dict Model

app.py

@@ -68,14 +68,14 @@ model = model_fn(model_dir)
 
 """
 if __name__ == '__main__':
-	video_path = "nlurbvsozt.mp4"
+	video_path = "examples/nlurbvsozt.mp4"
 	model = model_fn(model_dir)
-	a, b = predict_fn([model], video_path, meta)
+	a, b = predict_fn(model, video_path, meta)
 	print(a, b)
 """
 # Create the Gradio demo
 demo = gr.Interface(fn=predict_fn, # mapping function from input to output
-					inputs=[[model], gr.Video(autosize=True), meta],
+					inputs=[model, 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,

kernel_utils.py

@@ -333,7 +333,8 @@ def predict_on_video(face_extractor, video_path, batch_size, input_size, models,
                 # Make a prediction, then take the average.
                 with torch.no_grad():
                     preds = []
-                    for model in models:
+                    models_ = [models]
+                    for model in models_:
                         if device == 'cpu':
                             y_pred = model(x[:n])
                         else: