Merge pull request #1339 from WenmuZhou/py_inference_doc

[Dygraph] add py inference doc

configs/cls/cls_mv3.yml

@@ -8,7 +8,6 @@ Global:
   # evaluation is run every 5000 iterations after the 4000th iteration
   eval_batch_step: [0, 1000]
   # if pretrained_model is saved in static mode, load_static_weights must set to True
-  load_static_weights: True
   cal_metric_during_train: True
   pretrained_model:
   checkpoints:

deploy/cpp_infer/src/ocr_cls.cpp

@@ -81,7 +81,8 @@ cv::Mat Classifier::Run(cv::Mat &img) {
 
 void Classifier::LoadModel(const std::string &model_dir) {
   AnalysisConfig config;
-  config.SetModel(model_dir + ".pdmodel", model_dir + ".pdiparams");
+  config.SetModel(model_dir + "/inference.pdmodel",
+                  model_dir + "/inference.pdiparams");
 
   if (this->use_gpu_) {
     config.EnableUseGpu(this->gpu_mem_, this->gpu_id_);

deploy/cpp_infer/src/ocr_det.cpp

@@ -18,7 +18,8 @@ namespace PaddleOCR {
 
 void DBDetector::LoadModel(const std::string &model_dir) {
   AnalysisConfig config;
-  config.SetModel(model_dir + ".pdmodel", model_dir + ".pdiparams");
+  config.SetModel(model_dir + "/inference.pdmodel",
+                  model_dir + "/inference.pdiparams");
 
   if (this->use_gpu_) {
     config.EnableUseGpu(this->gpu_mem_, this->gpu_id_);

deploy/cpp_infer/src/ocr_rec.cpp

@@ -103,7 +103,8 @@ void CRNNRecognizer::Run(std::vector<std::vector<std::vector<int>>> boxes,
 
 void CRNNRecognizer::LoadModel(const std::string &model_dir) {
   AnalysisConfig config;
-  config.SetModel(model_dir + ".pdmodel", model_dir + ".pdiparams");
+  config.SetModel(model_dir + "/inference.pdmodel",
+                  model_dir + "/inference.pdiparams");
 
   if (this->use_gpu_) {
     config.EnableUseGpu(this->gpu_mem_, this->gpu_id_);

doc/doc_ch/angle_class.md

@@ -62,9 +62,9 @@ PaddleOCR提供了训练脚本、评估脚本和预测脚本。
 *如果您安装的是cpu版本，请将配置文件中的 `use_gpu` 字段修改为false*
 
 ```
-# GPU训练 支持单卡，多卡训练，通过selected_gpus指定卡号
+# GPU训练 支持单卡，多卡训练，通过gpus指定卡号
 # 启动训练，下面的命令已经写入train.sh文件中，只需修改文件里的配置文件路径即可
-python3 -m paddle.distributed.launch --selected_gpus '0,1,2,3,4,5,6,7'  tools/train.py -c configs/cls/cls_mv3.yml
+python3 -m paddle.distributed.launch --gpus '0,1,2,3,4,5,6,7'  tools/train.py -c configs/cls/cls_mv3.yml
 ```
 
 - 数据增强

doc/doc_en/angle_class_en.md

@@ -65,9 +65,9 @@ Start training:
 ```
 # Set PYTHONPATH path
 export PYTHONPATH=$PYTHONPATH:.
-# GPU training Support single card and multi-card training, specify the card number through selected_gpus
+# GPU training Support single card and multi-card training, specify the card number through gpus
 # Start training, the following command has been written into the train.sh file, just modify the configuration file path in the file
-python3 -m paddle.distributed.launch --selected_gpus '0,1,2,3,4,5,6,7'  tools/train.py -c configs/cls/cls_mv3.yml
+python3 -m paddle.distributed.launch --gpus '0,1,2,3,4,5,6,7'  tools/train.py -c configs/cls/cls_mv3.yml
 ```
 
 - Data Augmentation

tools/export_model.py

@@ -28,21 +28,15 @@ from ppocr.modeling.architectures import build_model
 from ppocr.postprocess import build_post_process
 from ppocr.utils.save_load import init_model
 from ppocr.utils.logging import get_logger
-from tools.program import load_config
-
-
-def parse_args():
-    parser = argparse.ArgumentParser()
-    parser.add_argument("-c", "--config", help="configuration file to use")
-    parser.add_argument(
-        "-o", "--output_path", type=str, default='./output/infer/')
-    return parser.parse_args()
+from tools.program import load_config, merge_config,ArgsParser
 
 
 def main():
-    FLAGS = parse_args()
+    FLAGS = ArgsParser().parse_args()
     config = load_config(FLAGS.config)
+    merge_config(FLAGS.opt)
     logger = get_logger()
+    print(config)
     # build post process
 
     post_process_class = build_post_process(config['PostProcess'],
@@ -57,8 +51,7 @@ def main():
     init_model(config, model, logger)
     model.eval()
 
-    save_path = '{}/{}/inference'.format(FLAGS.output_path,
-                                         config['Architecture']['model_type'])
+    save_path = '{}/inference'.format(config['Global']['save_inference_dir'])
     infer_shape = [3, 32, 100] if config['Architecture'][
         'model_type'] != "det" else [3, 640, 640]
     model = to_static(

tools/infer/utility.py

@@ -100,8 +100,8 @@ def create_predictor(args, mode, logger):
     if model_dir is None:
         logger.info("not find {} model file path {}".format(mode, model_dir))
         sys.exit(0)
-    model_file_path = model_dir + ".pdmodel"
-    params_file_path = model_dir + ".pdiparams"
+    model_file_path = model_dir + "/inference.pdmodel"
+    params_file_path = model_dir + "/inference.pdiparams"
     if not os.path.exists(model_file_path):
         logger.info("not find model file path {}".format(model_file_path))
         sys.exit(0)

train.sh

- python3 -m paddle.distributed.launch --selected_gpus '0,1,2,3,4,5,6,7'  tools/train.py -c configs/rec/rec_mv3_none_bilstm_ctc.yml
+ python3 -m paddle.distributed.launch --gpus '0,1,2,3,4,5,6,7'  tools/train.py -c configs/rec/rec_mv3_none_bilstm_ctc.yml
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