Merge pull request #552 from MissPenguin/develop
modify infer tools for sast
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aecbbe1cbf
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@ -20,7 +20,5 @@ EvalReader:
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TestReader:
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reader_function: ppocr.data.det.dataset_traversal,EvalTestReader
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process_function: ppocr.data.det.sast_process,SASTProcessTest
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infer_img:
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img_set_dir: ./train_data/icdar2015/text_localization/
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label_file_path: ./train_data/icdar2015/text_localization/test_icdar2015_label.txt
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do_eval: True
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infer_img: ./train_data/icdar2015/text_localization/ch4_test_images/img_11.jpg
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max_side_len: 1536
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@ -20,5 +20,5 @@ EvalReader:
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TestReader:
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reader_function: ppocr.data.det.dataset_traversal,EvalTestReader
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process_function: ppocr.data.det.sast_process,SASTProcessTest
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infer_img:
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infer_img: ./train_data/afs/total_text/Images/Test/img623.jpg
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max_side_len: 768
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@ -49,7 +49,7 @@ class SASTHead(object):
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for i in range(4):
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if i == 0:
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g[i] = deconv_bn_layer(input=h[i], num_filters=num_outputs[i + 1], act=None, name='fpn_up_g0')
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print("g[{}] shape: {}".format(i, g[i].shape))
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#print("g[{}] shape: {}".format(i, g[i].shape))
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else:
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g[i] = fluid.layers.elementwise_add(x=g[i - 1], y=h[i])
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g[i] = fluid.layers.relu(g[i])
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@ -58,7 +58,7 @@ class SASTHead(object):
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g[i] = conv_bn_layer(input=g[i], num_filters=num_outputs[i],
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filter_size=3, stride=1, act='relu', name='fpn_up_g%d_1'%i)
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g[i] = deconv_bn_layer(input=g[i], num_filters=num_outputs[i + 1], act=None, name='fpn_up_g%d_2'%i)
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print("g[{}] shape: {}".format(i, g[i].shape))
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#print("g[{}] shape: {}".format(i, g[i].shape))
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g[4] = fluid.layers.elementwise_add(x=g[3], y=h[4])
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g[4] = fluid.layers.relu(g[4])
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@ -22,10 +22,12 @@ from ppocr.utils.utility import initial_logger
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logger = initial_logger()
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from ppocr.utils.utility import get_image_file_list, check_and_read_gif
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import cv2
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from ppocr.data.det.sast_process import SASTProcessTest
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from ppocr.data.det.east_process import EASTProcessTest
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from ppocr.data.det.db_process import DBProcessTest
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from ppocr.postprocess.db_postprocess import DBPostProcess
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from ppocr.postprocess.east_postprocess import EASTPostPocess
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from ppocr.postprocess.sast_postprocess import SASTPostProcess
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import copy
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import numpy as np
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import math
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@ -52,6 +54,14 @@ class TextDetector(object):
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postprocess_params["cover_thresh"] = args.det_east_cover_thresh
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postprocess_params["nms_thresh"] = args.det_east_nms_thresh
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self.postprocess_op = EASTPostPocess(postprocess_params)
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elif self.det_algorithm == "SAST":
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self.preprocess_op = SASTProcessTest(preprocess_params)
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postprocess_params["score_thresh"] = args.det_sast_score_thresh
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postprocess_params["nms_thresh"] = args.det_sast_nms_thresh
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postprocess_params["sample_pts_num"] = args.det_sast_sample_pts_num
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postprocess_params["expand_scale"] = args.det_sast_expand_scale
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postprocess_params["shrink_ratio_of_width"] = args.det_sast_shrink_ratio_of_width
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self.postprocess_op = SASTPostProcess(postprocess_params)
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else:
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logger.info("unknown det_algorithm:{}".format(self.det_algorithm))
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sys.exit(0)
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@ -120,8 +130,14 @@ class TextDetector(object):
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if self.det_algorithm == "EAST":
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outs_dict['f_geo'] = outputs[0]
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outs_dict['f_score'] = outputs[1]
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elif self.det_algorithm == 'SAST':
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outs_dict['f_border'] = outputs[0]
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outs_dict['f_score'] = outputs[1]
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outs_dict['f_tco'] = outputs[2]
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outs_dict['f_tvo'] = outputs[3]
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else:
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outs_dict['maps'] = outputs[0]
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dt_boxes_list = self.postprocess_op(outs_dict, [ratio_list])
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dt_boxes = dt_boxes_list[0]
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dt_boxes = self.filter_tag_det_res(dt_boxes, ori_im.shape)
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@ -53,6 +53,13 @@ def parse_args():
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parser.add_argument("--det_east_cover_thresh", type=float, default=0.1)
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parser.add_argument("--det_east_nms_thresh", type=float, default=0.2)
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#SAST parmas
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parser.add_argument("--det_sast_score_thresh", type=float, default=0.5)
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parser.add_argument("--det_sast_nms_thresh", type=float, default=0.2)
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parser.add_argument("--det_sast_sample_pts_num", type=float, default=2)
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parser.add_argument("--det_sast_expand_scale", type=float, default=1.0)
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parser.add_argument("--det_sast_shrink_ratio_of_width", type=float, default=0.3)
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#params for text recognizer
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parser.add_argument("--rec_algorithm", type=str, default='CRNN')
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parser.add_argument("--rec_model_dir", type=str)
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@ -134,8 +134,10 @@ def main():
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dic = {'f_score': outs[0], 'f_geo': outs[1]}
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elif config['Global']['algorithm'] == 'DB':
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dic = {'maps': outs[0]}
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elif config['Global']['algorithm'] == 'SAST':
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dic = {'f_score': outs[0], 'f_border': outs[1], 'f_tvo': outs[2], 'f_tco': outs[3]}
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else:
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raise Exception("only support algorithm: ['EAST', 'DB']")
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raise Exception("only support algorithm: ['EAST', 'DB', 'SAST']")
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dt_boxes_list = postprocess(dic, ratio_list)
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for ino in range(img_num):
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dt_boxes = dt_boxes_list[ino]
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@ -149,7 +151,7 @@ def main():
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fout.write(otstr.encode())
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src_img = cv2.imread(img_name)
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draw_det_res(dt_boxes, config, src_img, img_name)
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logger.info("success!")
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