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45 lines
1.2 KiB
45 lines
1.2 KiB
from min_dalle import MinDalle |
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import tempfile |
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from typing import Iterator |
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from cog import BasePredictor, Path, Input |
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class Predictor(BasePredictor): |
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def setup(self): |
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self.model = MinDalle(is_mega=True) |
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def predict( |
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self, |
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text: str = Input( |
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description='Text', |
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default='Dali painting of WALL·E' |
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), |
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grid_size: int = Input( |
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description='Size of the image grid', |
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ge=1, |
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le=5, |
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default=4 |
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), |
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seed: int = Input( |
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description='Set the seed to a positive number for reproducible results', |
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default=-1 |
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), |
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log2_intermediate_image_count: int = Input( |
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description='Set the log2 number of intermediate images to show', |
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ge=0, |
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le=4, |
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default=3 |
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), |
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) -> Iterator[Path]: |
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image_stream = self.model.generate_image_stream( |
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text, |
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seed, |
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grid_size=grid_size, |
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log2_mid_count=log2_intermediate_image_count, |
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is_verbose=True |
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) |
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for image in image_stream: |
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out_path = Path(tempfile.mkdtemp()) / 'output.jpg' |
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image.save(str(out_path)) |
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yield out_path |