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from typing import Any, Dict, List |
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import base64 |
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import io |
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import tempfile |
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from PIL import Image |
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import logging |
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def process_image(img): |
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crash_img = img.crop((0,0, 200, 200)) |
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if crash_img: |
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img_io = io.BytesIO() |
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crash_img.save(img_io, "PNG") |
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img_io.seek(0) |
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return {"data": base64.b64encode(img_io.read()).decode("utf-8"), "mime_type": "image/png"} |
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else: |
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return {"error": "No crash diagram detected"} |
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class EndpointHandler: |
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def __init__(self, path: str = ""): |
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"""Initialize the endpoint handler. |
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Args: |
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path: Path to the model artifacts |
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""" |
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logging.warning("initialized") |
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pass |
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def __call__(self, data: Any) -> List[List[Dict[str, str]]]: |
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logging.warning("inside __call__") |
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logging.warning(f"data keys {data.keys()}") |
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inputs = data.pop("inputs", data) |
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logging.warning(f"inputs keys {inputs.keys()}") |
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imagedata = inputs.pop("imagedata", inputs) |
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if isinstance(imagedata, str): |
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logging.warning("decoding pdfdata") |
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image_bytes = base64.b64decode(imagedata) |
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img = Image.open(io.BytesIO(image_bytes)) |
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logging.warning(f"image {str(img)}") |
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return process_image(img) |
