: " $(du -h $compressed_img_path | cut -f1) " " $(du -h $reconstructed_img_path | cut -f1) >> $RESULTS_DIR/stats.txt
done

done

Run stable diffusion compression on C10N dataset

function stable_diffusion() {
for i in $C10N_DATA_DIR/*.ppm; do
img_name=$(basename -s .ppm $i)
src_img_path=$i

    compressed_img_path=$RESULTS_DIR/stable_diffusion/compressed/$img_name.z
    reconstructed_img_path=$RESULTS_DIR/stable_diffusion/reconstructed/$img_name.png

    # Run stable diffusion codec
    python3 $DIFFUSION_DIR/driver.py $src_img_path $compressed_img_path $reconstructed_img_path
    echo $img_name "Stable Diffusion Compression: " $(du -h $compressed_img_path | cut -f1) " " $(du -h $reconstructed_img_path | cut -f1) >> $RESULTS_DIR/stats.txt
done

done

Run HiFiC compression on C10N dataset

function hific() {
model="hific-lo"
for i in $C10N_DATA_DIR/*.ppm; do
img_name=$(basename -s .ppm $i)
src_img_path=$i

    compressed_img_path=$RESULTS_DIR/hific/compressed/$img_name.tfci
    reconstructed_img_path=$RESULTS_DIR/hific/reconstructed/$img_name.png

    # Run HiFiC codec
    python3 $HIFIC_DIR/tfci.py compress $model $src_img_path $compressed_img_path
    python3 $HIFIC_DIR/tfci.py decompress $compressed_img_path $reconstructed_img_path
    echo $img_name "HiFiC Compression: " $(du -h $compressed_img_path | cut -f1) " " $(du -h $reconstructed_img_path | cut -f1) >> $RESULTS_DIR/stats.txt
done

done

Choose compression method and run it

method=$1
if [ -z "$method" ]; then
echo "Usage: ./script.sh "
exit 1
fi

if [ "$method" == "lossless" ]; then
lossless
elif [ "$method" == "mycodec" ]; then
mycodec
elif [ "$method" == "clustering" ]; then
clustering
elif [ "$method" == "stable_diffusion" ]; then
stable_diffusion
elif [ "$method" == "hific" ]; then
hific
else
echo "Invalid method. Use 'lossless', 'mycodec', 'clustering', 'stable_diffusion', or 'hific'."
fi

@cs15b047
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This is a Python script to compress images using mycodec lossless compression algorithm.
The script first imports the necessary modules and sets up the image directory path.
It then defines a function to read an image file and convert it to a numpy array.
The script also defines a function to compress an image using mycodec algorithm.
The main function reads an image file using the read_image function, compresses it using the compress_image function,
saves the compressed data to a file, and displays the original and compressed images side by side for comparison.
The script uses a try-except block to handle exceptions such as file not found errors and memory errors.

     Here's a more detailed breakdown of the script:

     The first few lines import the necessary modules and define some constants:
     - `np`: NumPy module for working with arrays and matrices.
     - `os`: Operating system module for file manipulation.
     - `sys`: System module for accessing some variables used or maintained by the runtime environment.
     - `PIL`: Pillow module for working with images.
     - `IMAGE_DIR`: Constant for the image directory path.

     The next few lines define the read_image function that takes an image file path as an argument and returns a numpy array:
     1. Opens the image file using Pillow's Image class.
     2. Converts the image to a numpy array using Pillow's to_array function.

     The compress_image function takes an image numpy array and a compression level as arguments and returns the compressed data:
     1. Defines the mycodec lossless compression algorithm as a separate function mycodec_compress.
     2. Calls the mycodec_compress function to compress the image data.
     3. Converts the compressed data to a bytes object using the tobytes function.

     The main function reads an image file using the read_image function, compresses it using the compress_image function,
     saves the compressed data to a file with the same name as the input file but with a .mycodec extension,
     and displays the original and compressed images side by side for comparison using Pillow's ImageDraw class.

     The script handles exceptions such as file not found errors and memory errors using try-except blocks.

     The mycodec lossless compression algorithm is not provided in the script. It needs to be defined separately.
     Here's a brief outline of mycodec lossless compression algorithm:

     - Divide the image into non-overlapping blocks of size 8x8 pixels.
     - For each block, calculate the difference between the block's pixel values and the average pixel value of the block.
     - Encode the differences using Huffman coding.
     - Store the block's average pixel value and Huffman-encoded differences.
     - Repeat for all blocks.

     The script does not implement the Huffman coding part of the algorithm. It just compresses and decompresses the data using mycodec_compress and mycodec_decompress functions, respectively.

     Memory leaks:

     It is not possible to determine memory leaks from the provided code without running the code or analyzing it in more detail.

     However, one possible area of memory leaks is in the PNG image file handling using Pillow's Image class. Make sure to always close the image file using the close_() method after processing it to avoid memory leaks.

     Additionally, make sure to delete any unnecessary image objects and arrays using the del statement when they are no longer needed.

