Wasp face project

wasp_faces/Denoise

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+import numpy as np
+import os
+import cv2
+from pathlib import Path
+from matplotlib import pyplot as plt
+
+dir = #r"file path"
+
+for filename in os.listdir(dir):
+    if filename.endswith(".jpg"):
+        #read image
+        path = (dir + '\\' + filename)
+        print(path)
+        src = cv2.imread(path, cv2.IMREAD_UNCHANGED)
+
+        #denoise
+        dst = cv2.fastNlMeansDenoisingColored(src, None, 10, 10, 7, 21)
+        plt.subplot(121), plt.imshow(src)
+        plt.subplot(122), plt.imshow(dst)
+        plt.show()
+
+        #save image
+        file_no_ext = Path(dir + "\\" + filename).stem
+        cv2.imwrite(#fr"directory where images will be saved/{file_no_ext}_nobg.jpg" ,dst)
+
+    else:
+        continue

wasp_faces/Grabcut.py

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+#adapted from https://github.com/opencv/opencv/blob/master/samples/python/grabcut.py
+'''
+===============================================================================
+Interactive Image Segmentation using GrabCut algorithm.
+This sample shows interactive image segmentation using grabcut algorithm.
+USAGE:
+    python grabcut.py <filename>
+README FIRST:
+    Two windows will show up, one for input and one for output.
+    At first, in input window, draw a rectangle around the object using the
+right mouse button. Then press 'n' to segment the object (once or a few times)
+For any finer touch-ups, you can press any of the keys below and draw lines on
+the areas you want. Then again press 'n' to update the output.
+Key '0' - To select areas of sure background
+Key '1' - To select areas of sure foreground
+Key '2' - To select areas of probable background
+Key '3' - To select areas of probable foreground
+Key 'n' - To update the segmentation
+Key 'r' - To reset the setup
+Key 's' - To save the results
+===============================================================================
+'''
+
+# Python 2/3 compatibility
+from __future__ import print_function
+
+from pathlib import Path
+import os
+
+import numpy as np
+import cv2 as cv
+
+import sys
+
+class App():
+    BLUE = [255,0,0]        # rectangle color
+    RED = [0,0,255]         # PR BG
+    GREEN = [0,255,0]       # PR FG
+    BLACK = [0,0,0]         # sure BG
+    WHITE = [255,255,255]   # sure FG
+
+    DRAW_BG = {'color' : BLACK, 'val' : 0}
+    DRAW_FG = {'color' : WHITE, 'val' : 1}
+    DRAW_PR_BG = {'color' : RED, 'val' : 2}
+    DRAW_PR_FG = {'color' : GREEN, 'val' : 3}
+
+    # setting up flags
+    rect = (0,0,1,1)
+    drawing = False         # flag for drawing curves
+    rectangle = False       # flag for drawing rect
+    rect_over = False       # flag to check if rect drawn
+    rect_or_mask = 100      # flag for selecting rect or mask mode
+    value = DRAW_FG         # drawing initialized to FG
+    thickness = 2           # brush thickness
+
+    def onmouse(self, event, x, y, flags, param):
+        # Draw Rectangle
+        if event == cv.EVENT_RBUTTONDOWN:
+            self.rectangle = True
+            self.ix, self.iy = x,y
+
+        elif event == cv.EVENT_MOUSEMOVE:
+            if self.rectangle == True:
+                self.img = self.img2.copy()
+                cv.rectangle(self.img, (self.ix, self.iy), (x, y), self.BLUE, 2)
+                self.rect = (min(self.ix, x), min(self.iy, y), abs(self.ix - x), abs(self.iy - y))
+                self.rect_or_mask = 0
+
+        elif event == cv.EVENT_RBUTTONUP:
+            self.rectangle = False
+            self.rect_over = True
+            cv.rectangle(self.img, (self.ix, self.iy), (x, y), self.BLUE, 2)
+            self.rect = (min(self.ix, x), min(self.iy, y), abs(self.ix - x), abs(self.iy - y))
+            self.rect_or_mask = 0
+            print(" Now press the key 'n' a few times until no further change \n")
+
+        # draw touchup curves
+
+        if event == cv.EVENT_LBUTTONDOWN:
+            if self.rect_over == False:
+                print("first draw rectangle \n")
+            else:
+                self.drawing = True
+                cv.circle(self.img, (x,y), self.thickness, self.value['color'], -1)
+                cv.circle(self.mask, (x,y), self.thickness, self.value['val'], -1)
+
+        elif event == cv.EVENT_MOUSEMOVE:
+            if self.drawing == True:
+                cv.circle(self.img, (x, y), self.thickness, self.value['color'], -1)
+                cv.circle(self.mask, (x, y), self.thickness, self.value['val'], -1)
+
+        elif event == cv.EVENT_LBUTTONUP:
+            if self.drawing == True:
+                self.drawing = False
+                cv.circle(self.img, (x, y), self.thickness, self.value['color'], -1)
+                cv.circle(self.mask, (x, y), self.thickness, self.value['val'], -1)
+
+    def run(self):
+
+        dir = #r"directory of images to segment"
+        print(dir)
+
+        for filename in os.listdir(dir):
+            if filename.endswith(".JPG"):
+                # read image
