| | |
| | | |
| | | def find_biggest_blob(image, original_image,sid_mask): |
| | | if sid_mask[0] == "1": |
| | | move_left = 45 |
| | | move_left = 35 |
| | | elif sid_mask[0] == "x": |
| | | move_left = 55 |
| | | move_left = 40 |
| | | else: |
| | | move_left = 0 |
| | | # Remove noise |
| | | image2 = cv2.morphologyEx( |
| | | original_image, cv2.MORPH_OPEN, kernel(2, 2), iterations=7 |
| | | original_image, cv2.MORPH_OPEN, kernel(2, 2), iterations=3 |
| | | ) |
| | | # find biggest block of pixels |
| | | image1 = cv2.morphologyEx(image2, cv2.MORPH_DILATE, kernel(5, 25), iterations=4) |
| | |
| | | sid_err = [] |
| | | image = 255 - image |
| | | image_original = image.copy() |
| | | image = img_as_ubyte(image > 100) |
| | | image = img_as_ubyte(image > 70) |
| | | cv2.imwrite("/tmp/enSID0.png", image) |
| | | |
| | | # Remove noise |
| | | image = cv2.morphologyEx(image, cv2.MORPH_OPEN, kernel(2, 2), iterations=3) |
| | | #image = cv2.morphologyEx(image, cv2.MORPH_OPEN, kernel(2, 2), iterations=3) |
| | | |
| | | # Closing. Connect non connected parts |
| | | image = cv2.morphologyEx(image, cv2.MORPH_CLOSE, kernel(5, 3), iterations=4) |
| | | image = cv2.morphologyEx(image, cv2.MORPH_CLOSE, kernel(5, 1), iterations=4) |
| | | |
| | | # Again noise removal after closing |
| | | # image = cv2.morphologyEx(image, cv2.MORPH_OPEN, kernel(8, 8), iterations=1) |