Update README.md

README.md

@@ -25,3 +25,57 @@ Two sources were used for training:
 
 ## Usage
 
+The model can be used as any `ultralytics` model.
+
+The model needs to be downloaded. This is sufficient to perform once.
+
+```
+import os
+import requests
+from ultralytics import YOLO
+
+def download_detector(
+    url="https://huggingface.co/BVRA/TurtleDetector/resolve/main/turtle_detector.pt",
+    path_model="models/turtle_detector.pt",
+    force=False,
+):
+    if not os.path.exists(path_model) or force:
+        os.makedirs(os.path.dirname(path_model), exist_ok=True)
+        r = requests.get(url, timeout=60)
+        r.raise_for_status()
+        with open(path_model, "wb") as f:
+            f.write(r.content)
+
+path_model = "models/turtle_detector.pt"
+download_detector(path_model=path_model)
+```
+
+Once this is done, load the model.
+
+```
+from ultralytics import YOLO
+
+path_model = "models/turtle_detector.pt"
+model = YOLO(path_model)
+```
+
+Finally, download an image (or use yours) and run the prediction.
+
+```
+import requests
+from io import BytesIO
+from PIL import Image
+
+def load_image(url):
+    r = requests.get(url, timeout=30)
+    r.raise_for_status()
+    return Image.open(BytesIO(r.content)).convert("RGB")
+
+img_url = "https://huggingface.co/BVRA/TurtleDetector/resolve/main/images/321595639_581630651.jpg"
+img = load_image(img_url)
+
+result = model.predict(img, verbose=False, save=False, show=False)[0]
+img_annotated = result.plot()[:, :, ::-1]
+
+Image.fromarray(img_annotated)
+```