Create app.py

app.py

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+import gradio as gr
+
+# Dummy model functions for each version
+def model_v1(image):
+    # Process the image with Model Version 1
+    return "Model V1: Detected disease - [Example Disease]"
+
+def model_v2(image):
+    # First validate image is a tomato leaf, then predict disease
+    return "Model V2: Detected disease after validation - [Example Disease]"
+
+def model_v3(image):
+    # Use an alternative architecture for prediction
+    return "Model V3: Detected disease with advanced analysis - [Example Disease]"
+
+# Main function to select the proper model based on the version choice
+def process_image(image, version):
+    if image is None:
+        return "No image provided."
+    if version == "Version 1":
+        return model_v1(image)
+    elif version == "Version 2":
+        return model_v2(image)
+    elif version == "Version 3":
+        return model_v3(image)
+    else:
+        return "Invalid version selected."
+
+# A helper to choose between uploaded image and camera image.
+def combine_images(uploaded, camera):
+    # Prioritize the camera image if provided
+    return camera if camera is not None else uploaded
+
+# Define the Gradio Blocks interface
+with gr.Blocks() as demo:
+    gr.Markdown("# FarmVi8ion – AI-powered Crop Monitoring")
+    gr.Markdown("An advanced system for detecting tomato diseases using AI models.")
+
+    with gr.Row():
+        # Sidebar column: version and theme selection
+        with gr.Column(scale=1):
+            version = gr.Radio(
+                ["Version 1", "Version 2", "Version 3"],
+                label="Select Model Version",
+                value="Version 1"
+            )
+            theme_choice = gr.Radio(
+                ["Light", "Dark"],
+                label="Select Theme",
+                value="Light"
+            )
+            gr.Markdown("Upload an image or use the camera preview below.")
+        
+        # Main column: image inputs and results
+        with gr.Column(scale=2):
+            # Image input for file upload
+            image_input = gr.Image(
+                source="upload",
+                tool="editor",
+                label="Upload Tomato Leaf Image",
+                type="pil"
+            )
+            # Camera input for real-time preview
+            camera_input = gr.Image(
+                source="camera",
+                label="Or use Camera Preview",
+                type="pil"
+            )
+            submit = gr.Button("Analyze")
+    
+    # Output textbox for model result
+    output = gr.Textbox(label="Result")
+    
+    # Combine image from either input before processing
+    combined_image = gr.Image(visible=False)
+    # When submit is clicked, combine the two images and then process the image.
+    submit.click(
+        fn=lambda uploaded, camera, ver: process_image(combine_images(uploaded, camera), ver),
+        inputs=[image_input, camera_input, version],
+        outputs=output
+    )
+    
+    # Note on theme selection (this is a placeholder: dynamic theme switching may require extra custom code)
+    gr.Markdown(
+        "Note: The theme toggle is currently a placeholder. "
+        "To apply light/dark themes dynamically, consider adding custom CSS or reloading the interface."
+    )
+
+demo.launch()