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fix generate backend to generate "accurate" intermediate images

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- Closes #2784
- Closes #2775
This commit is contained in:
Lincoln Stein 2023-02-23 22:03:28 -05:00
parent 24407048a5
commit 7fb2da8741
1 changed files with 3 additions and 11 deletions
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14
ldm/invoke/generator/base.py
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@ -137,17 +137,9 @@ class Generator:
Given samples returned from a sampler, converts
it into a PIL Image
"""
x_samples = self.model.decode_first_stage(samples)
x_samples = torch.clamp((x_samples + 1.0) / 2.0, min=0.0, max=1.0)
if len(x_samples) != 1:
raise Exception(
f'>> expected to get a single image, but got {len(x_samples)}')
x_sample = 255.0 * rearrange(
x_samples[0].cpu().numpy(), 'c h w -> h w c'
)
return Image.fromarray(x_sample.astype(np.uint8))
# write an approximate RGB image from latent samples for a single step to PNG
with torch.inference_mode():
image = self.model.decode_latents(samples)
return self.model.numpy_to_pil(image)[0]
def repaste_and_color_correct(self, result: Image.Image, init_image: Image.Image, init_mask: Image.Image, mask_blur_radius: int = 8) -> Image.Image:
if init_image is None or init_mask is None: