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from typing import Dict, Any
import torch
import base64
from io import BytesIO
from model import Model
from PIL import Image
# set device
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
if device.type != 'cuda':
raise ValueError("need to run on GPU")
class EndpointHandler():
def __init__(self, path=""):
# load the optimized model
self.model = Model()
def __call__(self, data: Any) -> Any:
"""
Args:
data (:obj:):
includes the input data and the parameters for the inference.
Return:
A :obj:`dict`:. base64 encoded image
"""
inputs = data.pop("inputs", data)
image = Image.open(BytesIO(base64.b64decode(inputs['image'])))
# run inference pipeline
_, res = self.model.process_lineart(image)
# encoding image as base 64 is done by the default toolkit
return res
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