@@ -70,7 +70,7 @@ Alternatively, one can also perform inference using the classes:
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>>> inputs = image_processor(images=image, return_tensors="pt")
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>>> with torch.no_grad():
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... outputs = model(pixel_values)
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... outputs = model(inputs)
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>>> # interpolate to original size and visualize the prediction
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>>> ## ZoeDepth dynamically pads the input image. Thus we pass the original image size as argument
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