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1 change: 1 addition & 0 deletions 07_COCO/submissions/zhao1991.json
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{"images": [{"id": 1, "width": 640, "height": 511, "file_name": "img1.jpg"}, {"id": 2, "width": 480, "height": 640, "file_name": "img2.jpg"}], "annotations": [{"id": 1, "image_id": 1, "category_id": 70, "segmentation": {"size": [511, 640], "counts": "j^]61`>1kB4X:OnF1gN6W:`1XE_N>6V:a1SE^Nd06U:]1SEbNe06T:X1TEfNe08S:S1TEjNf06T:S2iEoMV:R2hEoMX:S2dEPN[:R2bEPN]:Q2aEPN_:R2^EPNa:R2\\EPNc:Q2ZEQNf:e3O1O1WFfKk7Z4SHhKm7Y4QHhKo7Y4nGjKQ8V4mGlKS8U4jGnKU8S4hGoKX8Q4fGRLY8o3dGSL\\8n3aGTL_8l3_GWL`8j3]GXLc8c5O001O001O00001O001O001O00001O00O10000O10000O100O10000O10000O10000WN_GSLb8l3aGRL_8m3eGoK\\8o3iGnKW8Q4mGlKS8R4QHkKP8W2[G^Ni0XOl7W2_G_Ni0SOl7\\2^G^Nk0fNT8j2TG^N]:_1gE^N[:`1hE^NY:_1kE_NV:_1mE^NU:`1nE^NS:_1QF^NQ:`1RF^No9`1TF]Nn9`1VF[Nn9c1UFXNo9_1gDmM^1`0n9b1ZFYNj9f1XFUNl9j1UFRNo9l1S2E;D<E;D<EedS2"}, "area": 16534.0, "bbox": [411.0, 238.0, 93.0, 242.0], "iscrowd": 0}, {"id": 2, "image_id": 1, "category_id": 81, "segmentation": {"size": [511, 640], "counts": "Sk44]?`0@?M4N1O2M2O2N1N2O2N1O1N10000O101O000O10000O1000001N10000O1000000O10001O0O10000O1000000O101O0O1000000O10000O2O00000O10000O1000001N10000O1000000O10001O0000O2N100O2N100O2N100O2N100O2N101N1O101N1O101N1O101N1O101N1O101N1O101N1O101N1O101N2N2O1N1O2O1N2N101N2N2O1N1O2O1N2N101N2N2O1N1O2O1Nmec7"}, "area": 7553.0, "bbox": [9.0, 314.0, 142.0, 78.0], "iscrowd": 0}, {"id": 3, "image_id": 2, "category_id": 1, "segmentation": {"size": [640, 480], "counts": "oS]11nc02J0Y\\O2ec07N2N2N001O001O00001O0g\\O^OTc0b0l\\O^OTc0b0l\\O_OSc0b0k\\O@Tc0`0l\\O@Tc0`0l\\O_OUc0a0k\\O_OVc0`0i\\OAWc0c0100000001N2O001O010O1O00100O001O0010O01O00000000O1000001O0000000O100000000000000O1000000000000O100000000000000O1000000O1000000O10000000001O000O100SG]O]Nc0`1B^N>_1H^N8^1N`N2Y1ZO[Fg0Y8OZ1]O[Fg0Y8L\\1>bNB^1>bNB^1>cNA]1?cNA]1`0bN@^1`0bN@^1`0bN@^1`0bN@^1`0cN_O]1b0bN_O]1a0cN_O]1a0cN]O_1c0bN[O^1f0bNYO^1i0aNVO`J@Q2d0bLh0m6SO_JDf1U1dL5V7ROaJE^1c1`LH`7POdJFW1o1ZLCd7iNjJFPNKX2^2oL[Om7gNmJF]Mh0Y2`3]5SLmJX1iMVOGe3a7nKoJo7P5SHPKl7P5THSKi7m4XHUKf7j4ZHWKe7h4]HmIZO@Y8c6_HgI^OCT8f6`HaI3VO]7Y7bH[I6[OX7W7fHYI7_OS7h6XIcIKCm6f6^I]INLd6c6dISI67W6d6e4N2N1O2JiBaIY=_6XNgIQFX6f9WJUFh5i9`JRF`5l9gJoEX5o9QKjEP5T:WKfEi4X:_KbEa4\\:gK^EZ4i8eIZH[2gNP4i8SJTHW2nNf3l8\\JjGc8T8f1L3JUHnGV4n7kKWHR4g7PL\\Hn3a7TLbHi3\\7YLgHe3V7]LmHa3Q7`LPI`3m6jK_HZMf0k6h6lKhHTMa0P7d6mKmHPMb0S7_6mK\\JR4a5PL`JP4^5RLbJn3[5TLfJl3X5ULjJj3S5XLnJh3P5ZLPKf3o4ZLRKf3o4XLRKi3n4VLQKk3o4TLRKm3n4QLRKP4n4PLQKQ4P5mKPKU4P5nJkH_NV2c6o4mJnH^NQ2h6Q5gJSI]Nk1n6R5^I`I_OG2f1T7m6_HVJb7R92N3M3M4L3K5H8H8cE\\GV9k8hFXGT9o8fFSGW9U9ZFTGe9e9fFkEe8X:[GlEP8MkGY:5jEm77fGP:>iEi7i:UHZEh7h:UH[Ej7f:TH]Ei7f:SH^Ek7^;M2M4M2M4M2M4M2M4M3L3N3L3N3WOPCWJY=b5g0J6J6J6J6J6I7J6N2M3N2M3N2J7G9G9G:K2M4M2M4M2M4M2M;F?