| import gradio as gr | |
| from PIL import Image | |
| def predict(value: Image.Image) -> str: | |
| return "Prediction!" | |
| with gr.Blocks() as demo: | |
| with gr.Row(): | |
| with gr.Column(): | |
| input_img = gr.Image(label="Input", sources="webcam") | |
| with gr.Column(): | |
| output_lbl = gr.Label(value="Output", label="Expression Prediction") | |
| input_img.stream(fn=predict, inputs=[input_img], outputs=[output_lbl], time_limit=15, stream_every=0.1, concurrency_limit=30) | |
| if __name__ == "__main__": | |
| demo.launch() |