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eynollah
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re-enable changes from c606391c31

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refactor_with_disable-dir-in
Clemens Neudecker 2 months ago
parent 22fed4fc22
commit 6020554555
1 changed files with 112 additions and 112 deletions
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eynollah/eynollah/utils/contour.py
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@ -154,95 +154,95 @@ def return_contours_of_interested_region(region_pre_p, pixel, min_area=0.0002):
return contours_imgs
# def do_work_of_contours_in_image(queue_of_all_params, contours_per_process, indexes_r_con_per_pro, img, slope_first):
# cnts_org_per_each_subprocess = []
# index_by_text_region_contours = []
# for mv in range(len(contours_per_process)):
# index_by_text_region_contours.append(indexes_r_con_per_pro[mv])
def do_work_of_contours_in_image(queue_of_all_params, contours_per_process, indexes_r_con_per_pro, img, slope_first):
cnts_org_per_each_subprocess = []
index_by_text_region_contours = []
for mv in range(len(contours_per_process)):
index_by_text_region_contours.append(indexes_r_con_per_pro[mv])
# img_copy = np.zeros(img.shape)
# img_copy = cv2.fillPoly(img_copy, pts=[contours_per_process[mv]], color=(1, 1, 1))
img_copy = np.zeros(img.shape)
img_copy = cv2.fillPoly(img_copy, pts=[contours_per_process[mv]], color=(1, 1, 1))
# img_copy = rotation_image_new(img_copy, -slope_first)
img_copy = rotation_image_new(img_copy, -slope_first)
# img_copy = img_copy.astype(np.uint8)
# imgray = cv2.cvtColor(img_copy, cv2.COLOR_BGR2GRAY)
# ret, thresh = cv2.threshold(imgray, 0, 255, 0)
img_copy = img_copy.astype(np.uint8)
imgray = cv2.cvtColor(img_copy, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(imgray, 0, 255, 0)
# cont_int, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cont_int, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# cont_int[0][:, 0, 0] = cont_int[0][:, 0, 0] + np.abs(img_copy.shape[1] - img.shape[1])
# cont_int[0][:, 0, 1] = cont_int[0][:, 0, 1] + np.abs(img_copy.shape[0] - img.shape[0])
cont_int[0][:, 0, 0] = cont_int[0][:, 0, 0] + np.abs(img_copy.shape[1] - img.shape[1])
cont_int[0][:, 0, 1] = cont_int[0][:, 0, 1] + np.abs(img_copy.shape[0] - img.shape[0])
# cnts_org_per_each_subprocess.append(cont_int[0])
cnts_org_per_each_subprocess.append(cont_int[0])
# queue_of_all_params.put([cnts_org_per_each_subprocess, index_by_text_region_contours])
queue_of_all_params.put([cnts_org_per_each_subprocess, index_by_text_region_contours])
# def get_textregion_contours_in_org_image_multi(cnts, img, slope_first):
def get_textregion_contours_in_org_image_multi(cnts, img, slope_first):
# num_cores = cpu_count()
# queue_of_all_params = Queue()
# processes = []
# nh = np.linspace(0, len(cnts), num_cores + 1)
# indexes_by_text_con = np.array(range(len(cnts)))
# for i in range(num_cores):
# contours_per_process = cnts[int(nh[i]): int(nh[i + 1])]
# indexes_text_con_per_process = indexes_by_text_con[int(nh[i]): int(nh[i + 1])]
# processes.append(Process(target=do_work_of_contours_in_image, args=(queue_of_all_params, contours_per_process, indexes_text_con_per_process, img, slope_first)))
# for i in range(num_cores):
# processes[i].start()
# cnts_org = []
# all_index_text_con = []
# for i in range(num_cores):
# list_all_par = queue_of_all_params.get(True)
# contours_for_sub_process = list_all_par[0]
# indexes_for_sub_process = list_all_par[1]
# for j in range(len(contours_for_sub_process)):
# cnts_org.append(contours_for_sub_process[j])
# all_index_text_con.append(indexes_for_sub_process[j])
# for i in range(num_cores):
# processes[i].join()
# print(all_index_text_con)
# return cnts_org
# def loop_contour_image(index_l, cnts, img, slope_first):
# img_copy = np.zeros(img.shape)
# img_copy = cv2.fillPoly(img_copy, pts=[cnts[index_l]], color=(1, 1, 1))
# # plt.imshow(img_copy)
# # plt.show()
# # print(img.shape,'img')
# img_copy = rotation_image_new(img_copy, -slope_first)
# # print(img_copy.shape,'img_copy')
# # plt.imshow(img_copy)
# # plt.show()
# img_copy = img_copy.astype(np.uint8)
# imgray = cv2.cvtColor(img_copy, cv2.COLOR_BGR2GRAY)
# ret, thresh = cv2.threshold(imgray, 0, 255, 0)
# cont_int, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# cont_int[0][:, 0, 0] = cont_int[0][:, 0, 0] + np.abs(img_copy.shape[1] - img.shape[1])
# cont_int[0][:, 0, 1] = cont_int[0][:, 0, 1] + np.abs(img_copy.shape[0] - img.shape[0])
# # print(np.shape(cont_int[0]))
# return cont_int[0]
# def get_textregion_contours_in_org_image_multi2(cnts, img, slope_first):
# cnts_org = []
# # print(cnts,'cnts')
# with Pool(cpu_count()) as p:
# cnts_org = p.starmap(loop_contour_image, [(index_l, cnts, img, slope_first) for index_l in range(len(cnts))])
num_cores = cpu_count()
