add HRNet export model tutorials (#5502)

tutorials/pp-series/HRNet-Keypoint/README.md

@@ -98,9 +98,9 @@ python -c "import paddle; print(paddle.__version__)"
 - If the coco dataset has been downloaded  
     The files can be organized according to the above data file organization structure.
 
-### 2.3 Training & Evaluation & Inference
+### 2.3 Training & Evaluation & Test
 
-We provides scripts for training, evalution and inference with various features according to different configure.
+We provides scripts for training, evalution and test with various features according to different configure.
 
 ```bash
 # training on single-GPU
@@ -115,7 +115,7 @@ python -m paddle.distributed.launch --gpus 0,1,2,3,4,5,6,7 tools/train.py -c con
 export CUDA_VISIBLE_DEVICES=0
 python tools/eval.py -c configs/hrnet_w32_256x192.yml -o weights=https://paddledet.bj.bcebos.com/models/keypoint/hrnet_w32_256x192.pdparams
 
-# Inference
+# test
 python tools/infer.py -c configs/hrnet_w32_256x192.yml --infer_img=dataset/test_image/hrnet_demo.jpg -o weights=https://paddledet.bj.bcebos.com/models/keypoint/hrnet_w32_256x192.pdparams
 
 # training with distillation
@@ -133,10 +133,32 @@ python -m paddle.distributed.launch --gpus 0,1,2,3,4,5,6,7 tools/train.py -c con
 export CUDA_VISIBLE_DEVICES=0
 python tools/eval.py -c configs/lite_hrnet_30_256x192_coco_pact.yml -o weights=https://paddledet.bj.bcebos.com/models/keypoint/lite_hrnet_30_256x192_coco_pact.pdparams
 
-# Inference with PACT quantization
+# test with PACT quantization
 python tools/infer.py -c configs/lite_hrnet_30_256x192_coco_pact.yml
 --infer_img=dataset/test_image/hrnet_demo.jpg -o weights=https://paddledet.bj.bcebos.com/models/keypoint/lite_hrnet_30_256x192_coco_pact.pdparams
 
+```
+
+### 2.4 Export model & Inference
+
+```bash
+# export model
+python tools/export_model.py -c configs/hrnet_w32_256x192.yml -o  weights=https://paddledet.bj.bcebos.com/models/keypoint/hrnet_w32_256x192_coco.pdparams
+
+# inference
+python deploy/infer.py  --model_dir=output_inference/hrnet_w32_256x192/ --image_file=dataset/test_image/hrnet_demo.jpg
+
+# export model with lite model
+python tools/export_model.py -c configs/lite_hrnet_30_256x192_coco.yml -o  weights=https://paddledet.bj.bcebos.com/models/keypoint/lite_hrnet_30_256x192_coco.pdparams
+
+# inference with lite model
+python deploy/infer.py  --model_dir=output_inference/lite_hrnet_30_256x192_coco/ --image_file=dataset/test_image/hrnet_demo.jpg
+
+# export model with PACT quantization
+python tools/export_model.py -c configs/lite_hrnet_30_256x192_coco_pact.yml -o  weights=https://paddledet.bj.bcebos.com/models/keypoint/lite_hrnet_30_256x192_coco_pact.pdparams
+
+# inference with PACT quantization
+python deploy/infer.py  --model_dir=output_inference/lite_hrnet_30_256x192_coco_pact/ --image_file=dataset/test_image/hrnet_demo.jpg
 
 ```
 

tutorials/pp-series/HRNet-Keypoint/dataset/download_coco.py

@@ -16,11 +16,11 @@ import sys
 import os.path as osp
 import logging
 # add python path of PadleDetection to sys.path
-parent_path = osp.abspath(osp.join(__file__, *(['..'] * 3)))
+parent_path = osp.abspath(osp.join(__file__, *(['..'] * 2)))
 if parent_path not in sys.path:
     sys.path.append(parent_path)
 
-from ppdet.utils.download import download_dataset
+from lib.utils.download import download_dataset
 
 logging.basicConfig(level=logging.INFO)
 

tutorials/pp-series/HRNet-Keypoint/tools/export_model.py

+# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import os
+import sys
+
+# add python path of PadleDetection to sys.path
+parent_path = os.path.abspath(os.path.join(__file__, *(['..'] * 2)))
+sys.path.insert(0, parent_path)
+
+# ignore warning log
+import warnings
+warnings.filterwarnings('ignore')
+import glob
+
+import paddle
+from lib.utils.workspace import load_config, merge_config
+from lib.slim import build_slim_model
+from lib.core.trainer import Trainer
+from lib.utils.check import check_gpu, check_version, check_config
+from lib.utils.cli import ArgsParser
+from lib.utils.logger import setup_logger
+
+logger = setup_logger('eval')
+
+
+def parse_args():
+    parser = ArgsParser()
+    parser.add_argument(
+        "--save-inference-dir",
+        default='output_inference',
+        type=str,
+        help="Evaluation directory, default is current directory.")
+
+    args = parser.parse_args()
+    return args
+
+
+def main():
+    FLAGS = parse_args()
+    cfg = load_config(FLAGS.config)
+    # cfg['output_eval'] = FLAGS.output_eval
+    merge_config(FLAGS.opt)
+
+    if cfg.use_gpu:
+        paddle.set_device('gpu')
+    else:
+        paddle.set_device('cpu')
+
+    if 'slim' in cfg:
+        cfg = build_slim_model(cfg, mode='test')
+
+    check_config(cfg)
+    check_gpu(cfg.use_gpu)
+    check_version()
+
+    # build trainer
+    trainer = Trainer(cfg, mode='test')
+
+    # load weights
+    trainer.load_weights(cfg.weights)
+
+    # export model
+    trainer.export(output_dir=FLAGS.save_inference_dir)
+
+
+if __name__ == '__main__':
+    main()