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remove unused return_contours_of_interested_region_and_bounding_box

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Konstantin Baierer 2021-02-23 16:37:13 +01:00
parent 732a27fe77
commit 9454a921b1
3 changed files with 21 additions and 21 deletions
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1
sbb_newspapers_org_image/eynollah.py
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@ -40,7 +40,6 @@ from .utils.contour import (
return_bonding_box_of_contours, return_bonding_box_of_contours,
return_contours_of_image, return_contours_of_image,
return_contours_of_interested_region, return_contours_of_interested_region,
return_contours_of_interested_region_and_bounding_box,
return_contours_of_interested_region_by_min_size, return_contours_of_interested_region_by_min_size,
return_contours_of_interested_textline, return_contours_of_interested_textline,
return_parent_contours, return_parent_contours,

21
sbb_newspapers_org_image/unused.py
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@ -3027,3 +3027,24 @@ def seperate_lines_new(img_path, thetha, num_col, dir_of_all, f_name):
##plt.imshow(img_patch_ineterst_revised) ##plt.imshow(img_patch_ineterst_revised)
##plt.show() ##plt.show()
return img_patch_ineterst_revised return img_patch_ineterst_revised
def return_contours_of_interested_region_and_bounding_box(region_pre_p, pixel):
# pixels of images are identified by 5
cnts_images = (region_pre_p[:, :, 0] == pixel) * 1
cnts_images = cnts_images.astype(np.uint8)
cnts_images = np.repeat(cnts_images[:, :, np.newaxis], 3, axis=2)
imgray = cv2.cvtColor(cnts_images, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(imgray, 0, 255, 0)
contours_imgs, hiearchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
contours_imgs = return_parent_contours(contours_imgs, hiearchy)
contours_imgs = filter_contours_area_of_image_tables(thresh, contours_imgs, hiearchy, max_area=1, min_area=0.0003)
boxes = []
for jj in range(len(contours_imgs)):
x, y, w, h = cv2.boundingRect(contours_imgs[jj])
boxes.append([int(x), int(y), int(w), int(h)])
return contours_imgs, boxes

20
sbb_newspapers_org_image/utils/contour.py
View file

@ -40,26 +40,6 @@ def find_features_of_contours(contours_main):
return y_min_main, y_max_main, areas_main return y_min_main, y_max_main, areas_main
def return_contours_of_interested_region_and_bounding_box(region_pre_p, pixel):
# pixels of images are identified by 5
cnts_images = (region_pre_p[:, :, 0] == pixel) * 1
cnts_images = cnts_images.astype(np.uint8)
cnts_images = np.repeat(cnts_images[:, :, np.newaxis], 3, axis=2)
imgray = cv2.cvtColor(cnts_images, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(imgray, 0, 255, 0)
contours_imgs, hiearchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
contours_imgs = return_parent_contours(contours_imgs, hiearchy)
contours_imgs = filter_contours_area_of_image_tables(thresh, contours_imgs, hiearchy, max_area=1, min_area=0.0003)
boxes = []
for jj in range(len(contours_imgs)):
x, y, w, h = cv2.boundingRect(contours_imgs[jj])
boxes.append([int(x), int(y), int(w), int(h)])
return contours_imgs, boxes
def get_text_region_boxes_by_given_contours(contours): def get_text_region_boxes_by_given_contours(contours):
kernel = np.ones((5, 5), np.uint8) kernel = np.ones((5, 5), np.uint8)