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Im following this ARG i found recently called neiz or whatever, their most recent video features a grid of pixels that a friend helped me sorta isolate in video editing software. It changes twice every second, and while he tried to lower the fps and reduce the amnt of images, the base number is still around 2k,
here are two grids and a duplicate of each;
because the grid was not perfectly tracked and un-distorted it changes from frame to frame at the start, but the color information is the same across several frames. How do i get rid of images that contain the same grid of colors and only keep one copy of it?
COLORS_AS_RGB = { 'red': np.array([255, 22, 1], dtype=np.uint8), 'green': np.array([0, 216, 0], dtype=np.uint8), 'blue': np.array([0, 15, 255], dtype=np.uint8) } # ... for i in range(0, len(images)-1): img_1_r_mask = cv2.inRange(images[i], COLORS_AS_RGB['red'], COLORS_AS_RGB['red']) img_1_g_mask = cv2.inRange(images[i], COLORS_AS_RGB['green'], COLORS_AS_RGB['green']) img_1_b_mask = cv2.inRange(images[i], COLORS_AS_RGB['blue'], COLORS_AS_RGB['blue']) img_1_c_mask = cv2.bitwise_or(img_1_r_mask, cv2.bitwise_or(img_1_g_mask, img_1_b_mask)) img_2_r_mask = cv2.inRange(images[i+1], COLORS_AS_RGB['red'], COLORS_AS_RGB['red']) img_2_g_mask = cv2.inRange(images[i+1], COLORS_AS_RGB['green'], COLORS_AS_RGB['green']) img_2_b_mask = cv2.inRange(images[i+1], COLORS_AS_RGB['blue'], COLORS_AS_RGB['blue']) img_2_c_mask = cv2.bitwise_or(img_2_r_mask, cv2.bitwise_or(img_2_g_mask, img_2_b_mask)) delta_mask = cv2.bitwise_xor(img_1_c_mask, img_2_c_mask) print(cv2.countNonZero(delta_mask)) if cv2.countNonZero(delta_mask) > 50: subset.append(images[i+1])Im just wondering if there's any functions or methods that would be better suited for this
