| import cv2 |
| import numpy as np |
| from config.CONFIG_UIED import Config |
| C = Config() |
|
|
|
|
| def read_img(path, resize_height=None, kernel_size=None): |
|
|
| def resize_by_height(org): |
| w_h_ratio = org.shape[1] / org.shape[0] |
| resize_w = resize_height * w_h_ratio |
| re = cv2.resize(org, (int(resize_w), int(resize_height))) |
| return re |
|
|
| try: |
| img = cv2.imread(path) |
| if kernel_size is not None: |
| img = cv2.medianBlur(img, kernel_size) |
| if img is None: |
| print("*** Image does not exist ***") |
| return None, None |
| if resize_height is not None: |
| img = resize_by_height(img) |
| gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) |
| return img, gray |
|
|
| except Exception as e: |
| print(e) |
| print("*** Img Reading Failed ***\n") |
| return None, None |
|
|
|
|
| def gray_to_gradient(img): |
| if len(img.shape) == 3: |
| img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) |
| img_f = np.copy(img) |
| img_f = img_f.astype("float") |
|
|
| kernel_h = np.array([[0,0,0], [0,-1.,1.], [0,0,0]]) |
| kernel_v = np.array([[0,0,0], [0,-1.,0], [0,1.,0]]) |
| dst1 = abs(cv2.filter2D(img_f, -1, kernel_h)) |
| dst2 = abs(cv2.filter2D(img_f, -1, kernel_v)) |
| gradient = (dst1 + dst2).astype('uint8') |
| return gradient |
|
|
|
|
| def reverse_binary(bin, show=False): |
| """ |
| Reverse the input binary image |
| """ |
| r, bin = cv2.threshold(bin, 1, 255, cv2.THRESH_BINARY_INV) |
| if show: |
| cv2.imshow('binary_rev', bin) |
| cv2.waitKey() |
| return bin |
|
|
|
|
| def binarization(org, grad_min, show=False, write_path=None, wait_key=0): |
| grey = cv2.cvtColor(org, cv2.COLOR_BGR2GRAY) |
| grad = gray_to_gradient(grey) |
| rec, binary = cv2.threshold(grad, grad_min, 255, cv2.THRESH_BINARY) |
| morph = cv2.morphologyEx(binary, cv2.MORPH_CLOSE, (3, 3)) |
| if write_path is not None: |
| cv2.imwrite(write_path, morph) |
| if show: |
| cv2.imshow('binary', morph) |
| if wait_key is not None: |
| cv2.waitKey(wait_key) |
| return morph |
|
|
