has anyone figured out how to use segmentation?

[gsgoldma]

I'm getting this error when trying to use it:

0%| | 0/20 [00:02<?, ?it/s]
Error completing request
Arguments: ('task(g6fede3wbf14x7h)', 'x marks the spot, pirate map', '', [], 20, 0, False, False, 1, 1, 7, -1.0, -1.0, 0, 0, 0, False, 512, 512, False, 0.7, 2, 'Latent', 0, 0, 0, [], 0, 0, 0, 0, 0, 0.25, False, True, False, 0, -1, False, 'keyword prompt', 'keyword1, keyword2', 'None', 'textual inversion first', True, False, 1, False, False, False, 1.1, 1.5, 100, 0.7, False, False, True, False, False, 0, 'Gustavosta/MagicPrompt-Stable-Diffusion', '', False, 7, 100, 'Constant', 0, 'Constant', 0, 4, False, 'x264', 'mci', 10, 0, False, True, True, True, 'intermediate', 'animation', False, False, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'Refresh models', True, 'segmentation', 'control_sd15_seg [fef5e48e]', 1, {'image': array([[[33, 21, 20],
[35, 22, 22],
[34, 21, 22],
...,
[24, 10, 8],
[23, 9, 8],
[24, 11, 9]],

   [[34, 24, 23],
    [33, 23, 21],
    [34, 24, 22],
    ...,
    [23, 11, 10],
    [20, 12,  8],
    [23, 12, 10]],

   [[35, 23, 23],
    [35, 25, 22],
    [36, 25, 23],
    ...,
    [24, 11, 10],
    [24, 13, 10],
    [23, 11, 10]],

   ...,

   [[30,  1,  4],
    [29,  3,  8],
    [31,  4,  6],
    ...,
    [41, 17,  7],
    [32, 12,  4],
    [25,  7,  0]],

   [[30,  0,  1],
    [29,  0,  4],
    [32,  1,  2],
    ...,
    [17,  5,  4],
    [15,  7,  6],
    [17,  4,  0]],

   [[28,  0,  1],
    [30,  0,  2],
    [34,  0,  2],
    ...,
    [13,  6,  6],
    [13,  2,  3],
    [17,  6,  2]]], dtype=uint8), 'mask': array([[[  0,   0,   0, 255],
    [  0,   0,   0, 255],
    [  0,   0,   0, 255],
    ...,
    [  0,   0,   0, 255],
    [  0,   0,   0, 255],
    [  0,   0,   0, 255]],

   [[  0,   0,   0, 255],
    [  0,   0,   0, 255],
    [  0,   0,   0, 255],
    ...,
    [  0,   0,   0, 255],
    [  0,   0,   0, 255],
    [  0,   0,   0, 255]],

   [[  0,   0,   0, 255],
    [  0,   0,   0, 255],
    [  0,   0,   0, 255],
    ...,
    [  0,   0,   0, 255],
    [  0,   0,   0, 255],
    [  0,   0,   0, 255]],

   ...,

   [[  0,   0,   0, 255],
    [  0,   0,   0, 255],
    [  0,   0,   0, 255],
    ...,
    [  0,   0,   0, 255],
    [  0,   0,   0, 255],
    [  0,   0,   0, 255]],

   [[  0,   0,   0, 255],
    [  0,   0,   0, 255],
    [  0,   0,   0, 255],
    ...,
    [  0,   0,   0, 255],
    [  0,   0,   0, 255],
    [  0,   0,   0, 255]],

