Upload 2 files

app.py

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+import gradio as gr
+from PIL import Image  # For image handling
+
+# Replace with paths or loading functions for your specific models
+def load_model_1():
+    # ... load your first model 
+    return model_1 
+
+def load_model_2():
+    # ... load your second model 
+    return model_2
+
+def load_model_3():
+    # ... load your third model 
+    return model_3
+
+def generate_caption(model, image):
+    # ... perform inference with your model 
+    return caption
+
+models = [load_model_1(), load_model_2(), load_model_3()]
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        image = gr.Image(label="Upload Chest X-ray")
+    with gr.Row():   
+        gr.Radio(["Model 1", "Model 2", "Model 3"], label="Select Model")
+    with gr.Row():
+        caption = gr.Textbox(label="Generated Caption") 
+
+    image.change(
+        fn=generate_caption, 
+        inputs=[image, gr.inputs.Radio], 
+        outputs=caption
+    )
+
+demo.launch() 

requirements.txt

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+gradio
+transformers  # Assuming you're using transformers models
+torchvision  # For image handling
+pillow