queue_of_all_params = Queue()
processes = []
nh = np.linspace(0, len(cnts), num_cores + 1)
indexes_by_text_con = np.array(range(len(cnts)))
for i in range(num_cores):
contours_per_process = cnts[int(nh[i]): int(nh[i + 1])]
indexes_text_con_per_process = indexes_by_text_con[int(nh[i]): int(nh[i + 1])]
processes.append(Process(target=do_work_of_contours_in_image, args=(queue_of_all_params, contours_per_process, indexes_text_con_per_process, img, slope_first)))
for i in range(num_cores):
processes[i].start()
cnts_org = []
all_index_text_con = []
for i in range(num_cores):
list_all_par = queue_of_all_params.get(True)
contours_for_sub_process = list_all_par[0]
indexes_for_sub_process = list_all_par[1]
for j in range(len(contours_for_sub_process)):
cnts_org.append(contours_for_sub_process[j])
all_index_text_con.append(indexes_for_sub_process[j])
for i in range(num_cores):
processes[i].join()
print(all_index_text_con)
return cnts_org
def loop_contour_image(index_l, cnts, img, slope_first):
img_copy = np.zeros(img.shape)
img_copy = cv2.fillPoly(img_copy, pts=[cnts[index_l]], color=(1, 1, 1))
# plt.imshow(img_copy)
# plt.show()
# print(img.shape,'img')
img_copy = rotation_image_new(img_copy, -slope_first)
# print(img_copy.shape,'img_copy')
# plt.imshow(img_copy)
# plt.show()
img_copy = img_copy.astype(np.uint8)
imgray = cv2.cvtColor(img_copy, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(imgray, 0, 255, 0)
cont_int, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cont_int[0][:, 0, 0] = cont_int[0][:, 0, 0] + np.abs(img_copy.shape[1] - img.shape[1])
cont_int[0][:, 0, 1] = cont_int[0][:, 0, 1] + np.abs(img_copy.shape[0] - img.shape[0])
# print(np.shape(cont_int[0]))
return cont_int[0]
def get_textregion_contours_in_org_image_multi2(cnts, img, slope_first):
cnts_org = []
# print(cnts,'cnts')
with Pool(cpu_count()) as p:
cnts_org = p.starmap(loop_contour_image, [(index_l, cnts, img, slope_first) for index_l in range(len(cnts))])
# return cnts_org
return cnts_org
def get_textregion_contours_in_org_image(cnts, img, slope_first):
@ -276,42 +276,42 @@ def get_textregion_contours_in_org_image(cnts, img, slope_first):
return cnts_org
# def get_textregion_contours_in_org_image_light(cnts, img, slope_first):
def get_textregion_contours_in_org_image_light(cnts, img, slope_first):
# h_o = img.shape[0]
# w_o = img.shape[1]
h_o = img.shape[0]
w_o = img.shape[1]
# img = cv2.resize(img, (int(img.shape[1]/3.), int(img.shape[0]/3.)), interpolation=cv2.INTER_NEAREST)
# # cnts = list( (np.array(cnts)/2).astype(np.int16) )
# # cnts = cnts/2
# cnts = [(i / 3).astype(np.int32) for i in cnts]
# cnts_org = []
# # print(cnts,'cnts')
# for i in range(len(cnts)):
# img_copy = np.zeros(img.shape)
# img_copy = cv2.fillPoly(img_copy, pts=[cnts[i]], color=(1, 1, 1))
# # plt.imshow(img_copy)
# # plt.show()
# # print(img.shape,'img')
# img_copy = rotation_image_new(img_copy, -slope_first)
# # print(img_copy.shape,'img_copy')
# # plt.imshow(img_copy)
# # plt.show()
# img_copy = img_copy.astype(np.uint8)
# imgray = cv2.cvtColor(img_copy, cv2.COLOR_BGR2GRAY)
# ret, thresh = cv2.threshold(imgray, 0, 255, 0)
# cont_int, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# cont_int[0][:, 0, 0] = cont_int[0][:, 0, 0] + np.abs(img_copy.shape[1] - img.shape[1])
# cont_int[0][:, 0, 1] = cont_int[0][:, 0, 1] + np.abs(img_copy.shape[0] - img.shape[0])
# # print(np.shape(cont_int[0]))
# cnts_org.append(cont_int[0]*3)
# return cnts_org
img = cv2.resize(img, (int(img.shape[1]/3.), int(img.shape[0]/3.)), interpolation=cv2.INTER_NEAREST)
# cnts = list( (np.array(cnts)/2).astype(np.int16) )
# cnts = cnts/2
cnts = [(i / 3).astype(np.int32) for i in cnts]
cnts_org = []
# print(cnts,'cnts')
for i in range(len(cnts)):
img_copy = np.zeros(img.shape)
img_copy = cv2.fillPoly(img_copy, pts=[cnts[i]], color=(1, 1, 1))
# plt.imshow(img_copy)
# plt.show()
# print(img.shape,'img')
img_copy = rotation_image_new(img_copy, -slope_first)
# print(img_copy.shape,'img_copy')
# plt.imshow(img_copy)
# plt.show()
img_copy = img_copy.astype(np.uint8)
imgray = cv2.cvtColor(img_copy, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(imgray, 0, 255, 0)
cont_int, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cont_int[0][:, 0, 0] = cont_int[0][:, 0, 0] + np.abs(img_copy.shape[1] - img.shape[1])
cont_int[0][:, 0, 1] = cont_int[0][:, 0, 1] + np.abs(img_copy.shape[0] - img.shape[0])
# print(np.shape(cont_int[0]))
cnts_org.append(cont_int[0]*3)
return cnts_org
def return_contours_of_interested_textline(region_pre_p, pixel):

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