[1.1.449] Anyline Preprocessor & MistoLine SDXL model #2907

huchenlei · 2024-05-19T18:32:41Z

huchenlei
May 19, 2024
Collaborator

Anyline Preprocessor

Anyline is a ControlNet line preprocessor that accurately extracts object edges, image details, and textual content from most images. Users can input any type of image to quickly obtain line drawings with clear edges, sufficient detail preservation, and high fidelity text, which are then used as input for conditional generation in Stable Diffusion.

https://github.com/TheMistoAI/ComfyUI-Anyline

Misto Line SDXL Model

MistoLine: A Versatile and Robust SDXL-ControlNet Model for Adaptable Line Art Conditioning.

MistoLine is an SDXL-ControlNet model that can adapt to any type of line art input, demonstrating high accuracy and excellent stability. It can generate high-quality images (with a short side greater than 1024px) based on user-provided line art of various types, including hand-drawn sketches, different ControlNet line preprocessors, and model-generated outlines. MistoLine eliminates the need to select different ControlNet models for different line preprocessors, as it exhibits strong generalization capabilities across diverse line art conditions.

We developed MistoLine by employing a novel line preprocessing algorithm Anyline and retraining the ControlNet model based on the Unet of stabilityai/ stable-diffusion-xl-base-1.0, along with innovations in large model training engineering. MistoLine showcases superior performance across different types of line art inputs, surpassing existing ControlNet models in terms of detail restoration, prompt alignment, and stability, particularly in more complex scenarios.

https://github.com/TheMistoAI/MistoLine

How to Use

Download model from https://huggingface.co/TheMistoAI/MistoLine/tree/main and rename the model to mistoLine_softedge_sdxl_fp16.safetensors.

Limitations

As you can see in the generation result, there can be some unwanted detailed being captured by anyline preprocessor, such as incorrectly captured hair detail.

To deal with this, it is recommended to end controlnet guidance early. Here is the result by setting ending control step to 0.5:

Lowering controlnet weight does not help much on smoothing hair details. Also it allows generation of unwanted shapes.

Setting Control Mode to My Prompt is more important does remove unwanted hair details, but it also allows generation of unwanted shapes.

Generation Params:

1girl,, absurdres, highres, (masterpiece:1.2), (best quality, highest quality),
Negative prompt: (lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green
Steps: 30, Sampler: DPM++ 2M, Schedule type: Karras, CFG scale: 7, Seed: 2805618844, Size: 1024x1024, Model hash: aeb7e9e689, Model: juggernautXL_v8Rundiffusion, Clip skip: 2, ControlNet 0: "Module: softedge_anyline, Model: mistoLine_softedge_sdxl_fp16 [2583d73c], Weight: 1.0, Resize Mode: Crop and Resize, Processor Res: 1280, Threshold A: 2.0, Threshold B: 0.5, Guidance Start: 0.0, Guidance End: 1.0, Pixel Perfect: True, Control Mode: My prompt is more important", Version: v1.9.3-13-g8e355f08

CCpt5 · 2024-05-19T21:29:55Z

CCpt5
May 19, 2024

Excellent! Just tested with something photorealistic and the results are way better than w/ typical Canny.

Stopping it at ~50% definitely seems to produce the best results. Hope people pick up on that.

0 replies

Slartibart23 · 2024-05-20T18:54:22Z

Slartibart23
May 20, 2024

call me an idiot... but where do i found and the A1111/Forge softedge_anyline preprocessor?? :)

4 replies

huchenlei May 20, 2024
Collaborator Author

It is not supported in Forge yet. To use it, just update your sd-webui-controlnet extension to 1.1.449.

Slartibart23 May 20, 2024

ahh... thanx a lot :-)

dan4ik94 May 21, 2024

@Slartibart23 @huchenlei I'm already using mistoline with lineart & softedge in Forge, works fine. Would anyline be better?

TimeSurging May 26, 2024

Ask a question: Can you install the Anyline preprocessor in Forge? thanks.

don1138 · 2024-05-21T16:42:47Z

don1138
May 21, 2024

Is this a CUDA/PC-only feature?

I'm on an M1 Mac, and when I tried using the mistoline_rank256.safetensors model with softedge_anyline, I got this error:

Traceback (most recent call last):
  ...
  File "/Users/USER1/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/serialization.py", line 250, in validate_cuda_device
    raise RuntimeError('Attempting to deserialize object on a CUDA '
RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your storages to the CPU.

2 replies

huchenlei May 21, 2024
Collaborator Author

Can you file an issue with full stacktrace? thanks!

From the current stacktrace, I am not sure whether it is the TEED model has issue loading or ControlNet model.

don1138 May 30, 2024

In further testing, I found that these preprocessors throw errors:

softedge_anyline
softedge_teed

while these work correctly, with no errors:

softedge_pidinet
softedge_pidisafe
softedge_hedsafe
softedge_hed

This may invalidate this as an issue, but In any case, here's the extended info as requested.

