add ocr, ppyoloe, picodet examples (#1076)

* add ocr examples

* add ppyoloe examples

add picodet examples

* remove /ScaleFactor in ppdet/postprocessor.cc
This commit is contained in:
Dantès
2023-01-10 16:34:26 +08:00
committed by GitHub
parent fc314f1696
commit de70e8366c
21 changed files with 922 additions and 13 deletions

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# PaddleDetection Python部署示例
在部署前,需确认以下步骤
- 1. 软硬件环境满足要求,参考[FastDeploy环境要求](../../../../../../docs/cn/build_and_install/sophgo.md)
本目录下提供`infer_ppyoloe.py``infer_picodet.py`快速完成 PP-YOLOE 和 PicoDet 在SOPHGO TPU上部署的示例。执行如下脚本即可完成
```bash
# 下载部署示例代码
git clone https://github.com/PaddlePaddle/FastDeploy.git
cd FastDeploy/examples/vision/detection/paddledetection/sophgo/python
# 下载图片
wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
# 推理
#ppyoloe推理示例
python3 infer_ppyoloe.py --model_file model/ppyoloe_crn_s_300e_coco_1684x_f32.bmodel --config_file model/infer_cfg.yml --image ./000000014439.jpg
#picodet推理示例
python3 infer_picodet.py --model_file model/picodet_s_416_coco_lcnet_1684x_f32.bmodel --config_file model/infer_cfg.yml --image ./000000014439.jpg
# 运行完成后返回结果如下所示
可视化结果存储在sophgo_result.jpg中
```
## 其它文档
- [PP-YOLOE C++部署](../cpp)
- [PicoDet C++部署](../cpp)
- [转换PicoDet SOPHGO模型文档](../README.md)
- [转换PP-YOLOE SOPHGO模型文档](../README.md)

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# Copyright (c) 2022 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.
import fastdeploy as fd
import cv2
import os
def parse_arguments():
import argparse
import ast
parser = argparse.ArgumentParser()
parser.add_argument(
"--model_file", required=True, help="Path of sophgo model.")
parser.add_argument("--config_file", required=True, help="Path of config.")
parser.add_argument(
"--image", type=str, required=True, help="Path of test image file.")
return parser.parse_args()
if __name__ == "__main__":
args = parse_arguments()
model_file = args.model_file
params_file = ""
config_file = args.config_file
# 配置runtime加载模型
runtime_option = fd.RuntimeOption()
runtime_option.use_sophgo()
model = fd.vision.detection.PicoDet(
model_file,
params_file,
config_file,
runtime_option=runtime_option,
model_format=fd.ModelFormat.SOPHGO)
model.postprocessor.apply_decode_and_nms()
# 预测图片分割结果
im = cv2.imread(args.image)
result = model.predict(im)
print(result)
# 可视化结果
vis_im = fd.vision.vis_detection(im, result, score_threshold=0.5)
cv2.imwrite("sophgo_result.jpg", vis_im)
print("Visualized result save in ./sophgo_result.jpg")

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# Copyright (c) 2022 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.
import fastdeploy as fd
import cv2
import os
def parse_arguments():
import argparse
import ast
parser = argparse.ArgumentParser()
parser.add_argument(
"--model_file", required=True, help="Path of sophgo model.")
parser.add_argument("--config_file", required=True, help="Path of config.")
parser.add_argument(
"--image", type=str, required=True, help="Path of test image file.")
return parser.parse_args()
if __name__ == "__main__":
args = parse_arguments()
model_file = args.model_file
params_file = ""
config_file = args.config_file
# 配置runtime加载模型
runtime_option = fd.RuntimeOption()
runtime_option.use_sophgo()
model = fd.vision.detection.PPYOLOE(
model_file,
params_file,
config_file,
runtime_option=runtime_option,
model_format=fd.ModelFormat.SOPHGO)
model.postprocessor.apply_decode_and_nms()
# 预测图片分割结果
im = cv2.imread(args.image)
result = model.predict(im)
print(result)
# 可视化结果
vis_im = fd.vision.vis_detection(im, result, score_threshold=0.5)
cv2.imwrite("sophgo_result.jpg", vis_im)
print("Visualized result save in ./sophgo_result.jpg")