     Here's a corrected version of the script:

     import os
     import sys
     import numpy as np
     from PIL import Image, ImageDraw, ImageFilter
     import io

     IMAGE_DIR = 'image_data/images/'

     def read_image(file_path):
         img = Image.open(file_path)
         img_array = np.asarray(img)
         img.close()
         return img_array

     def compress_image(image_array, compression_level):
         # Define mycodec lossless compression algorithm here.
         compressed_data = mycodec_compress(image_array)
         return compressed_data

     def mycodec_compress(image_data):
         # Define mycodec lossless compression algorithm here.
         # ...
         return compressed_data

     def mycodec_decompress(compressed_data):
         # Define mycodec lossless decompression algorithm here.
         # ...
         return decompressed_data

     def save_image(file_path, image_data):
         img = Image.fromarray(image_data)
         img.save(file_path)
         img.close()

     def main(file_path):
         image_data = read_image(file_path)
         compressed_data = compress_image(image_data, 1)
         file_name, ext = os.path.splitext(file_path)
         output_file = f"{file_name}.mycodec"
         with open(output_file, "wb") as out_file:
             out_file.write(compressed_data)

         with Image.open(file_path) as img:
             img_draw = ImageDraw.Draw(img)
             width, height = img.size
             for i in range(0, width, 32):
                 for j in range(0, height, 32):
                     x1 = i
                     y1 = j
                     x2 = i + 32
                     y2 = j + 32
                     img_draw.rectangle([(x1, y1), (x2, y2)], fill="white")
                     img_draw.text((x1, y1), "Original", fill="white")
                     img_draw.text((x1 + width // 2, y1), "Compressed", fill="white")
             img.show()
             img.close()

     if __name__ == "__main__":
         file_path = sys.argv[1]
         main(file_path)

@cs15b047
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The given Makefile appears to correctly compile and link the PNG code using the provided SRCS_PNG variable. However, it's important to ensure that any memory allocated during the compilation or linking process is properly freed to avoid memory leaks.

     To check for memory leaks in the PNG code, you should use a memory debugging tool such as Valgrind or AddressSanitizer. These tools can detect memory leaks and other memory-related issues.

     For instance, to use Valgrind on the PNG code:

     1. Install Valgrind on your system.
     2. Modify the PNG Makefile to use Valgrind during compilation:

        SRCS_PNG := \
            refpng.cpp \
            rle.cpp \
            delta.cpp \
            bucket.cpp \
            color_transform.cpp \
            compress.cpp \
            dct.cpp \
            utils.cpp \
            lossless.cpp \
            driver_lossless.cpp

        all: $(PNG)
        png: $(PNG)

        PNG := $(SRCS_PNG:.cpp=.o) $(PNG:.o)

        PNG := $(PNG:.o)

        $(PNG): %.o
            $(CC) $(FLAGS) -c $< -o $@ $(LDFLAGS)

        $(PNG): $(PNG)
            valgrind --leak-check=full --show-leaks --show-memaddr=yes \
                    --track-origins=yes --truncate-child-stats=yes $(CC) $^ \
                    -o $@ $(LDLFAGS) $(LDLFAGS) $(LDLFAGS)

        $(TARGET): $(PNG)

        $(TARGET): $(PNG)
            $(CC) $(FLAGS) -o $(TARGET) $(PNG) $(LDLFAGS)

        clean:
            rm -f $(PNG) $(TARGET)

  This will compile and link the PNG code using Valgrind and report any memory leaks during the execution. The reported memory leaks will be shown after the program finishes executing. You can then examine those leaks and determine whether they're due to specific lines in the PNG code.

  To fix a memory leak, you may need to modify the code to properly free the allocated memory using the appropriate C++ operators, such as `delete[]` or `free()`, depending on the memory allocation function used. Once fixed, recompile the code and rerun the Valgrind tool to check if the memory leak has been resolved.

@cs15b047
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Also, consider adding error handling and logging for better script readability and maintainability.

#!/bin/bash

DATA_DIR=./data
RESULTS_DIR=./results

Set up paths

LOSSLESS_DIR=./png
MYCODEC_DIR=./mycodec
CLUSTERING_DIR=./clustering
DIFFUSION_DIR=./stable-diffusion-compressor
CLIC_DATA_DIR=$DATA_DIR/clic
C10N_DATA_DIR=$DATA_DIR/c10n_benchmark

mkdir -p $RESULTS_DIR/lossless
mkdir -p $RESULTS_DIR/lossless/compressed
mkdir -p $RESULTS_DIR/lossless/reconstructed
mkdir -p $RESULTS_DIR/mycodec
mkdir -p $RESULTS_DIR/mycodec/compressed
mkdir -p $RESULTS_DIR/mycodec/reconstructed
mkdir -p $RESULTS_DIR/clustering
mkdir -p $RESULTS_DIR/clustering/compressed
mkdir -p $RESULTS_DIR/clustering/reconstructed
mkdir -p $RESULTS_DIR/stable_diffusion
mkdir -p $RESULTS_DIR/stable_diffusion/compressed
mkdir -p $RESULTS_DIR/stable_diffusion/reconstructed
mkdir -p $RESULTS_DIR/hific
mkdir -p $RESULTS_DIR/hific/compressed
mkdir -p $RESULTS_DIR/hific/reconstructed

Run lossless compression on C10N dataset

function lossless() {
for i in $C10N_DATA_DIR/*.ppm; do
img_name=$(basename -s .ppm $i)
src_img_path=$i

    compressed_img_path=$RESULTS_DIR/lossless/compressed/$img_name.z
    reconstructed_img_path=$RESULTS_DIR/lossless/reconstructed/$img_name.png

    # Run custom lossless codec
    $MYCODEC_DIR/mycodec $src_img_path $compressed_img_path $reconstructed_img_path
    echo $img_name "Lossless Compression: " $(du -h $compressed_img_path | cut -f1) " " $(du -h $reconstructed_img_path | cut -f1) >> $RESULTS_DIR/stats.txt
done

}

Run mycodec on C10N dataset

function mycodec() {
for i in $C10N_DATA_DIR/*.ppm; do
img_name=$(basename -s .ppm $i)
src_img_path=$i

    compressed_img_path=$RESULTS_DIR/mycodec/compressed/$img_name.z
    reconstructed_img_path=$RESULTS_DIR/mycodec/reconstructed/$img_name.png

    # Run custom codec
    $MYCODEC_DIR/mycodec $src_img_path $compressed_img_path $reconstructed_img_path
    echo $img_name "Mycodec: " $(du -h $compressed_img_path | cut -f1) " " $(du -h $reconstructed_img_path | cut -f1) >> $RESULTS_DIR/stats.txt
done

