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An Extension for Automatic1111 Webui that increases/decreases the details of images

License: MIT License

Python 100.00%

stable-diffusion-webui stable-diffusion-webui-plugin

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sd-webui-resharpen's Issues

Path Error in resharpen.py with StableDiffusionWebUI Forge – Suggestion for init.py Placement

Dear Haoming02,

Thank you for creating the "sharpness" control extension for StableDiffusionWebUI. I tried using this extension with StableDiffusionWebUI Forge and encountered a path error in resharpen.py.

I was wondering if placing the init.py file in the specified locations might resolve the error, reducing the likelihood of others encountering the same issue. The specified locations are sd-webui-resharpen and scripts.

Your consideration would be greatly appreciated. Thank you in advance.

Resharpen seems to stop batching

When I increase my batch count from 1 in txt2img when enabling resharpen I get "HINT: We don't support broadcasting, please use expand yourself before calling memory_efficient_attention". I only seem to get this with this extension enabled.
Tell a lie something else is causing this maybe just coincidence it was when I installed Resharpen.

Use via API?

Hi,
First, This is one of absolute best extensions i've discovered so far!
Congratulation on achieving this.

Now, is it possible to use this extension via the API or is it only usable through the WebUi?

[Feature request] Additional parameters for adding noise

First steps for initial rendering and latent hires fix are really sensitive for noise injection.
Lasts steps could be left "sane" to make some "housecleaning"
Could you please add parameters such as "start step" and "stop step" separately for initial and hires.fix?

Their behavior might be the next:
if value is floating (0.5 as an example) it means that its real value is 0.5*NumberOfSteps
if value is integer (2 as an example) it meaning is literal, so 2 steps

'NoneType' object is not iterable when changing resolution

The extension works as expected until I change the resolution to anything other than 1024x1024. It happens even with all other extensions disabled. Here is the error:

