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flux hires and refiner workflows

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This commit is contained in:
Vladimir Mandic
2024-09-08 10:48:22 -04:00
parent 787b321d57
commit 51e8567eec
7 changed files with 55 additions and 23 deletions
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modules/processing_args.py
+13
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@@ -34,6 +34,10 @@ def task_specific_kwargs(p, model):
'image': p.init_images,
'strength': p.denoising_strength,
}
if model.__class__.__name__ == 'FluxImg2ImgPipeline': # needs explicit width/height
p.width = 8 * math.ceil(p.init_images[0].width / 8)
p.height = 8 * math.ceil(p.init_images[0].height / 8)
task_args['width'], task_args['height'] = p.width, p.height
elif sd_models.get_diffusers_task(model) == sd_models.DiffusersTaskType.INSTRUCT and len(getattr(p, 'init_images', [])) > 0:
p.ops.append('instruct')
task_args = {
@@ -229,6 +233,15 @@ def set_pipeline_args(p, model, prompts: list, negative_prompts: list, prompts_2
args['cross_attention_kwargs'] = {}
args['cross_attention_kwargs'][k] = v
# handle missing resolution
if args.get('image', None) is not None and ('width' not in args or 'height' not in args):
if isinstance(args['image'], torch.Tensor) or isinstance(args['image'], np.ndarray):
args['width'] = 8 * args['image'].shape[-1]
args['height'] = 8 * args['image'].shape[-2]
else:
args['width'] = 8 * math.ceil(args['image'][0].width / 8)
args['height'] = 8 * math.ceil(args['image'][0].height / 8)
# handle implicit controlnet
if 'control_image' in possible and 'control_image' not in args and 'image' in args:
debug('Diffusers: set control image')