}

Run clustering (k-means) compression on C10N dataset

function clustering() {
K=200
for i in $C10N_DATA_DIR/*.ppm; do
img_name=$(basename -s .ppm $i)
src_img_path=$i

    compressed_img_path=$RESULTS_DIR/clustering/compressed/$img_name.z
    reconstructed_img_path=$RESULTS_DIR/clustering/reconstructed/$img_name.png

    # Run k-means clustering codec
    python3 $CLUSTERING_DIR/kmeans.py $src_img_path $compressed_img_path $reconstructed_img_path $K
    echo $img_name "Clustering Compression: " $(du -h $compressed_img_path | cut -f1) " " $(du -h $reconstructed_img_path | cut -f1) >> $RESULTS_DIR/stats.txt
done

done

Run stable diffusion compression on C10N dataset

function stable_diffusion() {
for i in $C10N_DATA_DIR/*.ppm; do
img_name=$(basename -s .ppm $i)
src_img_path=$i

    compressed_img_path=$RESULTS_DIR/stable_diffusion/compressed/$img_name.z
    reconstructed_img_path=$RESULTS_DIR/stable_diffusion/reconstructed/$img_name.png

    # Run stable diffusion codec
    python3 $DIFFUSION_DIR/driver.py $src_img_path $compressed_img_path $reconstructed_img_path
    echo $img_name "Stable Diffusion Compression: " $(du -h $compressed_img_path | cut -f1) " " $(du -h $reconstructed_img_path | cut -f1) >> $RESULTS_DIR/stats.txt
done

done

Run HiFiC compression on C10N dataset

function hific() {
model="hific-lo"
for i in $C10N_DATA_DIR/*.ppm; do
img_name=$(basename -s .ppm $i)
src_img_path=$i

    compressed_img_path=$RESULTS_DIR/hific/compressed/$img_name.tfci
    reconstructed_img_path=$RESULTS_DIR/hific/reconstructed/$img_name.png

    # Run HiFiC codec
    python3 $HIFIC_DIR/tfci.py compress $model $src_img_path $compressed_img_path
    python3 $HIFIC_DIR/tfci.py decompress $compressed_img_path $reconstructed_img_path
    echo $img_name "HiFiC Compression: " $(du -h $compressed_img_path | cut -f1) " " $(du -h $reconstructed_img_path | cut -f1) >> $RESULTS_DIR/stats.txt
done

done

Choose compression method and run it

method=$1
if [ -z "$method" ]; then
echo "Usage: ./script.sh "
exit 1
fi

if [ "$method" == "lossless" ]; then
lossless
elif [ "$method" == "mycodec" ]; then
mycodec
elif [ "$method" == "clustering" ]; then
clustering
elif [ "$method" == "stable_diffusion" ]; then
stable_diffusion
elif [ "$method" == "hific" ]; then
hific
else
echo "Invalid method. Use 'lossless', 'mycodec', 'clustering', 'stable_diffusion', or 'hific'."
fi

@cs15b047
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Owner Author

This is a Python script to compress images using mycodec lossless compression algorithm.
The script first imports the necessary modules and sets up the image directory path.
It then defines a function to read an image file and convert it to a numpy array.
The script also defines a function to compress an image using mycodec algorithm.
The main function reads an image file using the read_image function, compresses it using the compress_image function,
saves the compressed data to a file, and displays the original and compressed images side by side for comparison.
The script uses a try-except block to handle exceptions such as file not found errors and memory errors.

     Here's a more detailed breakdown of the script:

     The first few lines import the necessary modules and define some constants:
     - `np`: NumPy module for working with arrays and matrices.
     - `os`: Operating system module for file manipulation.
     - `sys`: System module for accessing some variables used or maintained by the runtime environment.
     - `PIL`: Pillow module for working with images.
     - `IMAGE_DIR`: Constant for the image directory path.

     The next few lines define the read_image function that takes an image file path as an argument and returns a numpy array:
     1. Opens the image file using Pillow's Image class.
     2. Converts the image to a numpy array using Pillow's to_array function.

     The compress_image function takes an image numpy array and a compression level as arguments and returns the compressed data:
     1. Defines the mycodec lossless compression algorithm as a separate function mycodec_compress.
     2. Calls the mycodec_compress function to compress the image data.
     3. Converts the compressed data to a bytes object using the tobytes function.

     The main function reads an image file using the read_image function, compresses it using the compress_image function,
     saves the compressed data to a file with the same name as the input file but with a .mycodec extension,
     and displays the original and compressed images side by side for comparison using Pillow's ImageDraw class.

     The script handles exceptions such as file not found errors and memory errors using try-except blocks.

     The mycodec lossless compression algorithm is not provided in the script. It needs to be defined separately.
     Here's a brief outline of mycodec lossless compression algorithm:

     - Divide the image into non-overlapping blocks of size 8x8 pixels.
     - For each block, calculate the difference between the block's pixel values and the average pixel value of the block.
     - Encode the differences using Huffman coding.
     - Store the block's average pixel value and Huffman-encoded differences.
     - Repeat for all blocks.

     The script does not implement the Huffman coding part of the algorithm. It just compresses and decompresses the data using mycodec_compress and mycodec_decompress functions, respectively.

     Memory leaks:

     It is not possible to determine memory leaks from the provided code without running the code or analyzing it in more detail.

     However, one possible area of memory leaks is in the PNG image file handling using Pillow's Image class. Make sure to always close the image file using the close_() method after processing it to avoid memory leaks.

     Additionally, make sure to delete any unnecessary image objects and arrays using the del statement when they are no longer needed.