@5]Oc0I6J6J6IXhS3"}, "area": 37267.0, "bbox": [72.0, 69.0, 248.0, 442.0], "iscrowd": 0}, {"id": 4, "image_id": 2, "category_id": 43, "segmentation": {"size": [640, 480], "counts": "UjT3e0Yc04K5L4K4M4M3L4L4M2M2N2N2O1N2N2O1N2N2N2O2M1O101N1O1O100O2N2O1O103N1O1N2O0O0100O0iNU_OfNK3Sa0h0d_OoN[O8Sa0c0S@ZOQ`0`0T@\\OP`0>V@_On?6SaZ5"}, "area": 3004.0, "bbox": [161.0, 142.0, 46.0, 98.0], "iscrowd": 0}], "categories": [{"supercategory": "person", "id": 1, "name": "person"}, {"supercategory": "vehicle", "id": 2, "name": "bicycle"}, {"supercategory": "vehicle", "id": 3, "name": "car"}, {"supercategory": "vehicle", "id": 4, "name": "motorcycle"}, {"supercategory": "vehicle", "id": 5, "name": "airplane"}, {"supercategory": "vehicle", "id": 6, "name": "bus"}, {"supercategory": "vehicle", "id": 7, "name": "train"}, {"supercategory": "vehicle", "id": 8, "name": "truck"}, {"supercategory": "vehicle", "id": 9, "name": "boat"}, {"supercategory": "outdoor", "id": 10, "name": "traffic light"}, {"supercategory": "outdoor", "id": 11, "name": "fire hydrant"}, {"supercategory": "outdoor", "id": 13, "name": "stop sign"}, {"supercategory": "outdoor", "id": 14, "name": "parking meter"}, {"supercategory": "outdoor", "id": 15, "name": "bench"}, {"supercategory": "animal", "id": 16, "name": "bird"}, {"supercategory": "animal", "id": 17, "name": "cat"}, {"supercategory": "animal", "id": 18, "name": "dog"}, {"supercategory": "animal", "id": 19, "name": "horse"}, {"supercategory": "animal", "id": 20, "name": "sheep"}, {"supercategory": "animal", "id": 21, "name": "cow"}, {"supercategory": "animal", "id": 22, "name": "elephant"}, {"supercategory": "animal", "id": 23, "name": "bear"}, {"supercategory": "animal", "id": 24, "name": "zebra"}, {"supercategory": "animal", "id": 25, "name": "giraffe"}, {"supercategory": "accessory", "id": 27, "name": "backpack"}, {"supercategory": "accessory", "id": 28, "name": "umbrella"}, {"supercategory": "accessory", "id": 31, "name": "handbag"}, {"supercategory": "accessory", "id": 32, "name": "tie"}, {"supercategory": "accessory", "id": 33, "name": "suitcase"}, {"supercategory": "sports", "id": 34, "name": "frisbee"}, {"supercategory": "sports", "id": 35, "name": "skis"}, {"supercategory": "sports", "id": 36, "name": "snowboard"}, {"supercategory": "sports", "id": 37, "name": "sports ball"}, {"supercategory": "sports", "id": 38, "name": "kite"}, {"supercategory": "sports", "id": 39, "name": "baseball bat"}, {"supercategory": "sports", "id": 40, "name": "baseball glove"}, {"supercategory": "sports", "id": 41, "name": "skateboard"}, {"supercategory": "sports", "id": 42, "name": "surfboard"}, {"supercategory": "sports", "id": 43, "name": "tennis racket"}, {"supercategory": "kitchen", "id": 44, "name": "bottle"}, {"supercategory": "kitchen", "id": 46, "name": "wine glass"}, {"supercategory": "kitchen", "id": 47, "name": "cup"}, {"supercategory": "kitchen", "id": 