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[Model] add function for setting anchor rknpu2 (PaddlePaddle#1728)
* add function for setting anchor rknpu2 add more demo for rknpu2 fixed md error * Update config.h --------- Co-authored-by: DefTruth <[email protected]>
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,54 @@ | ||
| // 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. | ||
| #include "fastdeploy/vision.h" | ||
|
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| void RKNPU2Infer(const std::string& model_file, const std::string& image_file) { | ||
| auto option = fastdeploy::RuntimeOption(); | ||
| option.UseRKNPU2(); | ||
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| auto format = fastdeploy::ModelFormat::RKNN; | ||
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| auto model = | ||
| fastdeploy::vision::detection::RKYOLOV7(model_file, option, format); | ||
|
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| auto im = cv::imread(image_file); | ||
|
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| fastdeploy::vision::DetectionResult res; | ||
| fastdeploy::TimeCounter tc; | ||
| tc.Start(); | ||
| if (!model.Predict(im, &res)) { | ||
| std::cerr << "Failed to predict." << std::endl; | ||
| return; | ||
| } | ||
| auto vis_im = fastdeploy::vision::VisDetection(im, res, 0.5); | ||
| tc.End(); | ||
| tc.PrintInfo("RKYOLOV5 in RKNN"); | ||
| std::cout << res.Str() << std::endl; | ||
| cv::imwrite("vis_result.jpg", vis_im); | ||
| std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl; | ||
| } | ||
|
|
||
| int main(int argc, char* argv[]) { | ||
| if (argc < 3) { | ||
| std::cout | ||
| << "Usage: infer_demo path/to/model_dir path/to/image run_option, " | ||
| "e.g ./infer_model ./picodet_model_dir ./test.jpeg" | ||
| << std::endl; | ||
| return -1; | ||
| } | ||
|
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| RKNPU2Infer(argv[1], argv[2]); | ||
|
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||
| return 0; | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,54 @@ | ||
| // 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. | ||
| #include "fastdeploy/vision.h" | ||
|
|
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| void RKNPU2Infer(const std::string& model_file, const std::string& image_file) { | ||
| auto option = fastdeploy::RuntimeOption(); | ||
| option.UseRKNPU2(); | ||
|
|
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| auto format = fastdeploy::ModelFormat::RKNN; | ||
|
|
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| auto model = | ||
| fastdeploy::vision::detection::RKYOLOX(model_file, option, format); | ||
|
|
||
| auto im = cv::imread(image_file); | ||
|
|
||
| fastdeploy::vision::DetectionResult res; | ||
| fastdeploy::TimeCounter tc; | ||
| tc.Start(); | ||
| if (!model.Predict(im, &res)) { | ||
| std::cerr << "Failed to predict." << std::endl; | ||
| return; | ||
| } | ||
| auto vis_im = fastdeploy::vision::VisDetection(im, res, 0.5); | ||
| tc.End(); | ||
| tc.PrintInfo("RKYOLOV5 in RKNN"); | ||
| std::cout << res.Str() << std::endl; | ||
| cv::imwrite("vis_result.jpg", vis_im); | ||
| std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl; | ||
| } | ||
|
|
||
| int main(int argc, char* argv[]) { | ||
| if (argc < 3) { | ||
| std::cout | ||
| << "Usage: infer_demo path/to/model_dir path/to/image run_option, " | ||
| "e.g ./infer_model ./picodet_model_dir ./test.jpeg" | ||
| << std::endl; | ||
| return -1; | ||
| } | ||
|
|
||
| RKNPU2Infer(argv[1], argv[2]); | ||
|
|
||
| return 0; | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,53 @@ | ||
| # 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 | ||
|
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|
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| def parse_arguments(): | ||
| import argparse | ||
| import ast | ||
| parser = argparse.ArgumentParser() | ||
| parser.add_argument( | ||
| "--model_file", required=True, help="Path of rknn model.") | ||
| parser.add_argument( | ||
| "--image", type=str, required=True, help="Path of test image file.") | ||
| return parser.parse_args() | ||
|
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|
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| if __name__ == "__main__": | ||
| args = parse_arguments() | ||
|
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| model_file = args.model_file | ||
| params_file = "" | ||
|
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| # 配置runtime，加载模型 | ||
| runtime_option = fd.RuntimeOption() | ||
| runtime_option.use_rknpu2() | ||
|
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| model = fd.vision.detection.RKYOLOV7( | ||
| model_file, | ||
| runtime_option=runtime_option, | ||
| model_format=fd.ModelFormat.RKNN) | ||
|
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| # 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("visualized_result.jpg", vis_im) | ||
| print("Visualized result save in ./visualized_result.jpg") |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,53 @@ | ||
| # 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 rknn model.") | ||
| parser.add_argument( | ||
| "--image", type=str, required=True, help="Path of test image file.") | ||
| return parser.parse_args() | ||
|
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||
|
|
||
| if __name__ == "__main__": | ||
| args = parse_arguments() | ||
|
|
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| model_file = args.model_file | ||
| params_file = "" | ||
|
|
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| # 配置runtime，加载模型 | ||
| runtime_option = fd.RuntimeOption() | ||
| runtime_option.use_rknpu2() | ||
|
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| model = fd.vision.detection.RKYOLOX( | ||
| model_file, | ||
| runtime_option=runtime_option, | ||
| model_format=fd.ModelFormat.RKNN) | ||
|
|
||
| # 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("visualized_result.jpg", vis_im) | ||
| print("Visualized result save in ./visualized_result.jpg") |
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