     Here's a corrected version of the script:

     import os
     import sys
     import numpy as np
     from PIL import Image, ImageDraw, ImageFilter
     import io

     IMAGE_DIR = 'image_data/images/'

     def read_image(file_path):
         img = Image.open(file_path)
         img_array = np.asarray(img)
         img.close()
         return img_array

     def compress_image(image_array, compression_level):
         # Define mycodec lossless compression algorithm here.
         compressed_data = mycodec_compress(image_array)
         return compressed_data

     def mycodec_compress(image_data):
         # Define mycodec lossless compression algorithm here.
         # ...
         return compressed_data

     def mycodec_decompress(compressed_data):
         # Define mycodec lossless decompression algorithm here.
         # ...
         return decompressed_data

     def save_image(file_path, image_data):
         img = Image.fromarray(image_data)
         img.save(file_path)
         img.close()

     def main(file_path):
         image_data = read_image(file_path)
         compressed_data = compress_image(image_data, 1)
         file_name, ext = os.path.splitext(file_path)
         output_file = f"{file_name}.mycodec"
         with open(output_file, "wb") as out_file:
             out_file.write(compressed_data)

         with Image.open(file_path) as img:
             img_draw = ImageDraw.Draw(img)
             width, height = img.size
             for i in range(0, width, 32):
                 for j in range(0, height, 32):
                     x1 = i
                     y1 = j
                     x2 = i + 32
                     y2 = j + 32
                     img_draw.rectangle([(x1, y1), (x2, y2)], fill="white")
                     img_draw.text((x1, y1), "Original", fill="white")
                     img_draw.text((x1 + width // 2, y1), "Compressed", fill="white")
             img.show()
             img.close()

     if __name__ == "__main__":
         file_path = sys.argv[1]
         main(file_path)

@cs15b047
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The given Makefile appears to correctly compile and link the PNG code using the provided SRCS_PNG variable. However, it's important to ensure that any memory allocated during the compilation or linking process is properly freed to avoid memory leaks.

     To check for memory leaks in the PNG code, you should use a memory debugging tool such as Valgrind or AddressSanitizer. These tools can detect memory leaks and other memory-related issues.

     For instance, to use Valgrind on the PNG code:

     1. Install Valgrind on your system.
     2. Modify the PNG Makefile to use Valgrind during compilation:

        SRCS_PNG := \
            refpng.cpp \
            rle.cpp \
            delta.cpp \
            bucket.cpp \
            color_transform.cpp \
            compress.cpp \
            dct.cpp \
            utils.cpp \
            lossless.cpp \
            driver_lossless.cpp

        all: $(PNG)
        png: $(PNG)

        PNG := $(SRCS_PNG:.cpp=.o) $(PNG:.o)

        PNG := $(PNG:.o)

        $(PNG): %.o
            $(CC) $(FLAGS) -c $< -o $@ $(LDFLAGS)

        $(PNG): $(PNG)
            valgrind --leak-check=full --show-leaks --show-memaddr=yes \
                    --track-origins=yes --truncate-child-stats=yes $(CC) $^ \
                    -o $@ $(LDLFAGS) $(LDLFAGS) $(LDLFAGS)

        $(TARGET): $(PNG)

        $(TARGET): $(PNG)
            $(CC) $(FLAGS) -o $(TARGET) $(PNG) $(LDLFAGS)

        clean:
            rm -f $(PNG) $(TARGET)

  This will compile and link the PNG code using Valgrind and report any memory leaks during the execution. The reported memory leaks will be shown after the program finishes executing. You can then examine those leaks and determine whether they're due to specific lines in the PNG code.

  To fix a memory leak, you may need to modify the code to properly free the allocated memory using the appropriate C++ operators, such as `delete[]` or `free()`, depending on the memory allocation function used. Once fixed, recompile the code and rerun the Valgrind tool to check if the memory leak has been resolved.

@cs15b047
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In the read_png_image function, there is no need to call write_png_file function inside it as it is not being used to read the PNG file. The following lines are causing memory leaks:

    1. `read_png_file(input_filepath.c_str());`

    2. `row_pointers = copy_vector_to_row_pointers(image, width, height);`

    3. `write_png_file(output_filepath.c_str());`

    4. `write_png_image(image, compressed_filepath, output_filepath);`

    5. `row_pointers = copy_vector_to_row_pointers(image, width, height);`

     To fix this issue, you can modify the `read_png_image` function as follows:

    1. Remove the calls to `read_png_file` and `write_png_file` functions.
    2. Allocate the `row_pointers` vector inside the `read_png_image` function, and copy the data directly to it.
    3. Remove the call to `write_png_image` function, and use the directly obtained `image` vector to write to the output file.

     Here's the fixed version of the `read_png_image` function:

     ```cpp
     vector<uint8_t*> row_pointers;
     read_png_file(input_filepath.c_str());
     get_image_data();

     vector<uint8_t> image;
     copy_row_pointers_to_vector(image, row_pointers, width, height);
     ```

     Then, in the `main` function, call the `read_png_image` function, and use the obtained `image` vector to write the output file:

     ```cpp
     vector<uint8_t> image = read_png_image(input_filepath);
     write_png_image(image, compressed_filepath, output_filepath);
     ```

     This will eliminate the memory leaks caused by the unnecessary function calls, and the `row_pointers` vector inside the `read_png_image` function.

@cs15b047
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cs15b047 commented Feb 2, 2025

Also, consider adding error handling and logging for better script readability and maintainability.

