Update README.md

README.md

@@ -1,5 +1,11 @@
 ---
 license: gpl
+pipeline_tag: object-detection
+tags:
+  - ultralytics
+  - yolo
+  - yolov10
+  - object-detection
 ---
 # Rock Paper Scissors Object Detection Model
 
@@ -21,3 +27,40 @@ The model trained on 100 images found online.  No augmentation of the images wer
 | rock     | 69      | 84        | 0.875  | 0.835 | 0.924 | 0.728    |
 | paper    | 56      | 65        | 0.899  | 0.815 | 0.909 | 0.721    |
 | scissors | 88      | 111       | 0.976  | 0.736 | 0.943 | 0.755    |
+
+## How to Use
+
+```
+pip install ultralytics
+pip install huggingface_hub
+```
+
+```
+from ultralytics import YOLO
+from huggingface_hub import hf_hub_download
+from matplotlib import pyplot as plt
+
+# Load the weights from our repository
+model_path = hf_hub_download(
+    local_dir=".",
+    repo_id="fairportrobotics/rock-paper-scissors",
+    filename="model.pt"
+)
+model = YOLO(model_path)
+
+# Load a test image
+sample_path = hf_hub_download(
+    local_dir=".",
+    repo_id="fairportrobotics/rock-paper-scissors",
+    filename="sample.jpg"
+)
+
+# Do the predictions
+res = model.predict(source=sample_path, project='.',name='detected', exist_ok=True, save=True, show=False, show_labels=True, show_conf=True, conf=0.5, )
+
+plt.figure(figsize=(15,10))
+plt.imshow(plt.imread('detected/sample.jpg'))
+plt.show()
+```
+
+As you can see the model isn't perfect ;)