Merge branch 'develop' of https://github.com/PaddlePaddle/PaddleOCR into develop

configs/det/det_mv3_db.yml

@@ -11,7 +11,7 @@ Global:
   test_batch_size_per_card: 16
   image_shape: [3, 640, 640]
   reader_yml: ./configs/det/det_db_icdar15_reader.yml
-  pretrain_weights: ./pretrain_models/MobileNetV3_pretrained/MobileNetV3_large_x0_5_pretrained/
+  pretrain_weights: ./pretrain_models/MobileNetV3_large_x0_5_pretrained/
   checkpoints:
   save_res_path: ./output/det_db/predicts_db.txt
   save_inference_dir:

ppocr/data/det/dataset_traversal.py

@@ -89,13 +89,13 @@ class EvalTestReader(object):
 
         def batch_iter_reader():
             batch_outs = []
-            for img_path, img_name in img_list:
+            for img_path in img_list:
                 img = cv2.imread(img_path)
                 if img is None:
                     logger.info("load image error:" + img_path)
                     continue
                 outs = process_function(img)
-                outs.append(img_name)
+                outs.append(img_path)
                 batch_outs.append(outs)
                 if len(batch_outs) == batch_size:
                     yield batch_outs

tools/infer/predict_det.py

@@ -20,11 +20,14 @@ 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.utils.utility import get_image_file_list
+from tools.infer.utility import draw_ocr
 import copy
 import numpy as np
 import math
 import time
 import sys
+import os
 
 
 class TextDetector(object):
@@ -152,7 +155,7 @@ class TextDetector(object):
 
 if __name__ == "__main__":
     args = utility.parse_args()
-    image_file_list = utility.get_image_file_list(args.image_dir)
+    image_file_list = get_image_file_list(args.image_dir)
     text_detector = TextDetector(args)
     count = 0
     total_time = 0
@@ -166,5 +169,14 @@ if __name__ == "__main__":
             total_time += elapse
         count += 1
         print("Predict time of %s:" % image_file, elapse)
-        utility.draw_text_det_res(dt_boxes, image_file)
+        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        draw_img = draw_ocr(img, dt_boxes, None, None, False)
+        draw_img_save = "./inference_results/"
+        if not os.path.exists(draw_img_save):
+            os.makedirs(draw_img_save)
+        cv2.imwrite(
+            os.path.join(draw_img_save, os.path.basename(image_file)),
+            draw_img[:, :, ::-1])
+        print("The visualized image saved in {}".format(
+            os.path.join(draw_img_save, os.path.basename(image_file))))
     print("Avg Time:", total_time / (count - 1))

tools/infer/utility.py

@@ -127,10 +127,10 @@ def resize_img(img, input_size=600):
 def draw_ocr(image, boxes, txts, scores, draw_txt=True, drop_score=0.5):
     from PIL import Image, ImageDraw, ImageFont
 
-    w, h = image.size
     img = image.copy()
     draw = ImageDraw.Draw(img)
-
+    if scores is None:
+        scores = [1] * len(boxes)
     for (box, score) in zip(boxes, scores):
         if score < drop_score:
             continue

tools/infer_det.py

@@ -40,7 +40,7 @@ set_paddle_flags(
 )
 
 from paddle import fluid
-from ppocr.utils.utility import create_module
+from ppocr.utils.utility import create_module, get_image_file_list
 import program
 from ppocr.utils.save_load import init_model
 from ppocr.data.reader_main import reader_main
@@ -50,20 +50,18 @@ from ppocr.utils.utility import initial_logger
 logger = initial_logger()
 
 
-def draw_det_res(dt_boxes, config, img_name, ino):
+def draw_det_res(dt_boxes, config, img, img_name):
     if len(dt_boxes) > 0:
-        img_set_path = config['TestReader']['img_set_dir']
-        img_path = img_set_path + img_name
         import cv2
-        src_im = cv2.imread(img_path)
+        src_im = img
         for box in dt_boxes:
             box = box.astype(np.int32).reshape((-1, 1, 2))
             cv2.polylines(src_im, [box], True, color=(255, 255, 0), thickness=2)
-        save_det_path = os.path.basename(config['Global'][
+        save_det_path = os.path.dirname(config['Global'][
             'save_res_path']) + "/det_results/"
         if not os.path.exists(save_det_path):
             os.makedirs(save_det_path)
-        save_path = os.path.join(save_det_path, "det_{}.jpg".format(img_name))
+        save_path = os.path.join(save_det_path, os.path.basename(img_name))
         cv2.imwrite(save_path, src_im)
         logger.info("The detected Image saved in {}".format(save_path))
 
@@ -103,8 +101,12 @@ def main():
         raise Exception("{} not exists!".format(checkpoints))
 
     save_res_path = config['Global']['save_res_path']
+    if not os.path.exists(os.path.dirname(save_res_path)):
+        os.makedirs(os.path.dirname(save_res_path))
     with open(save_res_path, "wb") as fout:
+
         test_reader = reader_main(config=config, mode='test')
+        # image_file_list = get_image_file_list(args.image_dir)
         tackling_num = 0
         for data in test_reader():
             img_num = len(data)
@@ -128,7 +130,13 @@ def main():
             postprocess_params.update(global_params)
             postprocess = create_module(postprocess_params['function'])\
                 (params=postprocess_params)
-            dt_boxes_list = postprocess({"maps": outs[0]}, ratio_list)
+            if config['Global']['algorithm'] == 'EAST':
+                dic = {'f_score': outs[0], 'f_geo': outs[1]}
+            elif config['Global']['algorithm'] == 'DB':
+                dic = {'maps': outs[0]}
+            else:
+                raise Exception("only support algorithm: ['EAST', 'BD']")
+            dt_boxes_list = postprocess(dic, ratio_list)
             for ino in range(img_num):
                 dt_boxes = dt_boxes_list[ino]
                 img_name = img_name_list[ino]
@@ -139,7 +147,8 @@ def main():
                     dt_boxes_json.append(tmp_json)
                 otstr = img_name + "\t" + json.dumps(dt_boxes_json) + "\n"
                 fout.write(otstr.encode())
-                draw_det_res(dt_boxes, config, img_name, ino)
+                src_img = cv2.imread(img_name)
+                draw_det_res(dt_boxes, config, src_img, img_name)
 
     logger.info("success!")