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| import numpy | |
| import gradio | |
| import huggingface_hub | |
| import json | |
| class NumpyArrayEncoder(json.JSONEncoder): | |
| def default(self, obj): | |
| if isinstance(obj, numpy.ndarray): | |
| return obj.tolist() | |
| return JSONEncoder.default(self, obj) | |
| analysis_network = huggingface_hub.from_pretrained_keras("cmudrc/wave-energy-analysis") | |
| synthesis_network = huggingface_hub.from_pretrained_keras("cmudrc/wave-energy-synthesis") | |
| with gradio.Blocks() as demo: | |
| geometry = gradio.Textbox(label="geometry") | |
| spectrum = gradio.Textbox(label="spectrum") | |
| analyze_it = gradio.Button("Analyze") | |
| synthesize_it = gradio.Button("Synthesize") | |
| analyze_it.click(fn=lambda x: json.dumps(analysis_network.predict(numpy.asarray([json.loads(x)])), cls=NumpyArrayEncoder), inputs=[geometry], outputs=[spectrum], api_name="analyze") | |
| synthesize_it.click(fn=lambda x: json.dumps(synthesis_network.predict(numpy.asarray(json.loads(x))), cls=NumpyArrayEncoder), inputs=[spectrum], outputs=[geometry], api_name="synthesize") | |
| demo.launch(debug=True) |