Gradio for Video

app.py

@@ -1,2 +1,27 @@
-import transformers
-import gradio
+import gradio as gr
+from transformers import pipeline
+
+video_model = pipeline("video-classification", model="Rohit1412/deepfakerohit2.0")
+
+def classify_video(video):
+    # Classify the uploaded video and return the results
+    predictions = video_model(video)
+    
+    # Create a dictionary of labels and their corresponding scores
+    result = {pred["label"]: pred["score"] for pred in predictions}
+    
+    # Return the result dictionary
+    return result
+
+# Create Gradio interface
+interface = gr.Interface(
+    fn=classify_video,
+    inputs=gr.Video(label="Upload Video"),
+    outputs=gr.Label(num_top_classes=3, label="Predictions"),
+    title="Video Classification App",
+    description="Upload a video to classify its content."
+)
+
+# Launch the interface
+if __name__ == "__main__":
+    interface.launch(debug=True)