modify infer tools for sast

configs/det/det_sast_icdar15_reader.yml

@@ -20,7 +20,5 @@ EvalReader:
 TestReader:
   reader_function: ppocr.data.det.dataset_traversal,EvalTestReader
   process_function: ppocr.data.det.sast_process,SASTProcessTest
-  infer_img: 
-  img_set_dir: ./train_data/icdar2015/text_localization/
-  label_file_path: ./train_data/icdar2015/text_localization/test_icdar2015_label.txt
-  do_eval: True
+  infer_img: ./train_data/icdar2015/text_localization/ch4_test_images/img_11.jpg
+  max_side_len: 1536

configs/det/det_sast_totaltext_reader.yml

@@ -20,5 +20,5 @@ EvalReader:
 TestReader:
   reader_function: ppocr.data.det.dataset_traversal,EvalTestReader
   process_function: ppocr.data.det.sast_process,SASTProcessTest
-  infer_img: 
+  infer_img: ./train_data/afs/total_text/Images/Test/img623.jpg
   max_side_len: 768

ppocr/modeling/heads/det_sast_head.py

@@ -49,7 +49,7 @@ class SASTHead(object):
         for i in range(4):
             if i == 0:
                 g[i] = deconv_bn_layer(input=h[i], num_filters=num_outputs[i + 1], act=None, name='fpn_up_g0')
-                print("g[{}] shape: {}".format(i, g[i].shape))
+                #print("g[{}] shape: {}".format(i, g[i].shape))
             else:
                 g[i] = fluid.layers.elementwise_add(x=g[i - 1], y=h[i])
                 g[i] = fluid.layers.relu(g[i])
@@ -58,7 +58,7 @@ class SASTHead(object):
                 g[i] = conv_bn_layer(input=g[i], num_filters=num_outputs[i],
                                     filter_size=3, stride=1, act='relu', name='fpn_up_g%d_1'%i)
                 g[i] = deconv_bn_layer(input=g[i], num_filters=num_outputs[i + 1], act=None, name='fpn_up_g%d_2'%i)
-                print("g[{}] shape: {}".format(i, g[i].shape))
+                #print("g[{}] shape: {}".format(i, g[i].shape))
 
         g[4] = fluid.layers.elementwise_add(x=g[3], y=h[4])
         g[4] = fluid.layers.relu(g[4])

tools/infer/predict_det.py

@@ -22,10 +22,12 @@ from ppocr.utils.utility import initial_logger
 logger = initial_logger()
 from ppocr.utils.utility import get_image_file_list, check_and_read_gif
 import cv2
+from ppocr.data.det.sast_process import SASTProcessTest
 from ppocr.data.det.east_process import EASTProcessTest
 from ppocr.data.det.db_process import DBProcessTest
 from ppocr.postprocess.db_postprocess import DBPostProcess
 from ppocr.postprocess.east_postprocess import EASTPostPocess
+from ppocr.postprocess.sast_postprocess import SASTPostProcess
 import copy
 import numpy as np
 import math
@@ -52,6 +54,14 @@ class TextDetector(object):
             postprocess_params["cover_thresh"] = args.det_east_cover_thresh
             postprocess_params["nms_thresh"] = args.det_east_nms_thresh
             self.postprocess_op = EASTPostPocess(postprocess_params)
+        elif self.det_algorithm == "SAST":
+            self.preprocess_op = SASTProcessTest(preprocess_params)
+            postprocess_params["score_thresh"] = args.det_sast_score_thresh
+            postprocess_params["nms_thresh"] = args.det_sast_nms_thresh
+            postprocess_params["sample_pts_num"] = args.det_sast_sample_pts_num
+            postprocess_params["expand_scale"] = args.det_sast_expand_scale
+            postprocess_params["shrink_ratio_of_width"] = args.det_sast_shrink_ratio_of_width
+            self.postprocess_op = SASTPostProcess(postprocess_params)
         else:
             logger.info("unknown det_algorithm:{}".format(self.det_algorithm))
             sys.exit(0)
@@ -120,8 +130,14 @@ class TextDetector(object):
         if self.det_algorithm == "EAST":
             outs_dict['f_geo'] = outputs[0]
             outs_dict['f_score'] = outputs[1]
+        elif self.det_algorithm == 'SAST':
+            outs_dict['f_border'] = outputs[0]
+            outs_dict['f_score'] = outputs[1]
+            outs_dict['f_tco'] = outputs[2]
+            outs_dict['f_tvo'] = outputs[3]
         else:
             outs_dict['maps'] = outputs[0]
+                
         dt_boxes_list = self.postprocess_op(outs_dict, [ratio_list])
         dt_boxes = dt_boxes_list[0]
         dt_boxes = self.filter_tag_det_res(dt_boxes, ori_im.shape)

tools/infer/utility.py

@@ -53,6 +53,13 @@ def parse_args():
     parser.add_argument("--det_east_cover_thresh", type=float, default=0.1)
     parser.add_argument("--det_east_nms_thresh", type=float, default=0.2)
 
+    #SAST parmas
+    parser.add_argument("--det_sast_score_thresh", type=float, default=0.5)
+    parser.add_argument("--det_sast_nms_thresh", type=float, default=0.2)
+    parser.add_argument("--det_sast_sample_pts_num", type=float, default=2)
+    parser.add_argument("--det_sast_expand_scale", type=float, default=1.0)
+    parser.add_argument("--det_sast_shrink_ratio_of_width", type=float, default=0.3)
+
     #params for text recognizer
     parser.add_argument("--rec_algorithm", type=str, default='CRNN')
     parser.add_argument("--rec_model_dir", type=str)

tools/infer_det.py

@@ -66,6 +66,25 @@ def draw_det_res(dt_boxes, config, img, img_name):
         cv2.imwrite(save_path, src_im)
         logger.info("The detected Image saved in {}".format(save_path))
 
+def gen_im_detection(src_im, detections):
+    """
+    Generate image with detection results.
+    """
+    im_detection = src_im.copy()
+
+    h, w, _ = im_detection.shape
+    thickness = int(max((h + w) / 2000, 1))
+
+    for poly in detections:
+        # Draw the first point
+        cv2.putText(im_detection, '0', org=(int(poly[0, 0]), int(poly[0, 1])),
+                    fontFace=cv2.FONT_HERSHEY_COMPLEX, fontScale=thickness, color=(255, 0, 0),
+                    thickness=thickness)
+
+        cv2.polylines(im_detection, np.array(poly).reshape((1, -1, 2)).astype(np.int32), isClosed=True,
+                  color=(0, 0, 255), thickness=thickness)
+
+    return im_detection
 
 def main():
     config = program.load_config(FLAGS.config)
@@ -134,8 +153,10 @@ def main():
                 dic = {'f_score': outs[0], 'f_geo': outs[1]}
             elif config['Global']['algorithm'] == 'DB':
                 dic = {'maps': outs[0]}
+            elif config['Global']['algorithm'] == 'SAST':
+                dic = {'f_score': outs[0], 'f_border': outs[1], 'f_tvo': outs[2], 'f_tco': outs[3]}
             else:
-                raise Exception("only support algorithm: ['EAST', 'DB']")
+                raise Exception("only support algorithm: ['EAST', 'DB', 'SAST']")
             dt_boxes_list = postprocess(dic, ratio_list)
             for ino in range(img_num):
                 dt_boxes = dt_boxes_list[ino]