48, "name": "fork"}, {"supercategory": "kitchen", "id": 49, "name": "knife"}, {"supercategory": "kitchen", "id": 50, "name": "spoon"}, {"supercategory": "kitchen", "id": 51, "name": "bowl"}, {"supercategory": "food", "id": 52, "name": "banana"}, {"supercategory": "food", "id": 53, "name": "apple"}, {"supercategory": "food", "id": 54, "name": "sandwich"}, {"supercategory": "food", "id": 55, "name": "orange"}, {"supercategory": "food", "id": 56, "name": "broccoli"}, {"supercategory": "food", "id": 57, "name": "carrot"}, {"supercategory": "food", "id": 58, "name": "hot dog"}, {"supercategory": "food", "id": 59, "name": "pizza"}, {"supercategory": "food", "id": 60, "name": "donut"}, {"supercategory": "food", "id": 61, "name": "cake"}, {"supercategory": "furniture", "id": 62, "name": "chair"}, {"supercategory": "furniture", "id": 63, "name": "couch"}, {"supercategory": "furniture", "id": 64, "name": "potted plant"}, {"supercategory": "furniture", "id": 65, "name": "bed"}, {"supercategory": "furniture", "id": 67, "name": "dining table"}, {"supercategory": "furniture", "id": 70, "name": "toilet"}, {"supercategory": "electronic", "id": 72, "name": "tv"}, {"supercategory": "electronic", "id": 73, "name": "laptop"}, {"supercategory": "electronic", "id": 74, "name": "mouse"}, {"supercategory": "electronic", "id": 75, "name": "remote"}, {"supercategory": "electronic", "id": 76, "name": "keyboard"}, {"supercategory": "electronic", "id": 77, "name": "cell phone"}, {"supercategory": "appliance", "id": 78, "name": "microwave"}, {"supercategory": "appliance", "id": 79, "name": "oven"}, {"supercategory": "appliance", "id": 80, "name": "toaster"}, {"supercategory": "appliance", "id": 81, "name": "sink"}, {"supercategory": "appliance", "id": 82, "name": "refrigerator"}, {"supercategory": "indoor", "id": 84, "name": "book"}, {"supercategory": "indoor", "id": 85, "name": "clock"}, {"supercategory": "indoor", "id": 86, "name": "vase"}, {"supercategory": "indoor", "id": 87, "name": "scissors"}, {"supercategory": "indoor", "id": 88, "name": "teddy bear"}, {"supercategory": "indoor", "id": 89, "name": "hair drier"}, {"supercategory": "indoor", "id": 90, "name": "toothbrush"}]}
137 changes: 137 additions & 0 deletions 07_COCO/submissions/zhao1991.py
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import json

import numpy as np
from PIL import Image
from pycocotools import mask


def main():

with open("annotations.txt") as file:
data = file.read().splitlines()
for row in data:
string_list = row.split(",")
# build the images dictionary
images = []
for i in range(1, 3):
image_data = {}
filename = "img" + str(i) + ".jpg"
img = Image.open(filename).convert("L")
image_data["id"] = i
image_data["width"] = img.size[0]
image_data["height"] = img.size[1]
image_data["file_name"] = filename
images.append(image_data)
# build the annotations dictionary
annotations = []
