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https://github.com/qurator-spk/eynollah.git
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re-enable changes from c606391c31
This commit is contained in:
Clemens Neudecker
parent
22fed4fc22
commit
6020554555
1 changed files with 93 additions and 93 deletions
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@ -154,95 +154,95 @@ def return_contours_of_interested_region(region_pre_p, pixel, min_area=0.0002):
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return contours_imgs
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# def do_work_of_contours_in_image(queue_of_all_params, contours_per_process, indexes_r_con_per_pro, img, slope_first):
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# cnts_org_per_each_subprocess = []
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# index_by_text_region_contours = []
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# for mv in range(len(contours_per_process)):
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# index_by_text_region_contours.append(indexes_r_con_per_pro[mv])
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def do_work_of_contours_in_image(queue_of_all_params, contours_per_process, indexes_r_con_per_pro, img, slope_first):
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cnts_org_per_each_subprocess = []
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index_by_text_region_contours = []
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for mv in range(len(contours_per_process)):
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index_by_text_region_contours.append(indexes_r_con_per_pro[mv])
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# img_copy = np.zeros(img.shape)
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# img_copy = cv2.fillPoly(img_copy, pts=[contours_per_process[mv]], color=(1, 1, 1))
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img_copy = np.zeros(img.shape)
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img_copy = cv2.fillPoly(img_copy, pts=[contours_per_process[mv]], color=(1, 1, 1))
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# img_copy = rotation_image_new(img_copy, -slope_first)
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img_copy = rotation_image_new(img_copy, -slope_first)
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# img_copy = img_copy.astype(np.uint8)
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# imgray = cv2.cvtColor(img_copy, cv2.COLOR_BGR2GRAY)
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# ret, thresh = cv2.threshold(imgray, 0, 255, 0)
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img_copy = img_copy.astype(np.uint8)
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imgray = cv2.cvtColor(img_copy, cv2.COLOR_BGR2GRAY)
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ret, thresh = cv2.threshold(imgray, 0, 255, 0)
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# cont_int, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
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cont_int, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
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# cont_int[0][:, 0, 0] = cont_int[0][:, 0, 0] + np.abs(img_copy.shape[1] - img.shape[1])
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# cont_int[0][:, 0, 1] = cont_int[0][:, 0, 1] + np.abs(img_copy.shape[0] - img.shape[0])
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cont_int[0][:, 0, 0] = cont_int[0][:, 0, 0] + np.abs(img_copy.shape[1] - img.shape[1])
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cont_int[0][:, 0, 1] = cont_int[0][:, 0, 1] + np.abs(img_copy.shape[0] - img.shape[0])
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# cnts_org_per_each_subprocess.append(cont_int[0])
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cnts_org_per_each_subprocess.append(cont_int[0])
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# queue_of_all_params.put([cnts_org_per_each_subprocess, index_by_text_region_contours])
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queue_of_all_params.put([cnts_org_per_each_subprocess, index_by_text_region_contours])
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# def get_textregion_contours_in_org_image_multi(cnts, img, slope_first):
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def get_textregion_contours_in_org_image_multi(cnts, img, slope_first):
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# num_cores = cpu_count()
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# queue_of_all_params = Queue()
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num_cores = cpu_count()
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queue_of_all_params = Queue()
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# processes = []
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# nh = np.linspace(0, len(cnts), num_cores + 1)
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# indexes_by_text_con = np.array(range(len(cnts)))
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# for i in range(num_cores):
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# contours_per_process = cnts[int(nh[i]): int(nh[i + 1])]
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# indexes_text_con_per_process = indexes_by_text_con[int(nh[i]): int(nh[i + 1])]
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processes = []
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nh = np.linspace(0, len(cnts), num_cores + 1)
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indexes_by_text_con = np.array(range(len(cnts)))
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for i in range(num_cores):
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contours_per_process = cnts[int(nh[i]): int(nh[i + 1])]
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indexes_text_con_per_process = indexes_by_text_con[int(nh[i]): int(nh[i + 1])]
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# 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)))
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# for i in range(num_cores):
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# processes[i].start()
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# cnts_org = []
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# all_index_text_con = []
