Metadata-Version: 2.1
Name: dethub
Version: 0.0.6
Summary: DetHub: Object Detection Model Hub
Home-page: https://github.com/goksenin-uav/dethub
Author: kadirnar
License: MIT
Keywords: machine-learning,deep-learning,ml,pytorch,vision,loss,image-classification,video-classification
Classifier: Development Status :: 5 - Production/Stable
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Education
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: tests
Provides-Extra: dev
License-File: LICENSE

<div align="center">
<h1>
DetHub: Object Detection Model Hub
</h1>
<img src="doc/torchvision.jpg" alt="Torchvision" width="800">
</div>

### Installation
```
git clone https://github.com/kadirnar/dethub
cd dethub
pip install -r requirements.txt
```
### Yolov5 Object Prediction and Visualization
```
run('yolov5', 'dethub/models/yolov5/yolov5n.pt', 'data/highway1.jpg')
```
<img src="doc/yolov5.jpg" alt="Yolov5" width="800">

### Torchvision Object Prediction and Visualization
```
run("torchvision", "dethub/models/torchvision/fasterrcnn_resnet50_fpn.pth", "data/highway1.jpg")
```
<img src="doc/torchvision.jpg" alt="Torchvision" width="800">

### TfHub Object Prediction and Visualization
```
run('tensorflow', 'https://tfhub.dev/tensorflow/efficientdet/d3/1', 'data/highway1.jpg')
```
<img src="doc/tensorflow.jpg" alt="TfHub" width="800">

### Contributing
Before opening a PR:
- Reformat with black and isort:
```bash
black . --config pyproject.toml
isort .
```
References:
- [SAHI](https://github.com/obss/sahi)
- [YOLOX](https://github.com/Megvii-BaseDetection/YOLOX)
- [Mcvarer](https://github.com/mcvarer/coco_toolkit)
