for image_path in files: try: #did this because the first file was not readable original_image = cv2.imread(image_path) (H,W) = original_image.shape[:2] except: continue image = original_image.copy() image_features = [] mouth = pants = shoes = 0 tshirt = shorts = sneakers = 0 image_name = os.path.basename(os.path.normpath(image_path)) if image_name.startswith('b'): class_name = 0 else: class_name=1 for height in range(0,H): for width in range(0,W): blue = image.item(height,width,0) #here we are extracting the blue,green and red colour in a particluar pixel . #Since cv2 library takes the colour channels as BGr instead of RGB; we pass #axis = 0 for blue,axis=1 for green,axis=2 for red green = image.item(height,width,1) red = image.item(height,width,2) # Homer - blue pants if (blue >= 150 and blue <= 180 and green >= 98 and green <= 120 and red >= 0 and red <= 90): image[height, width] = [0, 255, 255] pants += 1 # Homer - brown mouth if (blue >= 95 and blue <= 140 and green >= 160 and green <= 185 and red >= 175 and red <= 200): image[height, width] = [0, 255, 255] mouth += 1 # Homer - gray shoes if height > (H / 2): if (blue >= 25 and blue <= 45 and green >= 25 and green <= 45 and red >= 25 and red <= 45): image[height, width] = [0, 255, 255] shoes += 1 # Bart - orange t-shirt if (blue >= 11 and blue <= 22 and green >= 85 and green <= 105 and red >= 240 and red <= 255): image[height, width] = [0, 255, 128] tshirt += 1 # Bart - blue shorts if (blue >= 125 and blue <= 170 and green >= 0 and green <= 12 and red >= 0 and red <= 20): image[height, width] = [0, 255, 128] shorts += 1 # Bart - blue sneakers if height > (H / 2): if (blue >= 125 and blue <= 170 and green >= 0 and green <= 12 and red >= 0 and red <= 20): image[height, width] = [0, 255, 128] sneakers += 1 mouth = round((mouth / (H * W)) * 100, 9) #calculating how much percent of the total image is the mouth pants = round((pants / (H * W)) * 100, 9) shoes = round((shoes / (H * W)) * 100, 9) tshirt = round((tshirt / (H * W)) * 100, 9) shorts = round((shorts / (H * W)) * 100, 9) sneakers = round((sneakers / (H * W)) * 100, 9) image_features.append(mouth) image_features.append(pants) image_features.append(shoes) image_features.append(tshirt) image_features.append(shorts) image_features.append(sneakers) image_features.append(class_name) features.append(image_features) print('Homer mouth: %s - Homer pants: %s - Homer shoes: %s' % (image_features[0], image_features[1], image_features[2])) print('Bart t-shirt: %s - Bart shorts: %s - Bart sneakers: %s' % (image_features[3], image_features[4], image_features[5])) #converting the list values into string format f = (",".join([str(item) for item in image_features])) export += f + '\n' if show_images == True: image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) original_image = cv2.cvtColor(original_image, cv2.COLOR_BGR2RGB) fig, im = plt.subplots(1, 2) im[0].axis('off') im[0].imshow(original_image) im[1].axis('off') im[1].imshow(image) plt.show()