I'm running ControlNet v1.1.4491

A111:

version: v1.9.3-2-gca57a324
python: 3.10.14
torch: 2.4.0.dev20240523
xformers: N/A
gradio: 3.41.2

Here's the output from testing it with Run Preprocessor (the explosion icon):

2024-05-30 10:39:21,080 - ControlNet - INFO - Preview Resolution = 1280
Traceback (most recent call last):
  File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/gradio/routes.py", line 488, in run_predict
    output = await app.get_blocks().process_api(
  File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/gradio/blocks.py", line 1431, in process_api
    result = await self.call_function(
  File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/gradio/blocks.py", line 1103, in call_function
    prediction = await anyio.to_thread.run_sync(
  File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/anyio/to_thread.py", line 33, in run_sync
    return await get_asynclib().run_sync_in_worker_thread(
  File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 877, in run_sync_in_worker_thread
    return await future
  File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 807, in run
    result = context.run(func, *args)
  File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/gradio/utils.py", line 707, in wrapper
    response = f(*args, **kwargs)
  File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/scripts/controlnet_ui/controlnet_ui_group.py", line 928, in run_annotator
    result = preprocessor.cached_call(
  File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/scripts/supported_preprocessor.py", line 196, in cached_call
    result = self._cached_call(input_image, *args, **kwargs)
  File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/scripts/utils.py", line 82, in decorated_func
    return cached_func(*args, **kwargs)
  File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/scripts/utils.py", line 66, in cached_func
    return func(*args, **kwargs)
  File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/scripts/supported_preprocessor.py", line 209, in _cached_call
    return self(*args, **kwargs)
  File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/scripts/preprocessor/teed.py", line 87, in __call__
    self.model = TEEDDetector(mteed=True)
  File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/annotator/teed/__init__.py", line 26, in __init__
    self.load_mteed_model()
  File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/annotator/teed/__init__.py", line 49, in load_mteed_model
    self.model.load_state_dict(unsafe_torch_load(model_path))
  File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/serialization.py", line 1035, in load
    return _load(opened_zipfile,
  File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/serialization.py", line 1456, in _load
    result = unpickler.load()
  File "/opt/homebrew/Cellar/[email protected]/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/pickle.py", line 1213, in load
    dispatch[key[0]](self)
  File "/opt/homebrew/Cellar/[email protected]/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/pickle.py", line 1254, in load_binpersid
    self.append(self.persistent_load(pid))
  File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/serialization.py", line 1426, in persistent_load
    typed_storage = load_tensor(dtype, nbytes, key, _maybe_decode_ascii(location))
  File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/serialization.py", line 1400, in load_tensor
    wrap_storage=restore_location(storage, location),
  File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/serialization.py", line 394, in default_restore_location
    result = fn(storage, location)
  File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/serialization.py", line 371, in _deserialize
    device = _validate_device(location, backend_name)
  File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/serialization.py", line 344, in _validate_device
    raise RuntimeError(f'Attempting to deserialize object on a {backend_name.upper()} '
RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your storages to the CPU.

And here's the output from Generate:

