BertChristiaens commited on
Commit
b12d9cc
1 Parent(s): 41e92f0
Files changed (1) hide show
  1. models.py +5 -4
models.py CHANGED
@@ -201,18 +201,18 @@ def make_image_controlnet(image: np.ndarray,
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  flush()
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  image = Image.fromarray(image).convert("RGB")
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- controlnet_conditioning_image = Image.fromarray(controlnet_conditioning_image).convert("RGB").filter(ImageFilter.GaussianBlur(radius = 9))
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  mask_image = Image.fromarray((mask_image * 255).astype(np.uint8)).convert("RGB")
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  mask_image_postproc = convolution(mask_image)
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- st.success(f"{pipe.queue_size} images in the queue, can take up to {(pipe.queue_size)+1 * 10} seconds")
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  generated_image = pipe(
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  prompt=positive_prompt,
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  negative_prompt=negative_prompt,
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  num_inference_steps=20,
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- strength=[1.00, ],
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- guidance_scale=[7.0],
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  generator=[torch.Generator(device="cuda").manual_seed(seed)],
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  image=image,
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  mask_image=mask_image,
@@ -240,6 +240,7 @@ def make_inpainting(positive_prompt: str,
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  pipe = get_inpainting_pipeline()
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  flush()
 
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  image_ = pipe(image=image,
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  mask_image=Image.fromarray((mask_image * 255).astype(np.uint8)),
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  prompt=positive_prompt,
 
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  flush()
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  image = Image.fromarray(image).convert("RGB")
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+ controlnet_conditioning_image = Image.fromarray(controlnet_conditioning_image).convert("RGB")#.filter(ImageFilter.GaussianBlur(radius = 9))
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  mask_image = Image.fromarray((mask_image * 255).astype(np.uint8)).convert("RGB")
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  mask_image_postproc = convolution(mask_image)
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+ st.success(f"{pipe.queue_size} images in the queue, can take up to {(pipe.queue_size+1) * 10} seconds")
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  generated_image = pipe(
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  prompt=positive_prompt,
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  negative_prompt=negative_prompt,
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  num_inference_steps=20,
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+ strength=1.00,
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+ guidance_scale=7.0,
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  generator=[torch.Generator(device="cuda").manual_seed(seed)],
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  image=image,
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  mask_image=mask_image,
 
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  pipe = get_inpainting_pipeline()
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  flush()
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+ st.success(f"{pipe.queue_size} images in the queue, can take up to {(pipe.queue_size+1) * 10} seconds")
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  image_ = pipe(image=image,
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  mask_image=Image.fromarray((mask_image * 255).astype(np.uint8)),
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  prompt=positive_prompt,