global model

app.py

@@ -26,7 +26,7 @@ def convert_result(pred, class_names=["Real", "Fake"]):
 	assert len(class_names) == len(preds), "Class / Prediction should have the same length"
 	return {n: p for n, p in zip(class_names, preds)}
 
-def predict_fn(model, video, meta):
+def predict_fn(video, meta):
 	start = time.time()
 	prediction = predict_on_video(face_extractor=meta["face_extractor"],
 							   video_path=video,
@@ -75,7 +75,7 @@ if __name__ == '__main__':
 """
 # Create the Gradio demo
 demo = gr.Interface(fn=predict_fn, # mapping function from input to output
-					inputs=[model, gr.Video(), meta],
+					inputs=[gr.Video(), meta],
 					outputs=[gr.Label(num_top_classes=2, label="Predictions"), # what are the outputs?
 							 gr.Number(label="Prediction time (s)")], # our fn has two outputs, therefore we have two outputs
 					examples=example_list,