qurator-spk/eynollah
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Konstantin Baierer 2021-03-01 17:57:03 +01:00
parent 10ae13f9b0
commit adb96b5b49
2 changed files with 15 additions and 15 deletions
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24
qurator/eynollah/utils/contour.py
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@ -126,10 +126,10 @@ def return_contours_of_interested_region(region_pre_p, pixel, min_area=0.0002):
imgray = cv2.cvtColor(cnts_images, cv2.COLOR_BGR2GRAY) imgray = cv2.cvtColor(cnts_images, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(imgray, 0, 255, 0) ret, thresh = cv2.threshold(imgray, 0, 255, 0)
contours_imgs, hiearchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) contours_imgs, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
contours_imgs = return_parent_contours(contours_imgs, hiearchy) contours_imgs = return_parent_contours(contours_imgs, hierarchy)
contours_imgs = filter_contours_area_of_image_tables(thresh, contours_imgs, hiearchy, 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
@ -179,10 +179,10 @@ def return_contours_of_interested_textline(region_pre_p, pixel):
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)
ret, thresh = cv2.threshold(imgray, 0, 255, 0) ret, thresh = cv2.threshold(imgray, 0, 255, 0)
contours_imgs, hiearchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) contours_imgs, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
contours_imgs = return_parent_contours(contours_imgs, hiearchy) contours_imgs = return_parent_contours(contours_imgs, hierarchy)
contours_imgs = filter_contours_area_of_image_tables(thresh, contours_imgs, hiearchy, max_area=1, min_area=0.000000003) contours_imgs = filter_contours_area_of_image_tables(thresh, contours_imgs, hierarchy, max_area=1, min_area=0.000000003)
return contours_imgs return contours_imgs
def return_contours_of_image(image): def return_contours_of_image(image):
@ -209,10 +209,10 @@ def return_contours_of_interested_region_by_min_size(region_pre_p, pixel, min_si
imgray = cv2.cvtColor(cnts_images, cv2.COLOR_BGR2GRAY) imgray = cv2.cvtColor(cnts_images, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(imgray, 0, 255, 0) ret, thresh = cv2.threshold(imgray, 0, 255, 0)
contours_imgs, hiearchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) contours_imgs, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
contours_imgs = return_parent_contours(contours_imgs, hiearchy) contours_imgs = return_parent_contours(contours_imgs, hierarchy)
contours_imgs = filter_contours_area_of_image_tables(thresh, contours_imgs, hiearchy, max_area=1, min_area=min_size) contours_imgs = filter_contours_area_of_image_tables(thresh, contours_imgs, hierarchy, max_area=1, min_area=min_size)
return contours_imgs return contours_imgs
@ -227,10 +227,10 @@ def return_contours_of_interested_region_by_size(region_pre_p, pixel, min_area,
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)
ret, thresh = cv2.threshold(imgray, 0, 255, 0) ret, thresh = cv2.threshold(imgray, 0, 255, 0)
contours_imgs, hiearchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) contours_imgs, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
contours_imgs = return_parent_contours(contours_imgs, hiearchy) contours_imgs = return_parent_contours(contours_imgs, hierarchy)
contours_imgs = filter_contours_area_of_image_tables(thresh, contours_imgs, hiearchy, max_area=max_area, min_area=min_area) contours_imgs = filter_contours_area_of_image_tables(thresh, contours_imgs, hierarchy, max_area=max_area, min_area=min_area)
img_ret = np.zeros((region_pre_p.shape[0], region_pre_p.shape[1], 3)) img_ret = np.zeros((region_pre_p.shape[0], region_pre_p.shape[1], 3))
img_ret = cv2.fillPoly(img_ret, pts=contours_imgs, color=(1, 1, 1)) img_ret = cv2.fillPoly(img_ret, pts=contours_imgs, color=(1, 1, 1))

6
qurator/eynollah/utils/separate_lines.py
View file

@ -1340,10 +1340,10 @@ def separate_lines_vertical_cont(img_patch, contour_text_interest, thetha, box_i
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)
ret, thresh = cv2.threshold(imgray, 0, 255, 0) ret, thresh = cv2.threshold(imgray, 0, 255, 0)
contours_imgs, hiearchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) contours_imgs, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
contours_imgs = return_parent_contours(contours_imgs, hiearchy) contours_imgs = return_parent_contours(contours_imgs, hierarchy)
contours_imgs = filter_contours_area_of_image_tables(thresh, contours_imgs, hiearchy, max_area=max_area, min_area=min_area) contours_imgs = filter_contours_area_of_image_tables(thresh, contours_imgs, hierarchy, max_area=max_area, min_area=min_area)
cont_final = [] cont_final = []
###print(add_boxes_coor_into_textlines,'ikki') ###print(add_boxes_coor_into_textlines,'ikki')