Create app.py

app.py

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+import gradio as gr
+from fastai.vision.all import *
+
+# Load your trained model (replace with your model path)
+model_path = "path_to_your_trained_model.pkl"
+model = load_learner(model_path)
+
+# Emotion prediction function with percentage
+def predict_emotion(image):
+    # Perform prediction using your trained model
+    pred_class, pred_idx, outputs = model.predict(image)
+    
+    # Get the probability (confidence) of the prediction
+    confidence = outputs[pred_idx] * 100  # Convert to percentage
+    
+    return f"Predicted Emotion: {pred_class}", f"Confidence: {confidence:.2f}%"
+
+# Create the Gradio interface
+with gr.Blocks(theme='gstaff/xkcd') as demo:
+    gr.Markdown("# Emotion Recognition Classifier")
+    
+    with gr.Row():
+        with gr.Column():
+            # Image input widget
+            img_input = gr.Image(type="pil", label="Upload an image")
+            
+            # Text output widgets for emotion prediction and confidence percentage
+            label_output = gr.Textbox(label="Predicted Emotion")
+            confidence_output = gr.Textbox(label="Confidence Percentage")
+            
+            # Button to trigger emotion classification
+            img_input.upload(predict_emotion, img_input, [label_output, confidence_output])
+    
+    # Run the app
+    demo.launch(share=True)