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# for i in range(num_cores):
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# list_all_par = queue_of_all_params.get(True)
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# contours_for_sub_process = list_all_par[0]
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# indexes_for_sub_process = list_all_par[1]
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# for j in range(len(contours_for_sub_process)):
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# cnts_org.append(contours_for_sub_process[j])
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# all_index_text_con.append(indexes_for_sub_process[j])
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# for i in range(num_cores):
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# processes[i].join()
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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)))
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for i in range(num_cores):
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processes[i].start()
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cnts_org = []
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all_index_text_con = []
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for i in range(num_cores):
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list_all_par = queue_of_all_params.get(True)
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contours_for_sub_process = list_all_par[0]
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indexes_for_sub_process = list_all_par[1]
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for j in range(len(contours_for_sub_process)):
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cnts_org.append(contours_for_sub_process[j])
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all_index_text_con.append(indexes_for_sub_process[j])
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for i in range(num_cores):
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processes[i].join()
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# print(all_index_text_con)
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# return cnts_org
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print(all_index_text_con)
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return cnts_org
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# def loop_contour_image(index_l, cnts, img, slope_first):
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# img_copy = np.zeros(img.shape)
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# img_copy = cv2.fillPoly(img_copy, pts=[cnts[index_l]], color=(1, 1, 1))
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def loop_contour_image(index_l, cnts, img, slope_first):
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img_copy = np.zeros(img.shape)
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img_copy = cv2.fillPoly(img_copy, pts=[cnts[index_l]], color=(1, 1, 1))
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# # plt.imshow(img_copy)
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# # plt.show()
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# plt.imshow(img_copy)
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# plt.show()
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# # print(img.shape,'img')
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# img_copy = rotation_image_new(img_copy, -slope_first)
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# # print(img_copy.shape,'img_copy')
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# # plt.imshow(img_copy)
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# # plt.show()
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# print(img.shape,'img')
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img_copy = rotation_image_new(img_copy, -slope_first)
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# print(img_copy.shape,'img_copy')
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# plt.imshow(img_copy)
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# plt.show()
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# img_copy = img_copy.astype(np.uint8)
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# imgray = cv2.cvtColor(img_copy, cv2.COLOR_BGR2GRAY)
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# ret, thresh = cv2.threshold(imgray, 0, 255, 0)
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img_copy = img_copy.astype(np.uint8)
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imgray = cv2.cvtColor(img_copy, cv2.COLOR_BGR2GRAY)
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ret, thresh = cv2.threshold(imgray, 0, 255, 0)
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# cont_int, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
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cont_int, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
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# cont_int[0][:, 0, 0] = cont_int[0][:, 0, 0] + np.abs(img_copy.shape[1] - img.shape[1])
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# cont_int[0][:, 0, 1] = cont_int[0][:, 0, 1] + np.abs(img_copy.shape[0] - img.shape[0])
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# # print(np.shape(cont_int[0]))
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# return cont_int[0]
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cont_int[0][:, 0, 0] = cont_int[0][:, 0, 0] + np.abs(img_copy.shape[1] - img.shape[1])
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cont_int[0][:, 0, 1] = cont_int[0][:, 0, 1] + np.abs(img_copy.shape[0] - img.shape[0])
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# print(np.shape(cont_int[0]))
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return cont_int[0]
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# def get_textregion_contours_in_org_image_multi2(cnts, img, slope_first):
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def get_textregion_contours_in_org_image_multi2(cnts, img, slope_first):
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# cnts_org = []
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# # print(cnts,'cnts')
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# with Pool(cpu_count()) as p:
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# cnts_org = p.starmap(loop_contour_image, [(index_l, cnts, img, slope_first) for index_l in range(len(cnts))])
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cnts_org = []
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# print(cnts,'cnts')
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with Pool(cpu_count()) as p:
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cnts_org = p.starmap(loop_contour_image, [(index_l, cnts, img, slope_first) for index_l in range(len(cnts))])
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# return cnts_org
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return cnts_org
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def get_textregion_contours_in_org_image(cnts, img, slope_first):
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@ -276,42 +276,42 @@ def get_textregion_contours_in_org_image(cnts, img, slope_first):
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return cnts_org
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# def get_textregion_contours_in_org_image_light(cnts, img, slope_first):
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def get_textregion_contours_in_org_image_light(cnts, img, slope_first):
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# h_o = img.shape[0]
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# w_o = img.shape[1]
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h_o = img.shape[0]
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w_o = img.shape[1]
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# img = cv2.resize(img, (int(img.shape[1]/3.), int(img.shape[0]/3.)), interpolation=cv2.INTER_NEAREST)
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# # cnts = list( (np.array(cnts)/2).astype(np.int16) )
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# # cnts = cnts/2
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# cnts = [(i / 3).astype(np.int32) for i in cnts]
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# cnts_org = []
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# # print(cnts,'cnts')
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# for i in range(len(cnts)):
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# img_copy = np.zeros(img.shape)
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# img_copy = cv2.fillPoly(img_copy, pts=[cnts[i]], color=(1, 1, 1))
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img = cv2.resize(img, (int(img.shape[1]/3.), int(img.shape[0]/3.)), interpolation=cv2.INTER_NEAREST)
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# cnts = list( (np.array(cnts)/2).astype(np.int16) )
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# cnts = cnts/2
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cnts = [(i / 3).astype(np.int32) for i in cnts]
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cnts_org = []
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# print(cnts,'cnts')
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for i in range(len(cnts)):
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img_copy = np.zeros(img.shape)
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img_copy = cv2.fillPoly(img_copy, pts=[cnts[i]], color=(1, 1, 1))
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# # plt.imshow(img_copy)
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# # plt.show()
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# plt.imshow(img_copy)
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# plt.show()
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# # print(img.shape,'img')
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# img_copy = rotation_image_new(img_copy, -slope_first)
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# # print(img_copy.shape,'img_copy')
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# # plt.imshow(img_copy)
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# # plt.show()
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# print(img.shape,'img')
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img_copy = rotation_image_new(img_copy, -slope_first)
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# print(img_copy.shape,'img_copy')
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# plt.imshow(img_copy)
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# plt.show()
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# img_copy = img_copy.astype(np.uint8)
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# imgray = cv2.cvtColor(img_copy, cv2.COLOR_BGR2GRAY)
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# ret, thresh = cv2.threshold(imgray, 0, 255, 0)
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img_copy = img_copy.astype(np.uint8)
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imgray = cv2.cvtColor(img_copy, cv2.COLOR_BGR2GRAY)
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ret, thresh = cv2.threshold(imgray, 0, 255, 0)
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# cont_int, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
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cont_int, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
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# cont_int[0][:, 0, 0] = cont_int[0][:, 0, 0] + np.abs(img_copy.shape[1] - img.shape[1])
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# cont_int[0][:, 0, 1] = cont_int[0][:, 0, 1] + np.abs(img_copy.shape[0] - img.shape[0])
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# # print(np.shape(cont_int[0]))
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# cnts_org.append(cont_int[0]*3)
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cont_int[0][:, 0, 0] = cont_int[0][:, 0, 0] + np.abs(img_copy.shape[1] - img.shape[1])
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cont_int[0][:, 0, 1] = cont_int[0][:, 0, 1] + np.abs(img_copy.shape[0] - img.shape[0])
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# print(np.shape(cont_int[0]))
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cnts_org.append(cont_int[0]*3)
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# return cnts_org
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return cnts_org
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def return_contours_of_interested_textline(region_pre_p, pixel):
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