FastDeploy
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⚡️An Easy-to-use and Fast Deep Learning Model Deployment Toolkit for ☁️Cloud 📱Mobile and 📹Edge. Including Image, Video, Text and Audio 20+ main stream scenarios and 150+ SOTA models with end-to-end...
对应PaddleDetection:https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot
### PR types(PR类型) TensorRT后端 ### Describe - 移除原有PaddleDetection模型部署的Trick逻辑,改为使用TensorRT BatchedNMSDynamic_TRT插件(EfficientNMS_TRT无法对齐所有PaddleDetection检测模型结果)
### PR types Model ### Describe - **[HeadPose]** Support new model [FSANet](https://github.com/omasaht/headpose-fsanet-pytorch) - Add new result struct ```HeadPoseResult```
1.完善量化工具, 支持同一模型, 在QAT(train)和PTQ(eval)分别使用不同的图片预处理函数 2.打通PP_LiteSeg模型. 3.更新相关readme. 4.添加PP_LiteSeg量化模型部署example.
fast deploy 可以支持推理和可视化结果分开吗;预测得到的DetectionResult 结果 ( result = model.predict(im.copy()) ) .可以支持序列化吗? 然后在反序列化结果执行 vis_im = vision.vis_detection(im, result, score_threshold=0.5) 得到绘制检测对象的图片? 使用pickle序列化会出现错误 TypeError: can't pickle fastdeploy.libs.fastdeploy_main.vision.DetectionResult objects
### PR types(PR类型) Model ### Describe - Add text classification example for ernie-3.0
### PR types(PR类型) Benchmark ### Describe Add benchmark for ernie sequence classification. Statistics include: - Time cost of each stage, including tokenization, runtime and postprocessing - CPU memory cost -...
[文档](https://github.com/PaddlePaddle/FastDeploy/blob/develop/benchmark/README.md) 提供的案例有小错误,漏写了`tgz`后缀 原文: ``` wget https://bj.bcebos.com/paddlehub/fastdeploy/MobileNetV1_x0_25_infer.tgz tar -xvf MobileNetV1_x0_25_infer ``` 应该为: ``` wget https://bj.bcebos.com/paddlehub/fastdeploy/MobileNetV1_x0_25_infer.tgz tar -xvf MobileNetV1_x0_25_infer.tgz ```
请问现在能支持PPYOLOE+吗
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