+                path = (dir + '\\' + filename)
+                print(path)
+
+                self.img = cv.imread(path, cv.IMREAD_UNCHANGED)
+
+                self.img2 = self.img.copy()                               # a copy of original image
+                self.mask = np.zeros(self.img.shape[:2], dtype = np.uint8) # mask initialized to PR_BG
+                self.output = np.zeros(self.img.shape, np.uint8)           # output image to be shown
+
+                # input and output windows
+                cv.namedWindow('output', cv.WINDOW_NORMAL)
+                cv.namedWindow('input', cv.WINDOW_NORMAL)
+                cv.setMouseCallback('input', self.onmouse)
+                cv.moveWindow('input', self.img.shape[1]+10,90)
+
+                print(" Instructions: \n")
+                print(" Draw a rectangle around the object using right mouse button \n")
+
+                while(1):
+
+                    cv.imshow('output', self.output)
+                    cv.imshow('input', self.img)
+                    k = cv.waitKey(1)
+
+                    # key bindings
+                    if k == 27:         # esc to exit
+                        break
+                    elif k == ord('0'): # BG drawing
+                        print(" mark background regions with left mouse button \n")
+                        self.value = self.DRAW_BG
+                    elif k == ord('1'): # FG drawing
+                        print(" mark foreground regions with left mouse button \n")
+                        self.value = self.DRAW_FG
+                    elif k == ord('2'): # PR_BG drawing
+                        self.value = self.DRAW_PR_BG
+                    elif k == ord('3'): # PR_FG drawing
+                        self.value = self.DRAW_PR_FG
+                    elif k == ord('s'): # save image
+                        bar = np.zeros((self.img.shape[0], 5, 3), np.uint8)
+                        res = np.hstack((bar, self.output))
+                        file_no_ext = Path(dir + "\\" + filename).stem
+                        cv.imwrite(#fr"directory where images will be saved/{file_no_ext}_nobg.jpg" ,res)
+                        print(" Result saved as image \n")
+                    elif k == ord('r'): # reset everything
+                        print("resetting \n")
+                        self.rect = (0,0,1,1)
+                        self.drawing = False
+                        self.rectangle = False
+                        self.rect_or_mask = 100
+                        self.rect_over = False
+                        self.value = self.DRAW_FG
+                        self.img = self.img2.copy()
+                        self.mask = np.zeros(self.img.shape[:2], dtype = np.uint8) # mask initialized to PR_BG
+                        self.output = np.zeros(self.img.shape, np.uint8)           # output image to be shown
+                    elif k == ord('n'): # segment the image
+                        print(""" For finer touchups, mark foreground and background after pressing keys 0-3
+                        and again press 'n' \n""")
+                        try:
+                            bgdmodel = np.zeros((1, 65), np.float64)
+                            fgdmodel = np.zeros((1, 65), np.float64)
+                            if (self.rect_or_mask == 0):         # grabcut with rect
+                                cv.grabCut(self.img2, self.mask, self.rect, bgdmodel, fgdmodel, 1, cv.GC_INIT_WITH_RECT)
+                                self.rect_or_mask = 1
+                            elif (self.rect_or_mask == 1):       # grabcut with mask
+                                cv.grabCut(self.img2, self.mask, self.rect, bgdmodel, fgdmodel, 1, cv.GC_INIT_WITH_MASK)
+                        except:
+                            import traceback
+                            traceback.print_exc()
+
+                    mask2 = np.where((self.mask==1) + (self.mask==3), 255, 0).astype('uint8')
+                    self.output = cv.bitwise_and(self.img2, self.img2, mask=mask2)
+
+                print('Done')
+
+            else:
+                continue
+
+if __name__ == '__main__':
+    print(__doc__)
+    App().run()
+    cv.destroyAllWindows()

wasp_faces/SIFT

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+import numpy as np
+import matplotlib.pyplot as plt
+import cv2 as cv
+import skimage.segmentation
+import skimage.color as color
+
+img = cv.imread(#r'file path', cv.IMREAD_UNCHANGED)
+
+img_fz = skimage.segmentation.felzenszwalb(img)
+img_fz_col = color.label2rgb(img_fz, img, kind='avg')
+plt.imshow(img_fz_col)
+
+img_slic = skimage.segmentation.slic(img_fz_col, n_segments=200, compactness=10)
+#label2rgb replaces each discrete label with the average interior color
+img_av = color.label2rgb(img_slic, img_fz_col, kind='avg')
+plt.imshow(img_av)
+plt.show()
+
+gray= cv.cvtColor(img_av, cv.COLOR_BGR2GRAY)
+sift = cv.xfeatures2d.SIFT_create()
+kp = sift.detect(img_av,None)
+img_sift = cv.drawKeypoints(img_av,kp,None)
+plt.imshow(img_sift)
+plt.show()