Update README.md

README.md

@@ -55,7 +55,27 @@ Additionally, I utilized code from Ultralytics to produce an object counting in
 
 I also utilized Ultralytics’ heatmap code to display a heatmap on the input video, showing which regions of the enclosure were most frequently occupied. I specifically focused the heatmap on the land zone, where the otters were spending most of their resting time. I manipulated the code to focus on the land zone, using pixel locations to create a custom region within the video.
 
-
+```python
+# Load the YOLOv11 model
+model = YOLO("yolo11n.pt")
+
+# Path to the dataset configuration YAML file
+dataset_config = '/content/Dataset/data.yaml'  # Path to the YAML file
+
+# Train the model
+results = model.train(
+    data=dataset_config,  # Path to the YAML file
+    epochs=100,
+    batch=64,  # Set a valid batch size (adjust as needed)
+    imgsz=640,  # Image size for training
+    plots=True,
+    patience=50,
+    conf=0.55,
+    iou=0.5
+)
+
+print(results)
+```
 ---
 # Model Assessment
 ### Here are the metrics I used to assess the accuracy and performance of my model during training.