i = 0
for row in data[1:]:
string_list = row.split(",")
print(string_list)
ann_data = {}
ann_data["id"] = int(string_list[1])
ann_data["image_id"] = int(string_list[0][3:-4])
ann_data["category_id"] = int(string_list[2])
img = Image.open(string_list[3]).convert("L")
arr = np.array(img.getdata(), dtype=np.uint8).reshape(img.size[0], img.size[1], order="F")
Rs = mask.encode(np.asfortranarray(arr.transpose()))
ann_data["segmentation"] = Rs
# decode byte type to string type
Rs["counts"] = Rs["counts"].decode("utf-8")
ann_data["area"] = float(mask.area(Rs))
ann_data["bbox"] = mask.toBbox(Rs).tolist() # np.array to List
ann_data["iscrowd"] = 0
annotations.append(ann_data)
i += 1
# build the categories dictionary (copy)
categories = [
{"supercategory": "person", "id": 1, "name": "person"},
{"supercategory": "vehicle", "id": 2, "name": "bicycle"},
{"supercategory": "vehicle", "id": 3, "name": "car"},
{"supercategory": "vehicle", "id": 4, "name": "motorcycle"},
{"supercategory": "vehicle", "id": 5, "name": "airplane"},
{"supercategory": "vehicle", "id": 6, "name": "bus"},
{"supercategory": "vehicle", "id": 7, "name": "train"},
{"supercategory": "vehicle", "id": 8, "name": "truck"},
{"supercategory": "vehicle", "id": 9, "name": "boat"},
{"supercategory": "outdoor", "id": 10, "name": "traffic light"},
{"supercategory": "outdoor", "id": 11, "name": "fire hydrant"},
{"supercategory": "outdoor", "id": 13, "name": "stop sign"},
{"supercategory": "outdoor", "id": 14, "name": "parking meter"},
{"supercategory": "outdoor", "id": 15, "name": "bench"},
{"supercategory": "animal", "id": 16, "name": "bird"},
{"supercategory": "animal", "id": 17, "name": "cat"},
{"supercategory": "animal", "id": 18, "name": "dog"},
{"supercategory": "animal", "id": 19, "name": "horse"},
{"supercategory": "animal", "id": 20, "name": "sheep"},
{"supercategory": "animal", "id": 21, "name": "cow"},
{"supercategory": "animal", "id": 22, "name": "elephant"},
{"supercategory": "animal", "id": 23, "name": "bear"},
{"supercategory": "animal", "id": 24, "name": "zebra"},
{"supercategory": "animal", "id": 25, "name": "giraffe"},
{"supercategory": "accessory", "id": 27, "name": "backpack"},
{"supercategory": "accessory", "id": 28, "name": "umbrella"},
{"supercategory": "accessory", "id": 31, "name": "handbag"},
{"supercategory": "accessory", "id": 32, "name": "tie"},
{"supercategory": "accessory", "id": 33, "name": "suitcase"},
{"supercategory": "sports", "id": 34, "name": "frisbee"},
{"supercategory": "sports", "id": 35, "name": "skis"},
{"supercategory": "sports", "id": 36, "name": "snowboard"},
{"supercategory": "sports", "id": 37, "name": "sports ball"},
{"supercategory": "sports", "id": 38, "name": "kite"},
{"supercategory": "sports", "id": 39, "name": "baseball bat"},
{"supercategory": "sports", "id": 40, "name": "baseball glove"},
