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from typing import Dict, List, Any |
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from transformers import pipeline |
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import transformers |
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from PIL import Image |
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import base64 |
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from io import BytesIO |
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print('TRANSFORMERS VERSION') |
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print(transformers.__version__) |
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class EndpointHandler(): |
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def __init__(self, path=""): |
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self.pipe = pipeline(task="depth-estimation", model=path) |
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def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]: |
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base64_image = data.pop("inputs",data) |
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if base64_image is None: |
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raise ValueError("No image provided") |
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if base64_image.startswith('data:image/jpeg;base64,'): |
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base64_image = base64_image.replace('data:image/jpeg;base64,', '') |
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image_bytes = base64.b64decode(base64_image) |
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image = Image.open(BytesIO(image_bytes)) |
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depth = self.pipe(image)["depth"] |
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return depth |
