from transformers_js import import_transformers_js, as_url import gradio as gr transformers = await import_transformers_js() pipeline = transformers.pipeline depth_estimator = await pipeline('depth-estimation', 'Xenova/depth-anything-large-hf'); async def estimate(input_image): output = await depth_estimator(as_url(input_image)) # print("blob:", output.depth.toBlob()) return output demo = gr.Interface( fn=estimate, inputs=[ gr.Image(type="filepath") ], outputs=[ gr.JSON(), ], examples=[ ["bread_small.png"] ] ) demo.launch() transformers_js_py