Create app.py

app.py

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+import torch
+import gradio as gr
+from PIL import Image
+import requests
+
+# Download the model from Hugging Face model repo
+model_path = "best.pt"
+if not os.path.exists(model_path):
+    url = "https://huggingface.co/AlaaElsayed/YoloModel/resolve/main/best.pt"
+    r = requests.get(url)
+    with open(model_path, 'wb') as f:
+        f.write(r.content)
+
+# Load the YOLOv5 model
+model = torch.hub.load('ultralytics/yolov5', 'custom', path=model_path, source='local')
+
+# Define the detection function
+def detect(image):
+    results = model(image)
+    return Image.fromarray(results.render()[0])  # Convert to PIL for Gradio
+
+# Create Gradio interface
+demo = gr.Interface(
+    fn=detect,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Image(type="pil"),
+    title="YOLOv5 Object Detector",
+    description="Upload an image and let YOLOv5 detect objects using your custom model!"
+)
+
+demo.launch()