Merge pull request #65 from tink2123/save_epoch_0

Save weights at epoch 0

configs/det/det_mv3_east.yml

@@ -11,7 +11,7 @@ Global:
   test_batch_size_per_card: 16
   image_shape: [3, 512, 512]
   reader_yml: ./configs/det/det_east_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_east/predicts_east.txt
   save_inference_dir:
@@ -42,4 +42,4 @@ PostProcess:
   score_thresh: 0.8
   cover_thresh: 0.1
   nms_thresh: 0.2
-  
+  

configs/det/det_r50_vd_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/ResNet50_vd_pretrained/
+  pretrain_weights: ./pretrain_models/ResNet50_vd_ssld_pretrained/
   save_res_path: ./output/det_db/predicts_db.txt
   checkpoints:
   save_inference_dir:
@@ -50,4 +50,4 @@ PostProcess:
   box_thresh: 0.7
   max_candidates: 1000
   unclip_ratio: 1.5
-  
+  

configs/det/det_r50_vd_east.yml

@@ -11,7 +11,7 @@ Global:
   test_batch_size_per_card: 16
   image_shape: [3, 512, 512]
   reader_yml: ./configs/det/det_east_icdar15_reader.yml
-  pretrain_weights: ./pretrain_models/ResNet50_vd_pretrained/
+  pretrain_weights: ./pretrain_models/ResNet50_vd_ssld_pretrained/
   save_res_path: ./output/det_east/predicts_east.txt
   checkpoints:
   save_inference_dir:
@@ -41,4 +41,4 @@ PostProcess:
   score_thresh: 0.8
   cover_thresh: 0.1
   nms_thresh: 0.2
-  
+  

doc/detection.md

@@ -16,7 +16,7 @@ wget -P ./train_data/  https://paddleocr.bj.bcebos.com/dataset/test_icdar2015_la
 
 解压数据集和下载标注文件后，PaddleOCR/train_data/ 有两个文件夹和两个文件，分别是：
 ```
-/PaddleOCR/train_data/  
+/PaddleOCR/train_data/icdar2015/text_localization/
   └─ icdar_c4_train_imgs/         icdar数据集的训练数据
   └─ ch4_test_images/             icdar数据集的测试数据
   └─ train_icdar2015_label.txt    icdar数据集的训练标注
@@ -79,10 +79,10 @@ python3 tools/eval.py -c configs/det/det_mv3_db.yml  -o Global.checkpoints="./ou
 
 测试单张图像的检测效果
 ```
-python3 tools/infer_det.py -c config/det/det_mv3_db.yml -o TestReader.single_img_path="./doc/imgs_en/img_10.jpg" Global.checkpoints="./output/det_db/best_accuracy"
+python3 tools/infer_det.py -c configs/det/det_mv3_db.yml -o TestReader.single_img_path="./doc/imgs_en/img_10.jpg" Global.checkpoints="./output/det_db/best_accuracy"
 ```
 
 测试文件夹下所有图像的检测效果
 ```
-python3 tools/infer_det.py -c config/det/det_mv3_db.yml -o TestReader.single_img_path="./doc/imgs_en/" Global.checkpoints="./output/det_db/best_accuracy"
+python3 tools/infer_det.py -c configs/det/det_mv3_db.yml -o TestReader.single_img_path="./doc/imgs_en/" Global.checkpoints="./output/det_db/best_accuracy"
 ```

doc/installation.md

@@ -20,7 +20,7 @@ sudo nvidia-docker run --name ppocr -v $PWD:/paddle --network=host -it hub.baidu
 sudo nvidia-docker container exec -it ppocr /bin/bash
 ```
 
-2. 安装PaddlePaddle Fluid v1.7或更高版本
+2. 安装PaddlePaddle Fluid v1.7(暂不支持更高版本,适配工作进行中)
 ```
 pip3 install --upgrade pip
 

tools/program.py

@@ -269,7 +269,9 @@ def train_eval_det_run(config, exe, train_info_dict, eval_info_dict):
 
         except fluid.core.EOFException:
             train_loader.reset()
-
+        if epoch == 0 and save_epoch_step == 1:
+            save_path = save_model_dir + "/iter_epoch_0"
+            save_model(train_info_dict['train_program'],save_path)
         if epoch > 0 and epoch % save_epoch_step == 0:
             save_path = save_model_dir + "/iter_epoch_%d" % (epoch)
             save_model(train_info_dict['train_program'], save_path)
@@ -346,7 +348,9 @@ def train_eval_rec_run(config, exe, train_info_dict, eval_info_dict):
 
         except fluid.core.EOFException:
             train_loader.reset()
-
+        if epoch == 0 and save_epoch_step == 1:
+            save_path = save_model_dir + "/iter_epoch_0"
+            save_model(train_info_dict['train_program'],save_path)
         if epoch > 0 and epoch % save_epoch_step == 0:
             save_path = save_model_dir + "/iter_epoch_%d" % (epoch)
             save_model(train_info_dict['train_program'], save_path)