{"supercategory": "sports", "id": 41, "name": "skateboard"},
{"supercategory": "sports", "id": 42, "name": "surfboard"},
{"supercategory": "sports", "id": 43, "name": "tennis racket"},
{"supercategory": "kitchen", "id": 44, "name": "bottle"},
{"supercategory": "kitchen", "id": 46, "name": "wine glass"},
{"supercategory": "kitchen", "id": 47, "name": "cup"},
{"supercategory": "kitchen", "id": 48, "name": "fork"},
{"supercategory": "kitchen", "id": 49, "name": "knife"},
{"supercategory": "kitchen", "id": 50, "name": "spoon"},
{"supercategory": "kitchen", "id": 51, "name": "bowl"},
{"supercategory": "food", "id": 52, "name": "banana"},
{"supercategory": "food", "id": 53, "name": "apple"},
{"supercategory": "food", "id": 54, "name": "sandwich"},
{"supercategory": "food", "id": 55, "name": "orange"},
{"supercategory": "food", "id": 56, "name": "broccoli"},
{"supercategory": "food", "id": 57, "name": "carrot"},
{"supercategory": "food", "id": 58, "name": "hot dog"},
{"supercategory": "food", "id": 59, "name": "pizza"},
{"supercategory": "food", "id": 60, "name": "donut"},
{"supercategory": "food", "id": 61, "name": "cake"},
{"supercategory": "furniture", "id": 62, "name": "chair"},
{"supercategory": "furniture", "id": 63, "name": "couch"},
{"supercategory": "furniture", "id": 64, "name": "potted plant"},
{"supercategory": "furniture", "id": 65, "name": "bed"},
{"supercategory": "furniture", "id": 67, "name": "dining table"},
{"supercategory": "furniture", "id": 70, "name": "toilet"},
{"supercategory": "electronic", "id": 72, "name": "tv"},
{"supercategory": "electronic", "id": 73, "name": "laptop"},
{"supercategory": "electronic", "id": 74, "name": "mouse"},
{"supercategory": "electronic", "id": 75, "name": "remote"},
{"supercategory": "electronic", "id": 76, "name": "keyboard"},
{"supercategory": "electronic", "id": 77, "name": "cell phone"},
{"supercategory": "appliance", "id": 78, "name": "microwave"},
{"supercategory": "appliance", "id": 79, "name": "oven"},
{"supercategory": "appliance", "id": 80, "name": "toaster"},
{"supercategory": "appliance", "id": 81, "name": "sink"},
{"supercategory": "appliance", "id": 82, "name": "refrigerator"},
{"supercategory": "indoor", "id": 84, "name": "book"},
{"supercategory": "indoor", "id": 85, "name": "clock"},
{"supercategory": "indoor", "id": 86, "name": "vase"},
{"supercategory": "indoor", "id": 87, "name": "scissors"},
{"supercategory": "indoor", "id": 88, "name": "teddy bear"},
{"supercategory": "indoor", "id": 89, "name": "hair drier"},
{"supercategory": "indoor", "id": 90, "name": "toothbrush"},
]
# lastly combine all the individual pieces into a big dict
python_dict = {"images": images, "annotations": annotations, "categories": categories}
# save the json format in a file
with open("zhao1991.json", "w") as outfile:
json.dump(python_dict, outfile)


if __name__ == "__main__":
main()