kadirnar / Minimal-Yolov6

YOLOv6: Single-stage Object Detection

YOLOv6: Single-stage Object Detection

Installation

git clone --recurse-submodules https://github.com/kadirnar/YOLOv6.git
cd YOLOv6
pip install -r requirements.txt

Inference

detection_model = Yolov6(
    model_path="yolov6s.pt",
    source="assert/highway.jpg",
    img_size=1280,
    conf_thres=0.3,
    device="cpu",
)
detection_model.inference()

Training

Single GPU

python YOLOv6/tools/train.py --batch 32 --conf configs/yolov6s.py --data data/coco.yaml --device 0
                                         configs/yolov6n.py

Multi GPUs (DDP mode recommended)

python -m torch.distributed.launch --nproc_per_node 8 YOLOv6/tools/train.py --batch 256 --conf configs/yolov6s.py --data data/coco.yaml --device 0,1,2,3,4,5,6,7
                                                                                        configs/yolov6n.py

• conf: select config file to specify network/optimizer/hyperparameters
• data: prepare COCO dataset and specify dataset paths in data.yaml

Evaluation

Reproduce mAP on COCO val2017 dataset

python YOLOv6/tools/eval.py --data data/coco.yaml  --batch 32 --weights yolov6s.pt --task val
                                                                 yolov6n.pt

Deployment

• ONNX
• OpenVINO

Tutorials

• Train custom data
• Test speed

Benchmark

Model	Size	mAPval 0.5:0.95	SpeedV100 fp16 b32 (ms)	SpeedV100 fp32 b32 (ms)	SpeedT4 trt fp16 b1 (fps)	SpeedT4 trt fp16 b32 (fps)	Params (M)	Flops (G)
YOLOv6-n	416 640	30.8 35.0	0.3 0.5	0.4 0.7	1100 788	2716 1242	4.3 4.3	4.7 11.1
YOLOv6-tiny	640	41.3	0.9	1.5	425	602	15.0	36.7
YOLOv6-s	640	43.1	1.0	1.7	373	520	17.2	44.2

• Comparisons of the mAP and speed of different object detectors are tested on COCO val2017 dataset.
• Refer to Test speed tutorial to reproduce the speed results of YOLOv6.
• Params and Flops of YOLOv6 are estimated on deployed model.
• Speed results of other methods are tested in our environment using official codebase and model if not found from the corresponding official release.