#!/bin/bash

DATA_DIR=./data
RESULTS_DIR=./results

Set up paths

LOSSLESS_DIR=./png
MYCODEC_DIR=./mycodec
CLUSTERING_DIR=./clustering
DIFFUSION_DIR=./stable-diffusion-compressor
CLIC_DATA_DIR=$DATA_DIR/clic
C10N_DATA_DIR=$DATA_DIR/c10n_benchmark

mkdir -p $RESULTS_DIR/lossless
mkdir -p $RESULTS_DIR/lossless/compressed
mkdir -p $RESULTS_DIR/lossless/reconstructed
mkdir -p $RESULTS_DIR/mycodec
mkdir -p $RESULTS_DIR/mycodec/compressed
mkdir -p $RESULTS_DIR/mycodec/reconstructed
mkdir -p $RESULTS_DIR/clustering
mkdir -p $RESULTS_DIR/clustering/compressed
mkdir -p $RESULTS_DIR/clustering/reconstructed
mkdir -p $RESULTS_DIR/stable_diffusion
mkdir -p $RESULTS_DIR/stable_diffusion/compressed
mkdir -p $RESULTS_DIR/stable_diffusion/reconstructed
mkdir -p $RESULTS_DIR/hific
mkdir -p $RESULTS_DIR/hific/compressed
mkdir -p $RESULTS_DIR/hific/reconstructed

Run lossless compression on C10N dataset

function lossless() {
for i in $C10N_DATA_DIR/*.ppm; do
img_name=$(basename -s .ppm $i)
src_img_path=$i

    compressed_img_path=$RESULTS_DIR/lossless/compressed/$img_name.z
    reconstructed_img_path=$RESULTS_DIR/lossless/reconstructed/$img_name.png

    # Run custom lossless codec
    $MYCODEC_DIR/mycodec $src_img_path $compressed_img_path $reconstructed_img_path
    echo $img_name "Lossless Compression: " $(du -h $compressed_img_path | cut -f1) " " $(du -h $reconstructed_img_path | cut -f1) >> $RESULTS_DIR/stats.txt
done

}

Run mycodec on C10N dataset

function mycodec() {
for i in $C10N_DATA_DIR/*.ppm; do
img_name=$(basename -s .ppm $i)
src_img_path=$i

    compressed_img_path=$RESULTS_DIR/mycodec/compressed/$img_name.z
    reconstructed_img_path=$RESULTS_DIR/mycodec/reconstructed/$img_name.png

    # Run custom codec
    $MYCODEC_DIR/mycodec $src_img_path $compressed_img_path $reconstructed_img_path
    echo $img_name "Mycodec: " $(du -h $compressed_img_path | cut -f1) " " $(du -h $reconstructed_img_path | cut -f1) >> $RESULTS_DIR/stats.txt
done

}

Run clustering (k-means) compression on C10N dataset

function clustering() {
K=200
for i in $C10N_DATA_DIR/*.ppm; do
img_name=$(basename -s .ppm $i)
src_img_path=$i

    compressed_img_path=$RESULTS_DIR/clustering/compressed/$img_name.z
    reconstructed_img_path=$RESULTS_DIR/clustering/reconstructed/$img_name.png

    # Run k-means clustering codec
    python3 $CLUSTERING_DIR/kmeans.py $src_img_path $compressed_img_path $reconstructed_img_path $K
    echo $img_name "Clustering Compression: " $(du -h $compressed_img_path | cut -f1) " " $(du -h $reconstructed_img_path | cut -f1) >> $RESULTS_DIR/stats.txt
done

done

Run stable diffusion compression on C10N dataset

function stable_diffusion() {
for i in $C10N_DATA_DIR/*.ppm; do
img_name=$(basename -s .ppm $i)
src_img_path=$i

    compressed_img_path=$RESULTS_DIR/stable_diffusion/compressed/$img_name.z
    reconstructed_img_path=$RESULTS_DIR/stable_diffusion/reconstructed/$img_name.png

    # Run stable diffusion codec
    python3 $DIFFUSION_DIR/driver.py $src_img_path $compressed_img_path $reconstructed_img_path
    echo $img_name "Stable Diffusion Compression: " $(du -h $compressed_img_path | cut -f1) " " $(du -h $reconstructed_img_path | cut -f1) >> $RESULTS_DIR/stats.txt
done

done

Run HiFiC compression on C10N dataset

function hific() {
model="hific-lo"
for i in $C10N_DATA_DIR/*.ppm; do
img_name=$(basename -s .ppm $i)
src_img_path=$i

    compressed_img_path=$RESULTS_DIR/hific/compressed/$img_name.tfci
    reconstructed_img_path=$RESULTS_DIR/hific/reconstructed/$img_name.png

    # Run HiFiC codec
    python3 $HIFIC_DIR/tfci.py compress $model $src_img_path $compressed_img_path
    python3 $HIFIC_DIR/tfci.py decompress $compressed_img_path $reconstructed_img_path
    echo $img_name "HiFiC Compression: " $(du -h $compressed_img_path | cut -f1) " " $(du -h $reconstructed_img_path | cut -f1) >> $RESULTS_DIR/stats.txt
done

done

Choose compression method and run it

method=$1
if [ -z "$method" ]; then
echo "Usage: ./script.sh "
exit 1
fi

if [ "$method" == "lossless" ]; then
lossless
elif [ "$method" == "mycodec" ]; then
mycodec
elif [ "$method" == "clustering" ]; then
clustering
elif [ "$method" == "stable_diffusion" ]; then
stable_diffusion
elif [ "$method" == "hific" ]; then
hific
else
echo "Invalid method. Use 'lossless', 'mycodec', 'clustering', 'stable_diffusion', or 'hific'."
fi

@cs15b047
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cs15b047 commented Feb 2, 2025

This is a Python script to compress images using mycodec lossless compression algorithm.
The script first imports the necessary modules and sets up the image directory path.
It then defines a function to read an image file and convert it to a numpy array.
The script also defines a function to compress an image using mycodec algorithm.
The main function reads an image file using the read_image function, compresses it using the compress_image function,
saves the compressed data to a file, and displays the original and compressed images side by side for comparison.
The script uses a try-except block to handle exceptions such as file not found errors and memory errors.

