Update README.md

README.md

@@ -90,14 +90,62 @@ Users should be informed about the model's limitations and potential biases. Fur
 
  Load model and perform prediction:
 
+
+### How to use
+
+- Install [yolov5](https://github.com/fcakyon/yolov5-pip):
+
+```bash
+pip install -U yolov5
 ```
+
+- Load model and perform prediction:
+
+```python
 import yolov5
 
+# load model
+model = yolov5.load('foduucom/object_distance_estimation')
+  
+# set model parameters
+model.conf = 0.25  # NMS confidence threshold
+model.iou = 0.45  # NMS IoU threshold
+model.agnostic = False  # NMS class-agnostic
+model.multi_label = False  # NMS multiple labels per box
+model.max_det = 1000  # maximum number of detections per image
+
+# set image
+img = path
+
+# perform inference
+results = model(img, size=640)
+
+# inference with test time augmentation
+results = model(img, 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()
+
+# save results into "results/" folder
+results.save(save_dir='results/')
+```
+
+- Finetune the model on your custom dataset:
+
+```bash
+yolov5 train --data dataset.yaml --img 640 --batch -1 --weights foduucom/object_distance_estimation --epochs 10
+```
 
 
 
 
-'''### Compute Infrastructure
+### Compute Infrastructure
 
 #### Hardware