Update app.py

app.py

@@ -1,7 +1,41 @@
 import gradio as gr
+from huggingface_hub import hf_hub_download
+import torch
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Download the YOLOv5 model from Hugging Face
+model_path = hf_hub_download(repo_id="ultralytics/yolov5", filename="yolov5s.pt", revision="v7.0")
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+# Load the YOLOv5 model
+model = torch.hub.load('ultralytics/yolov5', 'custom', path=model_path)
+
+# Function to perform object detection
+def detect_objects(image):
+    # Perform inference with the YOLOv5 model
+    results = model(image)
+    
+    # Get the detected bounding boxes and labels
+    bboxes = results.xyxy[0].cpu().numpy()
+    labels = results.names
+
+    # Create a list of dictionaries for each detected object
+    detections = []
+    for bbox, label in zip(bboxes, labels):
+        x1, y1, x2, y2, conf, cls = bbox
+        detections.append({
+            'label': label,
+            'confidence': float(conf),
+            'x1': float(x1),
+            'y1': float(y1),
+            'x2': float(x2),
+            'y2': float(y2)
+        })
+
+    return detections
+
+# Create the Gradio app
+app = gr.Interface(detect_objects, gr.Image(type="pil"), "label", examples=[
+    ["example_image.jpg"]  # Replace with your own example image
+])
+
+# Run the app
+app.launch()