yolov9pip
Project description
Yolov9-Pip: Packaged version of the Yolov9 repository
This repo is a packaged version of the Yolov9 model.
⭐ Installation
pip install yolov9pip
🌠 Yolov9 Inference
import yolov9
# load pretrained or custom model
model = yolov9.load(
"yolov9-c.pt",
device="cpu",
)
# set model parameters
model.conf = 0.25 # NMS confidence threshold
model.iou = 0.45 # NMS IoU threshold
model.classes = None # (optional list) filter by class
# set image
imgs = "data/zidane.jpg"
# perform inference
results = model(imgs)
# inference with larger input size and test time augmentation
results = model(img, size=640)
# parse results
predictions = results.pred[0]
boxes = predictions[:, :4] # x1, y1, x2, y2
scores = predictions[:, 4]
categories = predictions[:, 5]
# show detection bounding boxes on image
results.show()
😍 Contributing
pip install -r dev-requirements.txt
pre-commit install
pre-commit run --all-files
🤗 Citation
@article{wang2024yolov9,
title={{YOLOv9}: Learning What You Want to Learn Using Programmable Gradient Information},
author={Wang, Chien-Yao and Liao, Hong-Yuan Mark},
booktitle={arXiv preprint arXiv:2402.13616},
year={2024}
}
Acknowledgement
A part of the code is borrowed from Yolov5-pip. Many thanks for their wonderful works.
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