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eynollah
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resolving issue https://github.com/qurator-spk/eynollah/issues/38

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pull/63/head
vahid 4 years ago
parent 7cbecadccc
commit c4b2c71e68
2 changed files with 93 additions and 80 deletions
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145
qurator/eynollah/eynollah.py
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@ -1869,89 +1869,98 @@ class Eynollah:
if np.abs(slope_deskew) >= SLOPE_THRESHOLD:
contours_only_text, hir_on_text = return_contours_of_image(text_only)
contours_only_text_parent = return_parent_contours(contours_only_text, hir_on_text)
areas_cnt_text = np.array([cv2.contourArea(contours_only_text_parent[j]) for j in range(len(contours_only_text_parent))])
areas_cnt_text = areas_cnt_text / float(text_only.shape[0] * text_only.shape[1])
self.logger.info('areas_cnt_text %s', areas_cnt_text)
contours_biggest = contours_only_text_parent[np.argmax(areas_cnt_text)]
contours_only_text_parent = [contours_only_text_parent[jz] for jz in range(len(contours_only_text_parent)) if areas_cnt_text[jz] > min_con_area]
areas_cnt_text_parent = [areas_cnt_text[jz] for jz in range(len(areas_cnt_text)) if areas_cnt_text[jz] > min_con_area]
index_con_parents = np.argsort(areas_cnt_text_parent)
contours_only_text_parent = list(np.array(contours_only_text_parent)[index_con_parents])
areas_cnt_text_parent = list(np.array(areas_cnt_text_parent)[index_con_parents])
if len(contours_only_text_parent) > 0:
areas_cnt_text = np.array([cv2.contourArea(contours_only_text_parent[j]) for j in range(len(contours_only_text_parent))])
areas_cnt_text = areas_cnt_text / float(text_only.shape[0] * text_only.shape[1])
self.logger.info('areas_cnt_text %s', areas_cnt_text)
contours_biggest = contours_only_text_parent[np.argmax(areas_cnt_text)]
contours_only_text_parent = [contours_only_text_parent[jz] for jz in range(len(contours_only_text_parent)) if areas_cnt_text[jz] > min_con_area]
areas_cnt_text_parent = [areas_cnt_text[jz] for jz in range(len(areas_cnt_text)) if areas_cnt_text[jz] > min_con_area]
cx_bigest_big, cy_biggest_big, _, _, _, _, _ = find_new_features_of_contours([contours_biggest])
cx_bigest, cy_biggest, _, _, _, _, _ = find_new_features_of_contours(contours_only_text_parent)
index_con_parents = np.argsort(areas_cnt_text_parent)
contours_only_text_parent = list(np.array(contours_only_text_parent)[index_con_parents])
areas_cnt_text_parent = list(np.array(areas_cnt_text_parent)[index_con_parents])
contours_only_text_d, hir_on_text_d = return_contours_of_image(text_only_d)
contours_only_text_parent_d = return_parent_contours(contours_only_text_d, hir_on_text_d)
cx_bigest_big, cy_biggest_big, _, _, _, _, _ = find_new_features_of_contours([contours_biggest])
cx_bigest, cy_biggest, _, _, _, _, _ = find_new_features_of_contours(contours_only_text_parent)
areas_cnt_text_d = np.array([cv2.contourArea(contours_only_text_parent_d[j]) for j in range(len(contours_only_text_parent_d))])
areas_cnt_text_d = areas_cnt_text_d / float(text_only_d.shape[0] * text_only_d.shape[1])
contours_only_text_d, hir_on_text_d = return_contours_of_image(text_only_d)
contours_only_text_parent_d = return_parent_contours(contours_only_text_d, hir_on_text_d)
contours_biggest_d = contours_only_text_parent_d[np.argmax(areas_cnt_text_d)]
index_con_parents_d=np.argsort(areas_cnt_text_d)
contours_only_text_parent_d=list(np.array(contours_only_text_parent_d)[index_con_parents_d] )
areas_cnt_text_d=list(np.array(areas_cnt_text_d)[index_con_parents_d] )
areas_cnt_text_d = np.array([cv2.contourArea(contours_only_text_parent_d[j]) for j in range(len(contours_only_text_parent_d))])
