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FastDeploy/examples/vision/detection/paddledetection
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English | 简体中文

PaddleDetection Model Deployment

Model Description

List of Supported Models

Now FastDeploy supports the deployment of the following models

Export Deployment Model

Before deployment, PaddleDetection needs to be exported into the deployment model. Refer to Export Models for more details.

Attention

  • Do not perform NMS removal when exporting the model
  • If you are running a native TensorRT backend (not a Paddle Inference backend), do not add the --trt parameter
  • Do not add the parameter fuse_normalize=True when exporting the model

Download Pre-trained Model

For developers' testing, models exported by PaddleDetection are provided below. Developers can download them directly.

The accuracy metric is from model descriptions in PaddleDetection. Refer to them for details.

Model Parameter Size Accuracy Note
picodet_l_320_coco_lcnet 23MB Box AP 42.6%
ppyoloe_crn_l_300e_coco 200MB Box AP 51.4%
ppyoloe_plus_crn_m_80e_coco 83.3MB Box AP 49.8%
ppyolo_r50vd_dcn_1x_coco 180MB Box AP 44.8% TensorRT not supported yet
ppyolov2_r101vd_dcn_365e_coco 282MB Box AP 49.7% TensorRT not supported yet
yolov3_darknet53_270e_coco 237MB Box AP 39.1%
yolox_s_300e_coco 35MB Box AP 40.4%
faster_rcnn_r50_vd_fpn_2x_coco 160MB Box AP 40.8% TensorRT not supported yet
mask_rcnn_r50_1x_coco 128M Box AP 37.4%, Mask AP 32.8% TensorRT、ORT not supported yet
ssd_mobilenet_v1_300_120e_voc 24.9M Box AP 73.8% TensorRT、ORT not supported yet
ssd_vgg16_300_240e_voc 106.5M Box AP 77.8% TensorRT、ORT not supported yet
ssdlite_mobilenet_v1_300_coco 29.1M TensorRT、ORT not supported yet
rtmdet_l_300e_coco 224M Box AP 51.2%
rtmdet_s_300e_coco 42M Box AP 44.5%
yolov5_l_300e_coco 183M Box AP 48.9%
yolov5_s_300e_coco 31M Box AP 37.6%
yolov6_l_300e_coco 229M Box AP 51.0%
yolov6_s_400e_coco 68M Box AP 43.4%
yolov7_l_300e_coco 145M Box AP 51.0%
yolov7_x_300e_coco 277M Box AP 53.0%

Detailed Deployment Documents