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@ -8,6 +8,7 @@ from tqdm import tqdm
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import cv2
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from shapely import geometry
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from pathlib import Path
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import matplotlib.pyplot as plt
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KERNEL = np.ones((5, 5), np.uint8)
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@ -84,8 +85,12 @@ def return_contours_of_interested_region(region_pre_p, pixel, min_area=0.0002):
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contours_imgs, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
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#print(len(contours_imgs), hierarchy)
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contours_imgs = return_parent_contours(contours_imgs, hierarchy)
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contours_imgs = filter_contours_area_of_image_tables(thresh, contours_imgs, hierarchy, max_area=1, min_area=min_area)
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#print(len(contours_imgs), "iki")
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#contours_imgs = filter_contours_area_of_image_tables(thresh, contours_imgs, hierarchy, max_area=1, min_area=min_area)
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return contours_imgs
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def update_region_contours(co_text, img_boundary, erosion_rate, dilation_rate, y_len, x_len, dilation_early=None):
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@ -103,12 +108,15 @@ def update_region_contours(co_text, img_boundary, erosion_rate, dilation_rate, y
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pixel = 1
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min_size = 0
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img_boundary_in = img_boundary_in.astype("uint8")
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con_eroded = return_contours_of_interested_region(img_boundary_in,pixel, min_size )
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try:
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co_text_eroded.append(con_eroded[0])
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except:
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co_text_eroded.append(con)
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#try:
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co_text_eroded.append(con_eroded[0])
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#except:
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#co_text_eroded.append(con)
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img_boundary_in_dilated = cv2.dilate(img_boundary_in[:,:], KERNEL, iterations=dilation_rate)
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@ -262,8 +270,8 @@ def get_images_of_ground_truth(gt_list, dir_in, output_dir, output_type, config_
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if "artificial_class_label" in keys:
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img_boundary = np.zeros((y_len, x_len))
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erosion_rate = 0#1
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dilation_rate = 3
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dilation_early = 2
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dilation_rate = 2
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dilation_early = 1
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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 )
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