areas_cnt_text_d = areas_cnt_text_d / float(text_only_d.shape[0] * text_only_d.shape[1])
cx_bigest_d_big, cy_biggest_d_big, _, _, _, _, _ = find_new_features_of_contours([contours_biggest_d])
cx_bigest_d, cy_biggest_d, _, _, _, _, _ = find_new_features_of_contours(contours_only_text_parent_d)
try:
if len(cx_bigest_d) >= 5:
cx_bigest_d_last5 = cx_bigest_d[-5:]
cy_biggest_d_last5 = cy_biggest_d[-5:]
dists_d = [math.sqrt((cx_bigest_big[0] - cx_bigest_d_last5[j]) ** 2 + (cy_biggest_big[0] - cy_biggest_d_last5[j]) ** 2) for j in range(len(cy_biggest_d_last5))]
ind_largest = len(cx_bigest_d) -5 + np.argmin(dists_d)
else:
cx_bigest_d_last5 = cx_bigest_d[-len(cx_bigest_d):]
cy_biggest_d_last5 = cy_biggest_d[-len(cx_bigest_d):]
dists_d = [math.sqrt((cx_bigest_big[0]-cx_bigest_d_last5[j])**2 + (cy_biggest_big[0]-cy_biggest_d_last5[j])**2) for j in range(len(cy_biggest_d_last5))]
ind_largest = len(cx_bigest_d) - len(cx_bigest_d) + np.argmin(dists_d)
contours_biggest_d = contours_only_text_parent_d[np.argmax(areas_cnt_text_d)]
index_con_parents_d=np.argsort(areas_cnt_text_d)
contours_only_text_parent_d=list(np.array(contours_only_text_parent_d)[index_con_parents_d] )
areas_cnt_text_d=list(np.array(areas_cnt_text_d)[index_con_parents_d] )
cx_bigest_d_big[0] = cx_bigest_d[ind_largest]
cy_biggest_d_big[0] = cy_biggest_d[ind_largest]
except Exception as why:
self.logger.error(why)
cx_bigest_d_big, cy_biggest_d_big, _, _, _, _, _ = find_new_features_of_contours([contours_biggest_d])
cx_bigest_d, cy_biggest_d, _, _, _, _, _ = find_new_features_of_contours(contours_only_text_parent_d)
try:
if len(cx_bigest_d) >= 5:
cx_bigest_d_last5 = cx_bigest_d[-5:]
cy_biggest_d_last5 = cy_biggest_d[-5:]
dists_d = [math.sqrt((cx_bigest_big[0] - cx_bigest_d_last5[j]) ** 2 + (cy_biggest_big[0] - cy_biggest_d_last5[j]) ** 2) for j in range(len(cy_biggest_d_last5))]
ind_largest = len(cx_bigest_d) -5 + np.argmin(dists_d)
else:
cx_bigest_d_last5 = cx_bigest_d[-len(cx_bigest_d):]
cy_biggest_d_last5 = cy_biggest_d[-len(cx_bigest_d):]
dists_d = [math.sqrt((cx_bigest_big[0]-cx_bigest_d_last5[j])**2 + (cy_biggest_big[0]-cy_biggest_d_last5[j])**2) for j in range(len(cy_biggest_d_last5))]
ind_largest = len(cx_bigest_d) - len(cx_bigest_d) + np.argmin(dists_d)
cx_bigest_d_big[0] = cx_bigest_d[ind_largest]
cy_biggest_d_big[0] = cy_biggest_d[ind_largest]
except Exception as why:
self.logger.error(why)
(h, w) = text_only.shape[:2]
center = (w // 2.0, h // 2.0)
M = cv2.getRotationMatrix2D(center, slope_deskew, 1.0)
M_22 = np.array(M)[:2, :2]
p_big = np.dot(M_22, [cx_bigest_big, cy_biggest_big])
x_diff = p_big[0] - cx_bigest_d_big
y_diff = p_big[1] - cy_biggest_d_big
contours_only_text_parent_d_ordered = []
for i in range(len(contours_only_text_parent)):
p = np.dot(M_22, [cx_bigest[i], cy_biggest[i]])
p[0] = p[0] - x_diff[0]
p[1] = p[1] - y_diff[0]
dists = [math.sqrt((p[0] - cx_bigest_d[j]) ** 2 + (p[1] - cy_biggest_d[j]) ** 2) for j in range(len(cx_bigest_d))]
contours_only_text_parent_d_ordered.append(contours_only_text_parent_d[np.argmin(dists)])
# img2=np.zeros((text_only.shape[0],text_only.shape[1],3))
# img2=cv2.fillPoly(img2,pts=[contours_only_text_parent_d[np.argmin(dists)]] ,color=(1,1,1))
# plt.imshow(img2[:,:,0])
# plt.show()
else:
contours_only_text_parent_d_ordered = []
contours_only_text_parent_d = []
(h, w) = text_only.shape[:2]
center = (w // 2.0, h // 2.0)
M = cv2.getRotationMatrix2D(center, slope_deskew, 1.0)
M_22 = np.array(M)[:2, :2]
p_big = np.dot(M_22, [cx_bigest_big, cy_biggest_big])
x_diff = p_big[0] - cx_bigest_d_big
y_diff = p_big[1] - cy_biggest_d_big
contours_only_text_parent_d_ordered = []
for i in range(len(contours_only_text_parent)):
p = np.dot(M_22, [cx_bigest[i], cy_biggest[i]])
p[0] = p[0] - x_diff[0]
p[1] = p[1] - y_diff[0]
