Update README.md

README.md

@@ -1,3 +1,63 @@
 ---
-license: apache-2.0
+license: gpl-3.0
+tags:
+  - object-detection
+  - computer-vision
+  - yolov9
+  - pypi
+datasets:
+  - detection-datasets/coco
 ---
+
+### Model Description
+[YOLOv9: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors](https://arxiv.org/abs/2402.13616)
+
+[YOLOv9-Pip: Packaged version of the Yolov9 repository](https://github.com/kadirnar/yolov9-pip)
+
+[Paper Repo: Implementation of paper - YOLOv9](https://github.com/WongKinYiu/yolov9)
+
+### Installation
+```
+pip install yolov9pip
+```
+
+### Yolov7 Inference
+```python
+import yolov9
+
+# load pretrained or custom model
+model = yolov7.load('kadirnar/yolov7-v0.1', hf_model=True)
+
+# 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 = 'inference/images'
+
+# perform inference
+results = model(imgs)
+
+# inference with larger input size and test time augmentation
+results = model(img, size=640, augment=True)
+
+# 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()
+```
+
+### BibTeX Entry and Citation Info
+ ```
+@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}
+}
+```