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contours: rename 'pixel' → 'label' for clarity

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Robert Sachunsky 2025-08-26 21:06:36 +02:00
parent dbbf1073df
commit eae1303ebb
1 changed files with 12 additions and 12 deletions
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24
src/eynollah/utils/contour.py
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@ -141,12 +141,12 @@ def return_parent_contours(contours, hierarchy):
if hierarchy[0][i][3] == -1] if hierarchy[0][i][3] == -1]
return contours_parent return contours_parent
def return_contours_of_interested_region(region_pre_p, pixel, min_area=0.0002): def return_contours_of_interested_region(region_pre_p, label, min_area=0.0002):
# pixels of images are identified by 5 # pixels of images are identified by 5
if len(region_pre_p.shape) == 3: if len(region_pre_p.shape) == 3:
cnts_images = (region_pre_p[:, :, 0] == pixel) * 1 cnts_images = (region_pre_p[:, :, 0] == label) * 1
else: else:
cnts_images = (region_pre_p[:, :] == pixel) * 1 cnts_images = (region_pre_p[:, :] == label) * 1
cnts_images = cnts_images.astype(np.uint8) cnts_images = cnts_images.astype(np.uint8)
cnts_images = np.repeat(cnts_images[:, :, np.newaxis], 3, axis=2) cnts_images = np.repeat(cnts_images[:, :, np.newaxis], 3, axis=2)
imgray = cv2.cvtColor(cnts_images, cv2.COLOR_BGR2GRAY) imgray = cv2.cvtColor(cnts_images, cv2.COLOR_BGR2GRAY)
@ -264,12 +264,12 @@ def get_textregion_contours_in_org_image_light(cnts, img, confidence_matrix, map
confs.append(np.sum(confidence_matrix * cnt_mask) / np.sum(cnt_mask)) confs.append(np.sum(confidence_matrix * cnt_mask) / np.sum(cnt_mask))
return cnts, confs return cnts, confs
def return_contours_of_interested_textline(region_pre_p, pixel): def return_contours_of_interested_textline(region_pre_p, label):
# pixels of images are identified by 5 # pixels of images are identified by 5
if len(region_pre_p.shape) == 3: if len(region_pre_p.shape) == 3:
cnts_images = (region_pre_p[:, :, 0] == pixel) * 1 cnts_images = (region_pre_p[:, :, 0] == label) * 1
else: else:
cnts_images = (region_pre_p[:, :] == pixel) * 1 cnts_images = (region_pre_p[:, :] == label) * 1
cnts_images = cnts_images.astype(np.uint8) cnts_images = cnts_images.astype(np.uint8)
cnts_images = np.repeat(cnts_images[:, :, np.newaxis], 3, axis=2) cnts_images = np.repeat(cnts_images[:, :, np.newaxis], 3, axis=2)
imgray = cv2.cvtColor(cnts_images, cv2.COLOR_BGR2GRAY) imgray = cv2.cvtColor(cnts_images, cv2.COLOR_BGR2GRAY)
@ -292,12 +292,12 @@ def return_contours_of_image(image):
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
return contours, hierarchy return contours, hierarchy
def return_contours_of_interested_region_by_min_size(region_pre_p, pixel, min_size=0.00003): def return_contours_of_interested_region_by_min_size(region_pre_p, label, min_size=0.00003):
# pixels of images are identified by 5 # pixels of images are identified by 5
if len(region_pre_p.shape) == 3: if len(region_pre_p.shape) == 3:
cnts_images = (region_pre_p[:, :, 0] == pixel) * 1 cnts_images = (region_pre_p[:, :, 0] == label) * 1
else: else:
cnts_images = (region_pre_p[:, :] == pixel) * 1 cnts_images = (region_pre_p[:, :] == label) * 1
cnts_images = cnts_images.astype(np.uint8) cnts_images = cnts_images.astype(np.uint8)
cnts_images = np.repeat(cnts_images[:, :, np.newaxis], 3, axis=2) cnts_images = np.repeat(cnts_images[:, :, np.newaxis], 3, axis=2)
imgray = cv2.cvtColor(cnts_images, cv2.COLOR_BGR2GRAY) imgray = cv2.cvtColor(cnts_images, cv2.COLOR_BGR2GRAY)
@ -310,12 +310,12 @@ def return_contours_of_interested_region_by_min_size(region_pre_p, pixel, min_si
return contours_imgs return contours_imgs
def return_contours_of_interested_region_by_size(region_pre_p, pixel, min_area, max_area): def return_contours_of_interested_region_by_size(region_pre_p, label, min_area, max_area):
# pixels of images are identified by 5 # pixels of images are identified by 5
if len(region_pre_p.shape) == 3: if len(region_pre_p.shape) == 3:
cnts_images = (region_pre_p[:, :, 0] == pixel) * 1 cnts_images = (region_pre_p[:, :, 0] == label) * 1
else: else:
cnts_images = (region_pre_p[:, :] == pixel) * 1 cnts_images = (region_pre_p[:, :] == label) * 1
cnts_images = cnts_images.astype(np.uint8) cnts_images = cnts_images.astype(np.uint8)
cnts_images = np.repeat(cnts_images[:, :, np.newaxis], 3, axis=2) cnts_images = np.repeat(cnts_images[:, :, np.newaxis], 3, axis=2)
imgray = cv2.cvtColor(cnts_images, cv2.COLOR_BGR2GRAY) imgray = cv2.cvtColor(cnts_images, cv2.COLOR_BGR2GRAY)