This repo using TensorRT to speed up yolov3 backbone and work with deep_sort torch. mainly run on Nvidia Jetson Nano but x64 may also works. haven't tried yet. note that it is a inference pipeline not for training model.
Thanks for ZQPei's great work. and also thanks to jkjung-avt for his tensorrt_demos, which give me a a lot to learn.
2020.4.12
Release yolov3-tiny416 inference
2020.4.11
first upload the project
Whole process time from read image to finished deepsort (include every img preprocess and postprocess)
Backbone | before TensorRT | TensorRT(detection + tracking) | FPS(detection + tracking) |
---|---|---|---|
Yolov3_416 | 750ms | 450ms | 1.5 ~ 2 |
Yolov3-tiny-416 | N/A | 100-150ms | 8 ~ 9 |
follow my step to set up everything
git clone xxxx
cd detector/YOLOv3/weight/
wget https://pjreddie.com/media/files/yolov3.weights
cd deep_sort/deep/checkpoint
# download ckpt.t7 from
https://drive.google.com/drive/folders/1xhG0kRH1EX5B9_Iz8gQJb7UNnn_riXi6 to this folder
cd detector/YOLOv3/nms
sh build.sh
firstly check the yolo weights under weights directory and just simply command like below to convert yolov3.weights file to onnx, and onnx will be yielded at the same dir ( ./weights/yolov3_416.onnx )
#if yolov3
python3 yolov3_to_onnx.py
#else yolov3_tiny
python3 yolov3_tiny_to_onnx.py
convert yolov3_416.onnx to tensorrt engine
#if yolov3
python3 onnx_to_tensorrt --onnx /path/to/yolov3_416.onnx --output_engine /path/to/yolov3_416.engine
#else yolov3_tiny
python3 onnx_to_tensorrt_tiny --onnx /path/to/yolov3_tiny_416.onnx --output_engine /path/to/yolov3_tiny_416.engine
Note: In onnx_to_tensorrt.py
, you can set max_workspace_size
= 1 << 30 in get_engine
function and delete builder.fp16_mode = True
if you are using x86 arch for better performance (both mAP and frames per second)
support video and webcam demo for now
support
Webcam demo - onboard camera, csi camera
#yolov3
python3 run_tracker.py
#yolov3 tiny
python3 run_tracker_tiny.py
Webcam demo - usb camera
#yolov3
python3 run_tracker.py --usb
#yolov3 tiny
python3 run_tracker_tiny.py --usb
Video demo
#yolov3
python3 run_tracker.py --file --filename your_test.mp4 --output_file ./output.mp4
#yolov3 tiny
python3 run_tracker_tiny.py --file --filename your_test.mp4 --output_file ./output.mp4
I had a hard time on saving video, now the VideoWriter works for me, but it might not work for you, issue me if you have any problem.