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import torch |
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from zoedepth.models.builder import build_model |
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from zoedepth.utils.config import get_config |
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class ZoeDepth: |
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def __init__(self, width=512, height=512): |
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conf = get_config("zoedepth_nk", "infer") |
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conf.img_size = [width, height] |
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self.model_zoe = build_model(conf) |
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self.DEVICE = "cuda" if torch.cuda.is_available() else "cpu" |
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self.zoe = self.model_zoe.to(self.DEVICE) |
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self.width = width |
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self.height = height |
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def predict(self, image): |
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self.zoe.core.prep.resizer._Resize__width = self.width |
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self.zoe.core.prep.resizer._Resize__height = self.height |
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depth_tensor = self.zoe.infer_pil(image, output_type="tensor") |
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return depth_tensor |
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def to(self, device): |
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self.DEVICE = device |
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self.zoe = self.model_zoe.to(device) |
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def save_raw_depth(self, depth, filepath): |
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depth.save(filepath, format='PNG', mode='I;16') |
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def delete(self): |
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del self.model_zoe |
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del self.zoe |