2024-05-30 10:40:24,907 - ControlNet - INFO - unit_separate = False, style_align = False
2024-05-30 10:40:25,157 - ControlNet - INFO - Loading model: mistoLine_softedge_sdxl_rank256 [0f320932]
2024-05-30 10:40:25,459 - ControlNet - INFO - Loaded state_dict from [/Users/Barracuda/stable-diffusion-webui/models/ControlNet/mistoLine_softedge_sdxl_rank256.safetensors]
2024-05-30 10:40:25,459 - ControlNet - INFO - Using ControlNet lora (SDXL)
2024-05-30 10:40:25,490 - ControlNet - INFO - ControlNet model mistoLine_softedge_sdxl_rank256 [0f320932](ControlModelType.ControlLoRA) loaded.
2024-05-30 10:40:25,505 - ControlNet - INFO - Using preprocessor: softedge_anyline
2024-05-30 10:40:25,505 - ControlNet - INFO - preprocessor resolution = 1016
*** Error running process: /Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/scripts/controlnet.py
    Traceback (most recent call last):
      File "/Users/Barracuda/stable-diffusion-webui/modules/scripts.py", line 825, in process
        script.process(p, *script_args)
      File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/scripts/controlnet.py", line 1222, in process
        self.controlnet_hack(p)
      File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/scripts/controlnet.py", line 1207, in controlnet_hack
        self.controlnet_main_entry(p)
      File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/scripts/controlnet.py", line 941, in controlnet_main_entry
        controls, hr_controls, additional_maps = get_control(
      File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/scripts/controlnet.py", line 290, in get_control
        controls, hr_controls = list(zip(*[preprocess_input_image(img) for img in optional_tqdm(input_images)]))
      File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/scripts/controlnet.py", line 290, in <listcomp>
        controls, hr_controls = list(zip(*[preprocess_input_image(img) for img in optional_tqdm(input_images)]))
      File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/scripts/controlnet.py", line 242, in preprocess_input_image
        result = preprocessor.cached_call(
      File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/scripts/supported_preprocessor.py", line 196, in cached_call
        result = self._cached_call(input_image, *args, **kwargs)
      File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/scripts/utils.py", line 82, in decorated_func
        return cached_func(*args, **kwargs)
      File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/scripts/utils.py", line 66, in cached_func
        return func(*args, **kwargs)
      File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/scripts/supported_preprocessor.py", line 209, in _cached_call
        return self(*args, **kwargs)
      File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/scripts/preprocessor/teed.py", line 87, in __call__
        self.model = TEEDDetector(mteed=True)
      File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/annotator/teed/__init__.py", line 26, in __init__
        self.load_mteed_model()
      File "/Users/Barracuda/stable-diffusion-webui/extensions/sd-controlnet/annotator/teed/__init__.py", line 49, in load_mteed_model
        self.model.load_state_dict(unsafe_torch_load(model_path))
      File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/serialization.py", line 1035, in load
        return _load(opened_zipfile,
      File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/serialization.py", line 1456, in _load
        result = unpickler.load()
      File "/opt/homebrew/Cellar/[email protected]/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/pickle.py", line 1213, in load
        dispatch[key[0]](self)
      File "/opt/homebrew/Cellar/[email protected]/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/pickle.py", line 1254, in load_binpersid
        self.append(self.persistent_load(pid))
      File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/serialization.py", line 1426, in persistent_load
        typed_storage = load_tensor(dtype, nbytes, key, _maybe_decode_ascii(location))
      File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/serialization.py", line 1400, in load_tensor
        wrap_storage=restore_location(storage, location),
      File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/serialization.py", line 394, in default_restore_location
        result = fn(storage, location)
      File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/serialization.py", line 371, in _deserialize
        device = _validate_device(location, backend_name)
      File "/Users/Barracuda/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/serialization.py", line 344, in _validate_device
        raise RuntimeError(f'Attempting to deserialize object on a {backend_name.upper()} '
    RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your storages to the CPU.

changpeidong · 2024-05-22T10:06:14Z

changpeidong
May 22, 2024

Why can I only generate 1:1 images in webui, the size is 1024x1024, and other ratios are not effective?

1 reply

dongshaojia Jul 1, 2024

Set Pixel Perfect to false

zou-yf · 2024-07-18T08:01:09Z

zou-yf
Jul 18, 2024

Could you please tell me why the image generated by my Anyline preprocessor looks like this?

0 replies

dongshaojia · 2024-07-18T08:53:34Z

dongshaojia
Jul 18, 2024

你需要下载对应的controlnet模型，他会自动从huggingface上下载，可能你访问不了huggingface，你可以在控制台看看那个模型的名称，从魔搭社区或者网上找可以访问的下载地址，下载到对应的文件夹 At 2024-07-18 16:01:31, "zou-yf" ***@***.***> wrote: Could you please tell me why the image generated by my Anyline preprocessor looks like this? 347763764-f7a73885-d180-44dc-9504-a1a7b0e7d3d3.png (view on web) — Reply to this email directly, view it on GitHub, or unsubscribe. You are receiving this because you commented.Message ID: ***@***.***>

1 reply

zou-yf Jul 19, 2024

我下载了MTEED.pth模型，并放置在了sd-webui-controlnet\annotator\downloads\TEED 目录下，我在4080的机器上是可以正常处理的，可是我在a100的机器上无法正常生成线稿，这个图可能看的比较明显

dongshaojia · 2024-07-19T00:52:01Z

dongshaojia
Jul 19, 2024

模型那点后边的那个刷新一下，在列表里选softedge的模型试试发自我的iPhone

…

在 2024年7月19日，08:48，zou-yf ***@***.***> 写道：我下载了MTEED.pth模型，并放置在了sd-webui-controlnet\annotator\downloads\TEED 目录下，我在4080的机器上是可以正常处理的，可是我在a100的机器上无法正常生成线稿，这个图可能看的比较明显，我不知道为什么 — Reply to this email directly, view it on GitHub, or unsubscribe. You are receiving this because you commented.

1 reply

zou-yf Jul 19, 2024

还是一样的效果，不管我是否加载模型

Mochalif085 · 2024-11-04T04:46:26Z

Mochalif085
Nov 4, 2024

can i use this for sd1.5?. is this only for sdxl?

1 reply

dan4ik94 Nov 4, 2024

only sdxl.

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[1.1.449] Anyline Preprocessor & MistoLine SDXL model #2907

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[1.1.449] Anyline Preprocessor & MistoLine SDXL model #2907

huchenlei May 19, 2024 Collaborator

Anyline Preprocessor

Misto Line SDXL Model

How to Use

Limitations

Replies: 8 comments · 10 replies

huchenlei May 20, 2024 Collaborator Author

huchenlei May 21, 2024 Collaborator Author

huchenlei
May 19, 2024
Collaborator

Replies: 8 comments 10 replies

huchenlei May 20, 2024
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huchenlei May 21, 2024
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