File size: 1,186 Bytes
f3abe3d 705a53a f3abe3d aa6b0c2 f3abe3d 705a53a f3abe3d 705a53a a520ae2 aa6b0c2 f3abe3d aa6b0c2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 |
from typing import Any, Dict, List
import base64
import io
import tempfile
from PIL import Image
import logging
def process_image(img):
crash_img = img.crop((0,0, 200, 200))
if crash_img:
img_io = io.BytesIO()
crash_img.save(img_io, "PNG")
img_io.seek(0)
# Return the cropped image as base64
return {"data": base64.b64encode(img_io.read()).decode("utf-8"), "mime_type": "image/png"}
else:
return {"error": "No crash diagram detected"}
class EndpointHandler:
def __init__(self, path: str = ""):
"""Initialize the endpoint handler.
Args:
path: Path to the model artifacts
"""
logging.warning("initialized")
pass
def __call__(self, data: Any) -> List[List[Dict[str, str]]]:
logging.warning("inside __call__")
inputs = data.pop("inputs", data)
imagedata = inputs.pop("imagedata", inputs)
if isinstance(imagedata, str):
logging.warning("decoding pdfdata")
image_bytes = base64.b64decode(imagedata)
img = Image.open(io.BytesIO(image_bytes))
return process_image(img) |