     Here's a more detailed breakdown of the script:

     The first few lines import the necessary modules and define some constants:
     - `np`: NumPy module for working with arrays and matrices.
     - `os`: Operating system module for file manipulation.
     - `sys`: System module for accessing some variables used or maintained by the runtime environment.
     - `PIL`: Pillow module for working with images.
     - `IMAGE_DIR`: Constant for the image directory path.

     The next few lines define the read_image function that takes an image file path as an argument and returns a numpy array:
     1. Opens the image file using Pillow's Image class.
     2. Converts the image to a numpy array using Pillow's to_array function.

     The compress_image function takes an image numpy array and a compression level as arguments and returns the compressed data:
     1. Defines the mycodec lossless compression algorithm as a separate function mycodec_compress.
     2. Calls the mycodec_compress function to compress the image data.
     3. Converts the compressed data to a bytes object using the tobytes function.

     The main function reads an image file using the read_image function, compresses it using the compress_image function,
     saves the compressed data to a file with the same name as the input file but with a .mycodec extension,
     and displays the original and compressed images side by side for comparison using Pillow's ImageDraw class.

     The script handles exceptions such as file not found errors and memory errors using try-except blocks.

     The mycodec lossless compression algorithm is not provided in the script. It needs to be defined separately.
     Here's a brief outline of mycodec lossless compression algorithm:

     - Divide the image into non-overlapping blocks of size 8x8 pixels.
     - For each block, calculate the difference between the block's pixel values and the average pixel value of the block.
     - Encode the differences using Huffman coding.
     - Store the block's average pixel value and Huffman-encoded differences.
     - Repeat for all blocks.

     The script does not implement the Huffman coding part of the algorithm. It just compresses and decompresses the data using mycodec_compress and mycodec_decompress functions, respectively.

     Memory leaks:

     It is not possible to determine memory leaks from the provided code without running the code or analyzing it in more detail.

     However, one possible area of memory leaks is in the PNG image file handling using Pillow's Image class. Make sure to always close the image file using the close_() method after processing it to avoid memory leaks.

     Additionally, make sure to delete any unnecessary image objects and arrays using the del statement when they are no longer needed.

     Here's a corrected version of the script:

     import os
     import sys
     import numpy as np
     from PIL import Image, ImageDraw, ImageFilter
     import io

     IMAGE_DIR = 'image_data/images/'

     def read_image(file_path):
         img = Image.open(file_path)
         img_array = np.asarray(img)
         img.close()
         return img_array

     def compress_image(image_array, compression_level):
         # Define mycodec lossless compression algorithm here.
         compressed_data = mycodec_compress(image_array)
         return compressed_data

     def mycodec_compress(image_data):
         # Define mycodec lossless compression algorithm here.
         # ...
         return compressed_data

     def mycodec_decompress(compressed_data):
         # Define mycodec lossless decompression algorithm here.
         # ...
         return decompressed_data

     def save_image(file_path, image_data):
         img = Image.fromarray(image_data)
         img.save(file_path)
         img.close()

     def main(file_path):
         image_data = read_image(file_path)
         compressed_data = compress_image(image_data, 1)
         file_name, ext = os.path.splitext(file_path)
         output_file = f"{file_name}.mycodec"
         with open(output_file, "wb") as out_file:
             out_file.write(compressed_data)

         with Image.open(file_path) as img:
             img_draw = ImageDraw.Draw(img)
             width, height = img.size
             for i in range(0, width, 32):
                 for j in range(0, height, 32):
                     x1 = i
                     y1 = j
                     x2 = i + 32
                     y2 = j + 32
                     img_draw.rectangle([(x1, y1), (x2, y2)], fill="white")
                     img_draw.text((x1, y1), "Original", fill="white")
                     img_draw.text((x1 + width // 2, y1), "Compressed", fill="white")
             img.show()
             img.close()

     if __name__ == "__main__":
         file_path = sys.argv[1]
         main(file_path)

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cs15b047 commented Feb 2, 2025

The given Makefile appears to correctly compile and link the PNG code using the provided SRCS_PNG variable. However, it's important to ensure that any memory allocated during the compilation or linking process is properly freed to avoid memory leaks.

     To check for memory leaks in the PNG code, you should use a memory debugging tool such as Valgrind or AddressSanitizer. These tools can detect memory leaks and other memory-related issues.

     For instance, to use Valgrind on the PNG code:

     1. Install Valgrind on your system.
     2. Modify the PNG Makefile to use Valgrind during compilation:

        SRCS_PNG := \
            refpng.cpp \
            rle.cpp \
            delta.cpp \
            bucket.cpp \
            color_transform.cpp \
            compress.cpp \
            dct.cpp \
            utils.cpp \
            lossless.cpp \
            driver_lossless.cpp

        all: $(PNG)
        png: $(PNG)

        PNG := $(SRCS_PNG:.cpp=.o) $(PNG:.o)

        PNG := $(PNG:.o)

        $(PNG): %.o
            $(CC) $(FLAGS) -c $< -o $@ $(LDFLAGS)

        $(PNG): $(PNG)
            valgrind --leak-check=full --show-leaks --show-memaddr=yes \
                    --track-origins=yes --truncate-child-stats=yes $(CC) $^ \
                    -o $@ $(LDLFAGS) $(LDLFAGS) $(LDLFAGS)

        $(TARGET): $(PNG)

        $(TARGET): $(PNG)
            $(CC) $(FLAGS) -o $(TARGET) $(PNG) $(LDLFAGS)

        clean:
            rm -f $(PNG) $(TARGET)

  This will compile and link the PNG code using Valgrind and report any memory leaks during the execution. The reported memory leaks will be shown after the program finishes executing. You can then examine those leaks and determine whether they're due to specific lines in the PNG code.