Begin to load 1 model
Reuse 1 loaded models
[Memory Management] Current Free GPU Memory (MB) =  16281.34912109375
[Memory Management] Model Memory (MB) =  0.0
[Memory Management] Minimal Inference Memory (MB) =  1024.0
[Memory Management] Estimated Remaining GPU Memory (MB) =  15257.34912109375
Moving model(s) has taken 0.03 seconds
  0%|                                                                                                                                                                                                                | 0/28 [00:00<?, ?it/s]
Traceback (most recent call last):
  File "N:\AI\stable-diffusion-webui-forge\modules_forge\main_thread.py", line 37, in loop
    task.work()
  File "N:\AI\stable-diffusion-webui-forge\modules_forge\main_thread.py", line 26, in work
    self.result = self.func(*self.args, **self.kwargs)
  File "N:\AI\stable-diffusion-webui-forge\modules\txt2img.py", line 111, in txt2img_function
    processed = processing.process_images(p)
  File "N:\AI\stable-diffusion-webui-forge\modules\processing.py", line 752, in process_images
    res = process_images_inner(p)
  File "N:\AI\stable-diffusion-webui-forge\modules\processing.py", line 922, in process_images_inner
    samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)
  File "N:\AI\stable-diffusion-webui-forge\modules\processing.py", line 1275, in sample
    samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
  File "N:\AI\stable-diffusion-webui-forge\modules\sd_samplers_kdiffusion.py", line 251, in sample
    samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
  File "N:\AI\stable-diffusion-webui-forge\modules\sd_samplers_common.py", line 263, in launch_sampling
    return func()
  File "N:\AI\stable-diffusion-webui-forge\modules\sd_samplers_kdiffusion.py", line 251, in <lambda>
    samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
  File "N:\AI\stable-diffusion-webui-forge\venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "N:\AI\stable-diffusion-webui-forge\repositories\k-diffusion\k_diffusion\sampling.py", line 145, in sample_euler_ancestral
    denoised = model(x, sigmas[i] * s_in, **extra_args)
  File "N:\AI\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "N:\AI\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "N:\AI\stable-diffusion-webui-forge\modules\sd_samplers_cfg_denoiser.py", line 182, in forward
    denoised = forge_sampler.forge_sample(self, denoiser_params=denoiser_params,
  File "N:\AI\stable-diffusion-webui-forge\modules_forge\forge_sampler.py", line 88, in forge_sample
    denoised = sampling_function(model, x, timestep, uncond, cond, cond_scale, model_options, seed)
  File "N:\AI\stable-diffusion-webui-forge\ldm_patched\modules\samplers.py", line 289, in sampling_function
    cond_pred, uncond_pred = calc_cond_uncond_batch(model, cond, uncond_, x, timestep, model_options)
  File "N:\AI\stable-diffusion-webui-forge\ldm_patched\modules\samplers.py", line 258, in calc_cond_uncond_batch
    output = model.apply_model(input_x, timestep_, **c).chunk(batch_chunks)
  File "N:\AI\stable-diffusion-webui-forge\ldm_patched\modules\model_base.py", line 90, in apply_model
    model_output = self.diffusion_model(xc, t, context=context, control=control, transformer_options=transformer_options, **extra_conds).float()
  File "N:\AI\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "N:\AI\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "N:\AI\stable-diffusion-webui-forge\ldm_patched\ldm\modules\diffusionmodules\openaimodel.py", line 867, in forward
    h = forward_timestep_embed(module, h, emb, context, transformer_options, time_context=time_context, num_video_frames=num_video_frames, image_only_indicator=image_only_indicator)
  File "N:\AI\stable-diffusion-webui-forge\ldm_patched\ldm\modules\diffusionmodules\openaimodel.py", line 55, in forward_timestep_embed
    x = layer(x, context, transformer_options)
  File "N:\AI\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "N:\AI\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "N:\AI\stable-diffusion-webui-forge\ldm_patched\ldm\modules\attention.py", line 620, in forward
    x = block(x, context=context[i], transformer_options=transformer_options)
  File "N:\AI\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "N:\AI\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "N:\AI\stable-diffusion-webui-forge\ldm_patched\ldm\modules\attention.py", line 447, in forward
    return checkpoint(self._forward, (x, context, transformer_options), self.parameters(), self.checkpoint)
  File "N:\AI\stable-diffusion-webui-forge\ldm_patched\ldm\modules\diffusionmodules\util.py", line 194, in checkpoint
    return func(*inputs)
  File "N:\AI\stable-diffusion-webui-forge\ldm_patched\ldm\modules\attention.py", line 552, in _forward
    n = p(n, extra_options)
  File "N:\AI\stable-diffusion-webui-forge\extensions\sd-forge-couple\scripts\attention_couple.py", line 67, in attn2_output_patch
    mask_downsample = get_mask(
  File "N:\AI\stable-diffusion-webui-forge\extensions\sd-forge-couple\scripts\attention_masks.py", line 27, in get_mask
    mask_downsample = mask_downsample.view(num_conds, num_tokens, 1).repeat_interleave(
RuntimeError: shape '[3, 4160, 1]' is invalid for input of size 768
shape '[3, 4160, 1]' is invalid for input of size 768
*** Error completing request
*** Arguments: ('task(vqkdx3uwi27upfo)', <gradio.routes.Request object at 0x0000020E10B9F940>, '1girl\n1boy', '', [], 28, 'Euler a', 1, 1, 7, 1024, 1032, False, 0.45, 1.3, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', '', '', [], 0, False, '', 0.8, 2797109398, False, -1, 0, 0, 0, 0.0, 4, 512, 512, True, 'None', 'None', 0, True, 'Horizontal', 'None', '', 'Basic', [['0:0.5', '0.0:1.0', '1.0'], ['0.5:1.0', '0.0:1.0', '1.0']], False, False, 'positive', 'comma', 0, False, False, 'start', '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, False, False, False, 0, False) {}
    Traceback (most recent call last):
      File "N:\AI\stable-diffusion-webui-forge\modules\call_queue.py", line 57, in f
        res = list(func(*args, **kwargs))
    TypeError: 'NoneType' object is not iterable

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