Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+from PIL import Image
+import requests
+from io import BytesIO
+
+# Load the emotion detection model from Hugging Face's Transformers library
+emotion_model = pipeline("image-classification", model="EleutherAI/emotion-english", device=0)
+
+# Define the function to make predictions on user-uploaded images
+def predict_emotion(image):
+    # Open the uploaded image
+    img = Image.open(BytesIO(image.encode("utf-8")))
+
+    # Make prediction using the emotion detection model
+    result = emotion_model(img)
+
+    # Extract the emotion label with the highest confidence
+    emotion = result[0]['label']
+
+    return f"Predicted emotion: {emotion}"
+
+# Define the Gradio interface
+iface = gr.Interface(
+    fn=predict_emotion,
+    inputs=gr.Image(),
+    outputs="text",
+    live=True,
+    interpretation="default",
+    title="Face Expression Predictor",
+    description="Upload an image and get the predicted face expression."
+)
+
+# Launch the Gradio app
+iface.launch()