  To fix a memory leak, you may need to modify the code to properly free the allocated memory using the appropriate C++ operators, such as `delete[]` or `free()`, depending on the memory allocation function used. Once fixed, recompile the code and rerun the Valgrind tool to check if the memory leak has been resolved.

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cs15b047 commented Feb 2, 2025

In the read_png_image function, there is no need to call write_png_file function inside it as it is not being used to read the PNG file. The following lines are causing memory leaks:

    1. `read_png_file(input_filepath.c_str());`

    2. `row_pointers = copy_vector_to_row_pointers(image, width, height);`

    3. `write_png_file(output_filepath.c_str());`

    4. `write_png_image(image, compressed_filepath, output_filepath);`

    5. `row_pointers = copy_vector_to_row_pointers(image, width, height);`

     To fix this issue, you can modify the `read_png_image` function as follows:

    1. Remove the calls to `read_png_file` and `write_png_file` functions.
    2. Allocate the `row_pointers` vector inside the `read_png_image` function, and copy the data directly to it.
    3. Remove the call to `write_png_image` function, and use the directly obtained `image` vector to write to the output file.

     Here's the fixed version of the `read_png_image` function:

     ```cpp
     vector<uint8_t*> row_pointers;
     read_png_file(input_filepath.c_str());
     get_image_data();

     vector<uint8_t> image;
     copy_row_pointers_to_vector(image, row_pointers, width, height);
     ```

     Then, in the `main` function, call the `read_png_image` function, and use the obtained `image` vector to write the output file:

     ```cpp
     vector<uint8_t> image = read_png_image(input_filepath);
     write_png_image(image, compressed_filepath, output_filepath);
     ```

     This will eliminate the memory leaks caused by the unnecessary function calls, and the `row_pointers` vector inside the `read_png_image` function.

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cs15b047 commented Feb 2, 2025

In the following code snippet, the 'image' vector is allocated using 'new' and not freed in the function. This results in a memory leak. To fix it, the 'image' vector should be allocated using 'std::vector<uint8_t> image(width * height)' instead of 'new std::vector<uint8_t>(width * height)'.

// Function to compress image using RLE encoding + ZLib compression
vector<uint8_t> compress_image_rle_and_zlib(vector<uint8_t>& image, int width, int height, string filepath) {
// RLE encoding
vector<pair<uint8_t, int>> rle_vec;

for (int i = 0; i < width * height; ++i) {
    if (i % width == 0) {
        rle_vec.push_back(make_pair(image[i], 1));
        continue;
    }

    if (rle_vec.back().first == image[i] && rle_vec.back().second + 1 < 255) {
        rle_vec.back().second++;
        continue;
    }

    rle_vec.push_back(make_pair(image[i], 1));
}

// ZLib compression
stringstream ss;
ss << rle_vec.size() << '\n';
for (auto it : rle_vec) {
    ss << it.first << ' ' << it.second;
    if (it != rle_vec.back()) ss << ' ';
}

ss << '\0';
vector<char> buffer = ss.str().c_str();
compress(buffer, filepath);

return {}; // Returning an empty vector instead of the original 'image' vector may cause issues. To avoid this, the 'image' vector should be passed as a reference or returned as a return value.

}

vector<uint8_t> decompress_image_rle_and_zlib(string filename) {
// Decompress ZLib
vector buffer = decompress1(filename);

// Tokenize the decompressed string by ' '
vector<string> tokens = split(string(buffer.begin(), buffer.end()), " ");

// Parse each token into an RLE pair
vector<pair<uint8_t, int>> rle_vec;
for (auto token : tokens) {
    int pos = token.find(' ');
    int count = (pos > 0) ? stoi(token.substr(pos + 1)) : 1;
    rle_vec.push_back(make_pair(stoi(token.substr(0, pos)), count));
}

// Reconstruct the original image from RLE pairs
vector<uint8_t> image(width * height);
int idx = 0;
for (auto it : rle_vec) {
    for (int i = 0; i < it.second; ++i) {
        image[idx++] = it.first;
    }
}

return image;

}

// Function to compress image using RGB to YCbCr conversion + ZLib compression
vector<uint8_t> compress_image_rgb_to_YCbCr_and_zlib(vector<uint8_t>& image, int width, int height, string filepath) {
// RGB to YCbCr conversion
vector ycbcr_vec(3 * width * height);
for (int y = 0; y < height; ++y) {
for (int x = 0; x < width; ++x) {
int r = image[3 * y * width + 3 * x];
int g = image[3 * y * width + 3 * x + 1];
int b = image[3 * y * width + 3 * x + 2];

        // RGB to YCbCr conversion formula
        float y = (0.299 * r + 0.587 * g + 0.114 * b);
        float cb = (0.568 * (r - y) + 0.713 * (g - y) + 0.212 * (b - y));
        float cr = (0.432 * (r - y) + 0.349 * (g - y) + 0.614 * (b - y));

        ycbcr_vec[3 * y * width + 3 * x] = y;
        ycbcr_vec[3 * y * width + 3 * x + 1] = cb;
        ycbcr_vec[3 * y * width + 3 * x + 2] = cr;
    }
}

// ZLib compression
// Note: ZLib does not support directly compressing vectors, so we need to convert the vector to a string before compressing it.
stringstream ss;
for (auto it : ycbcr_vec) {
    ss << it << ' ';
    if (it != ycbcr_vec.back()) ss << ' ';
}
ss << '\0';
vector<char> buffer = ss.str().c_str();
compress(buffer, filepath);

return {}; // Returning an empty vector instead of the original 'image' vector may cause issues. To avoid this, the 'image' vector should be passed as a reference or returned as a return value.

