min-dalle-test/replicate_predictor.py
2022-07-05 09:06:27 -04:00

52 lines
1.5 KiB
Python

from min_dalle import MinDalle
import tempfile
from typing import Iterator
from cog import BasePredictor, Path, Input
class ReplicatePredictor(BasePredictor):
def setup(self):
self.model = MinDalle(is_mega=True, is_reusable=True)
def predict(
self,
text: str = Input(
description='Text',
default='Dali painting of WALL·E'
),
grid_size: int = Input(
description='Size of the image grid',
ge=1,
le=4,
default=4
),
log2_intermediate_image_count: int = Input(
description='Number of images to show while running, each adds a slight delay',
ge=0,
le=4,
default=2
),
log2_supercondition_factor: int = Input(
description='Higher values result in better agreement with the text but a narrower variety of generated images',
ge=1,
le=6,
default=4
),
) -> Iterator[Path]:
seed = -1
image_stream = self.model.generate_image_stream(
text,
seed,
grid_size=grid_size,
log2_mid_count=log2_intermediate_image_count,
log2_supercondition_factor=log2_supercondition_factor,
is_verbose=True
)
iter = 0
path = Path(tempfile.mkdtemp())
for image in image_stream:
iter += 1
image_path = path / 'min-dalle-iter-{}.jpg'.format(iter)
image.save(str(image_path))
yield image_path