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sbb_pixelwise_segmentation
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Code Issues Releases Wiki Activity

early_erosion is added

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unifying-training-models
vahidrezanezhad 4 months ago
parent cca4d17823
commit 4150675621
1 changed files with 10 additions and 4 deletions
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14
gt_gen_utils.py
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@ -93,7 +93,7 @@ def return_contours_of_interested_region(region_pre_p, pixel, min_area=0.0002):
#contours_imgs = filter_contours_area_of_image_tables(thresh, contours_imgs, hierarchy, max_area=1, min_area=min_area) #contours_imgs = filter_contours_area_of_image_tables(thresh, contours_imgs, hierarchy, max_area=1, min_area=min_area)
return contours_imgs return contours_imgs
def update_region_contours(co_text, img_boundary, erosion_rate, dilation_rate, y_len, x_len, dilation_early=None): def update_region_contours(co_text, img_boundary, erosion_rate, dilation_rate, y_len, x_len, dilation_early=None, erosion_early=None):
co_text_eroded = [] co_text_eroded = []
for con in co_text: for con in co_text:
img_boundary_in = np.zeros( (y_len,x_len) ) img_boundary_in = np.zeros( (y_len,x_len) )
@ -102,6 +102,9 @@ def update_region_contours(co_text, img_boundary, erosion_rate, dilation_rate, y
if dilation_early: if dilation_early:
img_boundary_in = cv2.dilate(img_boundary_in[:,:], KERNEL, iterations=dilation_early) img_boundary_in = cv2.dilate(img_boundary_in[:,:], KERNEL, iterations=dilation_early)
if erosion_early:
img_boundary_in = cv2.erode(img_boundary_in[:,:], KERNEL, iterations=erosion_early)
#img_boundary_in = cv2.erode(img_boundary_in[:,:], KERNEL, iterations=7)#asiatica #img_boundary_in = cv2.erode(img_boundary_in[:,:], KERNEL, iterations=7)#asiatica
if erosion_rate > 0: if erosion_rate > 0:
img_boundary_in = cv2.erode(img_boundary_in[:,:], KERNEL, iterations=erosion_rate) img_boundary_in = cv2.erode(img_boundary_in[:,:], KERNEL, iterations=erosion_rate)
@ -137,6 +140,7 @@ def get_images_of_ground_truth(gt_list, dir_in, output_dir, output_type, config_
ls_org_imgs_stem = [item.split('.')[0] for item in ls_org_imgs] ls_org_imgs_stem = [item.split('.')[0] for item in ls_org_imgs]
for index in tqdm(range(len(gt_list))): for index in tqdm(range(len(gt_list))):
#try: #try:
print(gt_list[index])
tree1 = ET.parse(dir_in+'/'+gt_list[index], parser = ET.XMLParser(encoding = 'iso-8859-5')) tree1 = ET.parse(dir_in+'/'+gt_list[index], parser = ET.XMLParser(encoding = 'iso-8859-5'))
root1=tree1.getroot() root1=tree1.getroot()
alltags=[elem.tag for elem in root1.iter()] alltags=[elem.tag for elem in root1.iter()]
@ -271,8 +275,9 @@ def get_images_of_ground_truth(gt_list, dir_in, output_dir, output_type, config_
img_boundary = np.zeros((y_len, x_len)) img_boundary = np.zeros((y_len, x_len))
erosion_rate = 0#1 erosion_rate = 0#1
dilation_rate = 2 dilation_rate = 2
dilation_early = 1 dilation_early = 0
co_use_case, img_boundary = update_region_contours(co_use_case, img_boundary, erosion_rate, dilation_rate, y_len, x_len, dilation_early=dilation_early ) erosion_early = 2
co_use_case, img_boundary = update_region_contours(co_use_case, img_boundary, erosion_rate, dilation_rate, y_len, x_len, dilation_early=dilation_early, erosion_early=erosion_early)
img = np.zeros((y_len, x_len, 3)) img = np.zeros((y_len, x_len, 3))
@ -280,7 +285,8 @@ def get_images_of_ground_truth(gt_list, dir_in, output_dir, output_type, config_
img_poly = cv2.fillPoly(img, pts=co_use_case, color=(1, 1, 1)) img_poly = cv2.fillPoly(img, pts=co_use_case, color=(1, 1, 1))
if "artificial_class_label" in keys: if "artificial_class_label" in keys:
img_mask = np.copy(img_poly) img_mask = np.copy(img_poly)
img_poly[:,:][(img_boundary[:,:]==1) & (img_mask[:,:,0]!=1)] = artificial_class_label ##img_poly[:,:][(img_boundary[:,:]==1) & (img_mask[:,:,0]!=1)] = artificial_class_label
img_poly[:,:][img_boundary[:,:]==1] = artificial_class_label
elif output_type == '3d': elif output_type == '3d':
img_poly = cv2.fillPoly(img, pts=co_use_case, color=textline_rgb_color) img_poly = cv2.fillPoly(img, pts=co_use_case, color=textline_rgb_color)
if "artificial_class_label" in keys: if "artificial_class_label" in keys:

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