dists = [math.sqrt((p[0] - cx_bigest_d[j]) ** 2 + (p[1] - cy_biggest_d[j]) ** 2) for j in range(len(cx_bigest_d))]
contours_only_text_parent_d_ordered.append(contours_only_text_parent_d[np.argmin(dists)])
# img2=np.zeros((text_only.shape[0],text_only.shape[1],3))
# img2=cv2.fillPoly(img2,pts=[contours_only_text_parent_d[np.argmin(dists)]] ,color=(1,1,1))
# plt.imshow(img2[:,:,0])
# plt.show()
else:
contours_only_text, hir_on_text = return_contours_of_image(text_only)
contours_only_text_parent = return_parent_contours(contours_only_text, hir_on_text)
areas_cnt_text = np.array([cv2.contourArea(contours_only_text_parent[j]) for j in range(len(contours_only_text_parent))])
areas_cnt_text = areas_cnt_text / float(text_only.shape[0] * text_only.shape[1])
if len(contours_only_text_parent) > 0:
areas_cnt_text = np.array([cv2.contourArea(contours_only_text_parent[j]) for j in range(len(contours_only_text_parent))])
areas_cnt_text = areas_cnt_text / float(text_only.shape[0] * text_only.shape[1])
contours_biggest = contours_only_text_parent[np.argmax(areas_cnt_text)]
contours_only_text_parent = [contours_only_text_parent[jz] for jz in range(len(contours_only_text_parent)) if areas_cnt_text[jz] > min_con_area]
areas_cnt_text_parent = [areas_cnt_text[jz] for jz in range(len(areas_cnt_text)) if areas_cnt_text[jz] > min_con_area]
contours_biggest = contours_only_text_parent[np.argmax(areas_cnt_text)]
contours_only_text_parent = [contours_only_text_parent[jz] for jz in range(len(contours_only_text_parent)) if areas_cnt_text[jz] > min_con_area]
areas_cnt_text_parent = [areas_cnt_text[jz] for jz in range(len(areas_cnt_text)) if areas_cnt_text[jz] > min_con_area]
index_con_parents = np.argsort(areas_cnt_text_parent)
contours_only_text_parent = list(np.array(contours_only_text_parent)[index_con_parents])
areas_cnt_text_parent = list(np.array(areas_cnt_text_parent)[index_con_parents])
index_con_parents = np.argsort(areas_cnt_text_parent)
contours_only_text_parent = list(np.array(contours_only_text_parent)[index_con_parents])
areas_cnt_text_parent = list(np.array(areas_cnt_text_parent)[index_con_parents])
cx_bigest_big, cy_biggest_big, _, _, _, _, _ = find_new_features_of_contours([contours_biggest])
cx_bigest, cy_biggest, _, _, _, _, _ = find_new_features_of_contours(contours_only_text_parent)
self.logger.debug('areas_cnt_text_parent %s', areas_cnt_text_parent)
# self.logger.debug('areas_cnt_text_parent_d %s', areas_cnt_text_parent_d)
# self.logger.debug('len(contours_only_text_parent) %s', len(contours_only_text_parent_d))
cx_bigest_big, cy_biggest_big, _, _, _, _, _ = find_new_features_of_contours([contours_biggest])
cx_bigest, cy_biggest, _, _, _, _, _ = find_new_features_of_contours(contours_only_text_parent)
self.logger.debug('areas_cnt_text_parent %s', areas_cnt_text_parent)
# self.logger.debug('areas_cnt_text_parent_d %s', areas_cnt_text_parent_d)
# self.logger.debug('len(contours_only_text_parent) %s', len(contours_only_text_parent_d))
else:
pass
txt_con_org = get_textregion_contours_in_org_image(contours_only_text_parent, self.image, slope_first)
boxes_text, _ = get_text_region_boxes_by_given_contours(contours_only_text_parent)
boxes_marginals, _ = get_text_region_boxes_by_given_contours(polygons_of_marginals)

6
qurator/eynollah/utils/__init__.py
Unescape Escape View File

@ -1560,7 +1560,11 @@ def find_number_of_columns_in_document(region_pre_p, num_col_classifier, pixel_l
#regions_without_separators_tile=cv2.erode(regions_without_separators_tile,kernel,iterations = 3)
#
num_col, peaks_neg_fin=find_num_col(regions_without_separators_tile,multiplier=7.0)
try:
num_col, peaks_neg_fin = find_num_col(regions_without_separators_tile,multiplier=7.0)
except:
num_col = 0
peaks_neg_fin = []
if num_col>num_col_fin:
num_col_fin=num_col

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