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eynollah
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simplify

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pull/142/head
Robert Sachunsky 2 weeks ago
parent 54cb15056b
commit 5e0c1da711
1 changed files with 29 additions and 58 deletions
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src/eynollah/eynollah.py
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@ -823,8 +823,8 @@ class Eynollah:
def do_prediction(self, patches, img, model, n_batch_inference=1, marginal_of_patch_percent=0.1, thresholding_for_some_classes_in_light_version=False, thresholding_for_artificial_class_in_light_version=False):
self.logger.debug("enter do_prediction")
img_height_model = model.layers[len(model.layers) - 1].output_shape[1]
img_width_model = model.layers[len(model.layers) - 1].output_shape[2]
img_height_model = model.layers[-1].output_shape[1]
img_width_model = model.layers[-1].output_shape[2]
if not patches:
img_h_page = img.shape[0]
@ -1034,8 +1034,8 @@ class Eynollah:
def do_prediction_new_concept(self, patches, img, model, n_batch_inference=1, marginal_of_patch_percent=0.1, thresholding_for_some_classes_in_light_version=False, thresholding_for_artificial_class_in_light_version=False):
self.logger.debug("enter do_prediction_new_concept")
img_height_model = model.layers[len(model.layers) - 1].output_shape[1]
img_width_model = model.layers[len(model.layers) - 1].output_shape[2]
img_height_model = model.layers[-1].output_shape[1]
img_width_model = model.layers[-1].output_shape[2]
if not patches:
img_h_page = img.shape[0]
@ -1043,7 +1043,7 @@ class Eynollah:
img = img / 255.0
img = resize_image(img, img_height_model, img_width_model)
label_p_pred = model.predict(img.reshape(1, img.shape[0], img.shape[1], img.shape[2]), verbose=0)
label_p_pred = model.predict(img[np.newaxis], verbose=0)
seg = np.argmax(label_p_pred, axis=3)[0]
if thresholding_for_artificial_class_in_light_version:
@ -4928,31 +4928,31 @@ class Eynollah:
#print("text region early 2 in %.1fs", time.time() - t0)
###min_con_area = 0.000005
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)
if len(contours_only_text_parent) > 0:
areas_cnt_text = np.array([cv2.contourArea(c) for c in 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 = [c for jz, c in enumerate(contours_only_text_parent) if areas_cnt_text[jz] > MIN_AREA_REGION]
areas_cnt_text_parent = [area for area in areas_cnt_text if area > MIN_AREA_REGION]
index_con_parents = np.argsort(areas_cnt_text_parent)
contours_only_text_parent = self.return_list_of_contours_with_desired_order(contours_only_text_parent, index_con_parents)
##try:
##contours_only_text_parent = list(np.array(contours_only_text_parent,dtype=object)[index_con_parents])
##except:
##contours_only_text_parent = list(np.array(contours_only_text_parent,dtype=np.int32)[index_con_parents])
##areas_cnt_text_parent = list(np.array(areas_cnt_text_parent)[index_con_parents])
areas_cnt_text_parent = self.return_list_of_contours_with_desired_order(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)
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)
if len(contours_only_text_parent) > 0:
areas_cnt_text = np.array([cv2.contourArea(c) for c in 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 = [c for jz, c in enumerate(contours_only_text_parent) if areas_cnt_text[jz] > MIN_AREA_REGION]
areas_cnt_text_parent = [area for area in areas_cnt_text if area > MIN_AREA_REGION]
index_con_parents = np.argsort(areas_cnt_text_parent)
contours_only_text_parent = self.return_list_of_contours_with_desired_order(contours_only_text_parent, index_con_parents)
##try:
##contours_only_text_parent = list(np.array(contours_only_text_parent,dtype=object)[index_con_parents])
##except:
##contours_only_text_parent = list(np.array(contours_only_text_parent,dtype=np.int32)[index_con_parents])
##areas_cnt_text_parent = list(np.array(areas_cnt_text_parent)[index_con_parents])
areas_cnt_text_parent = self.return_list_of_contours_with_desired_order(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)
if np.abs(slope_deskew) >= SLOPE_THRESHOLD:
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)
@ -5018,35 +5018,6 @@ class Eynollah:
contours_only_text_parent_d_ordered = []
contours_only_text_parent_d = []
contours_only_text_parent = []
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)
if len(contours_only_text_parent) > 0:
areas_cnt_text = np.array([cv2.contourArea(c) for c in 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 = [c for jz, c in enumerate(contours_only_text_parent) if areas_cnt_text[jz] > MIN_AREA_REGION]
areas_cnt_text_parent = [area for area in areas_cnt_text if area > MIN_AREA_REGION]
index_con_parents = np.argsort(areas_cnt_text_parent)
contours_only_text_parent = self.return_list_of_contours_with_desired_order(contours_only_text_parent, index_con_parents)
#try:
#contours_only_text_parent = list(np.array(contours_only_text_parent,dtype=object)[index_con_parents])
#except:
#contours_only_text_parent = list(np.array(contours_only_text_parent,dtype=np.int32)[index_con_parents])
#areas_cnt_text_parent = list(np.array(areas_cnt_text_parent)[index_con_parents])
areas_cnt_text_parent = self.return_list_of_contours_with_desired_order(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))
else:
pass
#print("text region early 3 in %.1fs", time.time() - t0)
if self.light_version:

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