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import torch
from transformers import GLPNImageProcessor, GLPNForDepthEstimation
from image_resize import resize_img
def depth_detection(image, pad=16):
feature_extractor = GLPNImageProcessor.from_pretrained("vinvino02/glpn-nyu")
model = GLPNForDepthEstimation.from_pretrained("vinvino02/glpn-nyu")
new_img = resize_img(image)
inputs = feature_extractor(images=new_img, return_tensors="pt")
with torch.no_grad():
outputs = model(**inputs)
predicted_depth = outputs.predicted_depth
output = predicted_depth.squeeze().cpu().numpy() * 1000.0
output = output[pad:-pad, pad:-pad]
new_image = new_img.crop((pad, pad, new_img.width - pad, new_img.height - pad))
return new_image,output
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