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from typing import List | |
import numpy as np | |
from PIL import Image | |
from PIL.Image import Image as PILImage | |
from .session_base import BaseSession | |
class SimpleSession(BaseSession): | |
def predict(self, img: PILImage) -> List[PILImage]: | |
ort_outs = self.inner_session.run( | |
None, | |
self.normalize( | |
img, (0.485, 0.456, 0.406), (0.229, 0.224, 0.225), (320, 320) | |
), | |
) | |
pred = ort_outs[0][:, 0, :, :] | |
ma = np.max(pred) | |
mi = np.min(pred) | |
pred = (pred - mi) / (ma - mi) | |
pred = np.squeeze(pred) | |
mask = Image.fromarray((pred * 255).astype("uint8"), mode="L") | |
mask = mask.resize(img.size, Image.LANCZOS) | |
return [mask] | |