Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+from PIL import Image
+
+# Load the pipeline
+pipe = pipeline(
+    "image-classification",
+    model="mariamhsein16/FacialExpressionDetection"
+)
+
+# Prediction function
+def predict_expression(image):
+    if image is None:
+        return "Please upload an image."
+
+    results = pipe(image)
+
+    # Format results nicely
+    formatted_results = []
+    for r in results:
+        label = r["label"]
+        score = round(r["score"] * 100, 2)
+        formatted_results.append(f"{label}: {score}%")
+
+    return "\n".join(formatted_results)
+
+# Gradio UI
+with gr.Blocks(title="Facial Expression Detection") as demo:
+    gr.Markdown("## 😊 Facial Expression Detection")
+    gr.Markdown("Upload a face image to detect the facial expression.")
+
+    with gr.Row():
+        image_input = gr.Image(type="pil", label="Upload Image")
+        output_text = gr.Textbox(label="Predictions")
+
+    submit_btn = gr.Button("Detect Expression")
+
+    submit_btn.click(
+        fn=predict_expression,
+        inputs=image_input,
+        outputs=output_text
+    )
+
+# Launch app
+demo.launch()