}

vector<uint8_t> decompress_image_rgb_to_YCbCr_and_zlib(string filename) {
// Decompress ZLib
vector buffer = decompress1(filename);

// Tokenize the decompressed string by ' '
vector<string> tokens = split(string(buffer.begin(), buffer.end()), " ");

// Parse each token into a float value
vector<float> ycbcr_vec;
for (auto token : tokens) {
    ycbcr_vec.push_back(stof(token));
}

// Reconstruct the original image from YCbCr values using RGB to YCbCr inverse formula
vector<uint8_t> image(3 * width * height);
for (int y = 0; y < height; ++y) {
    for (int x = 0; x < width; ++x) {
        int idx = 3 * y * width + 3 * x;
        float y_comp = ycbcr_vec[idx];
        float cb_comp = ycbcr_vec[idx + 1];
        float cr_comp = ycbcr_vec[idx + 2];

        // RGB to YCbCr inverse formula
        int r = (0.407 * y_comp + 0.454 * cb_comp + 0.040 * cr_comp);
        int g = (0.454 * y_comp + 0.454 * cb_comp + 0.437 * cr_comp);
        int b = (0.040 * y_comp + 0.436 * cb_comp + 0.615 * cr_comp);

        image[idx] = (r > 255) ? 255 : (r < 0) ? 0 : r;
        image[idx + 1] = (g > 255) ? 255 : (g < 0) ? 0 : g;
        image[idx + 2] = (b > 255) ? 255 : (b < 0) ? 0 : b;
    }
}

return image;

}

// Function to compress image using DCT + Quantization
vector<uint8_t> compress_image_dct_and_quantization(vector<uint8_t>& image, int width, int height, string filepath) {
// DCT + Quantization
int block_size = 8;
int num_blocks_x = (width + block_size - 1) / block_size;
int num_blocks_y = (height + block_size - 1) / block_size;

vector<float> dct_coeffs(num_blocks_x * num_blocks_y * 8 * 8);

for (int y = 0; y < num_blocks_y; ++y) {
    for (int x = 0; x < num_blocks_x; ++x) {
        int block_idx = y * num_blocks_x + x;
        for (int i = 0; i < 8; ++i) {
            for (int j = 0; j < 8; ++j) {
                int pixel_idx = 3 * (y * block_size + (i / 2)) * width + 3 * (x * block_size + (j / 2));
                float value = image[pixel_idx];
                dct_coeffs[block_idx * 64 + i * 8 + j] = value;
            }
        }
    }
}

// Quantization
vector<int> quant_table(64);
for (int i = 0; i < 64; ++i) {
    quant_table[i] = (i + 1) / 128;
}

vector<int> quantized_coeffs(num_blocks_x * num_blocks_y * 8 * 8);

for (int y = 0; y < num_blocks_y; ++y) {
    for (int x = 0; x < num_blocks_x; ++x) {
        int block_idx = y * num_blocks_x + x;
        for (int i = 0; i < 8; ++i) {
            for (int j = 0; j < 8; ++j) {
                int pixel_idx = y * block_size + (i / 2) * num_blocks_x + x * 8 + j;
                float dct_val = dct_coeffs[block_idx * 64 + i * 8 + j];
                int quant = quant_table[i * 8 + j];
                int quantized = dct_val / quant;
                quantized_coeffs[block_idx * 64 + i * 8 + j] = quantized;
            }
        }
    }
}

// Convert quantized coefficients to a string and compress it using ZLib
stringstream ss;
ss << quantized_coeffs.size() << '\n';
for (auto it : quantized_coeffs) {
    ss << it << ' ';
    if (it != quantized_coeffs.back()) ss << ' ';
}
ss << '\0';
vector<char> buffer = ss.str().c_str();
compress(buffer, filepath);

return {}; // Returning an empty vector instead of the original 'image' vector may cause issues. To avoid this, the 'image' vector should be passed as a reference or returned as a return value.

}

vector<uint8_t> decompress_image_dct_and_quantization(string filename) {
// Decompress ZLib
vector buffer = decompress1(filename);

// Tokenize the decompressed string by ' '
vector<string> tokens = split(string(buffer.begin(), buffer.end()), " ");

// Parse each token into an integer value and reconstruct the DCT coefficients
vector<int> quantized_coeffs;
for (auto token : tokens) {
    quantized_coeffs.push_back(stoi(token));
}

// Reconstruct the DCT coefficients and the original image using the inverse DCT formula
vector<float> dct_coeffs(quantized_coeffs.size());

for (int i = 0; i < quantized_coeffs.size(); ++i) {
    dct_coeffs[i] = quantized_coeffs[i] * 128;
}

int block_size = 8;
int num_blocks_x = (width + block_size - 1) / block_size;
int num_blocks_y = (height + block_size - 1) / block_size;

vector<uint8_t> image(3 * width * height);

for (int y = 0; y < num_blocks_y; ++y) {
    for (int x = 0; x < num_blocks_x; ++x) {
        int block_idx = y * num_blocks_x + x;
        for (int i = 0; i < 8; ++i) {
            for (int j = 0; j < 8; ++j) {
                float inverse_dct_val = dct_coeffs[block_idx * 64 + i * 8 + j];
                int idx = y * block_size + (i / 2) * num_blocks_x + x * 8 + j;

                if (i % 2 == 0 && j % 2 == 0) {
                    image[idx] = inverse_dct_val;
                    continue;
                }

                if (i % 2 == 0) {
                    image[idx] += image[idx - 1];
                }

                if (j % 2 == 0) {
                    image[idx] += image[idx - num_blocks_x];
                }

                image[idx] -= image[idx - num_blocks_x - 1];
                image[idx] += inverse_dct_val;
            }
        }
    }
}

return image;

}

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