Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+from PIL import Image
+
+# Load the model from Hugging Face Hub
+detector = pipeline(
+    task="object-detection",
+    model="jayanthapoojary1989/rsna-pneumonia-yolov8s",  # Change model name if you want to use another
+    threshold=0.5  # Set your detection confidence threshold
+)
+
+def detect_objects(image):
+    # Run object detection
+    results = detector(image)
+    # Draw bounding boxes
+    image = image.copy()
+    for result in results:
+        box = result['box']
+        label = result['label']
+        score = result['score']
+        draw = ImageDraw.Draw(image)
+        draw.rectangle([box['xmin'], box['ymin'], box['xmax'], box['ymax']], outline="red", width=3)
+        draw.text((box['xmin'], box['ymin'] - 10), f"{label} ({score:.2f})", fill="red")
+    return image
+
+# Create Gradio Interface
+interface = gr.Interface(
+    fn=detect_objects,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Image(type="pil"),
+    title="Pneumonia Detection on Chest X-rays",
+    description="Upload a chest X-ray image. The model will predict bounding boxes for pneumonia regions."
+)
+
+# Launch the app
+if __name__ == "__main__":
+    interface.launch()