   [[  0,   0,   0, 255],
    [  0,   0,   0, 255],
    [  0,   0,   0, 255],
    ...,
    [  0,   0,   0, 255],
    [  0,   0,   0, 255],
    [  0,   0,   0, 255]]], dtype=uint8)}, True, 'Scale to Fit (Inner Fit)', False, True, None, '', 'Get Tags', '', '', False, False, 'Denoised', 5.0, 0.0, 0.0, False, 'mp4', 'h264', 2.0, 0.0, 0.0, False, 0.0, True, True, False, 0.9, 5, '0.0001', False, 'None', '', 0.1, False, False, False, 3, 0, False, False, 0, '', False, False, False, False, 'Auto', 0.5, 1, False, False, False, '', '', '', '', '', '', '', '', '', '', '', '', '', True, -1.0, False, '', True, False, 0, 384, 0, True, True, True, 1, '\n            <h3><strong>Combinations</strong></h3>\n            Choose a number of terms from a list, in this case we choose two artists\n            <code>{2$$artist1|artist2|artist3}</code>\n            If $$ is not provided, then 1$$ is assumed.\n            <br/><br/>\n\n            <h3><strong>Wildcards</strong></h3>\n            <p>Available wildcards</p>\n            <ul>\n        </ul>\n            <br/>\n            <code>WILDCARD_DIR: scripts/wildcards</code><br/>\n            <small>You can add more wildcards by creating a text file with one term per line and name is mywildcards.txt. Place it in scripts/wildcards. <code>__mywildcards__</code> will then become available.</small>\n        ', None, '', 'outputs', 1, '', 0, '', True, False, False, False, False, False, 1, 1, False, True, False, '', 1, True, 100, True, 50, '', '', 8, True, 16, 'Median cut', 8, True, True, 16, 'PNN', True, False, None, None, '', '', '', '', 'Auto rename', {'label': 'Upload avatars config'}, 'Open outputs directory', 'Export to WebUI style', True, {'label': 'Presets'}, {'label': 'QC preview'}, '', [], 'Select', 'QC scan', 'Show pics', None, False, False, 'positive', 'comma', 0, '', 25, True, 5.0, False, False, '', '', '', 'Positive', 0, ', ', True, 32, 0, 'Median cut', 'luminance', False, 'svg', True, True, False, 0.5, 1, '', 0, '', 0, '', True, False, False, False, 0, False, 'Not set', True, True, '', '', '', '', '', 1.3, 'Not set', 'Not set', 1.3, 'Not set', 1.3, 'Not set', 1.3, 1.3, 'Not set', 1.3, 'Not set', 1.3, 'Not set', 1.3, 'Not set', 1.3, 'Not set', 1.3, 'Not set', False, 'None', '', 'None', 30, 4, 0, 0, False, 'None', '<br>', 'None', 30, 4, 0, 0, 4, 0.4, True, 32, None, True, None, None, False, '', 5, 24, 12.5, 1000, 'DDIM', 0, 64, 64, '', 64, 7.5, 0.42, 'DDIM', 64, 64, 1, 0, 92, True, True, True, False, False, False, 'midas_v21_small', False, True, False, True, True, [], False, '', True, False, 'D:\\stable-diffusion-webui\\extensions\\sd-webui-riffusion\\outputs', 'Refresh Inline Audio (Last Batch)', None, None, None, None, None, None, None, None, False, 4.0, '', 10.0, 'Linear', 3, False, True, 30.0, True, False, False, 0, 0.0, 'Lanczos', 1, True, 10.0, True, 30.0, True, 0.0, 'Lanczos', 1, '{inspiration}', None, 'linear', 'lerp', 'token', 'random', '30', 'fixed', 1, '8', None, 'Lanczos', 2, 0, 0, 'mp4', 10.0, 0, '', True, False, False, 'Euler a', 0.95, 0.75, 'zero', 'pos', 'linear', 0.01, 0.0, 0.75, None, 'Lanczos', 1, 0, 0) {}

Traceback (most recent call last):
File "D:\stable-diffusion-webui\modules\call_queue.py", line 56, in f
res = list(func(*args, **kwargs))
File "D:\stable-diffusion-webui\modules\call_queue.py", line 37, in f
res = func(*args, **kwargs)
File "D:\stable-diffusion-webui\modules\txt2img.py", line 56, in txt2img
processed = process_images(p)
File "D:\stable-diffusion-webui\modules\processing.py", line 486, in process_images
res = process_images_inner(p)
File "D:\stable-diffusion-webui\modules\processing.py", line 628, in process_images_inner
samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, prompts=prompts)
File "D:\stable-diffusion-webui\modules\processing.py", line 828, in sample
samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
File "D:\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 323, in sample
samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
File "D:\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 221, in launch_sampling
return func()
File "D:\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 323, in
samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "D:\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\sampling.py", line 145, in sample_euler_ancestral
denoised = model(x, sigmas[i] * s_in, **extra_args)
File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "D:\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 122, in forward
x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond={"c_crossattn": [cond_in[a:b]], "c_concat": [image_cond_in[a:b]]})
File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "D:\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 112, in forward
eps = self.get_eps(input * c_in, self.sigma_to_t(sigma), **kwargs)
File "D:\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 138, in get_eps
return self.inner_model.apply_model(*args, **kwargs)
File "D:\stable-diffusion-webui\modules\sd_hijack_utils.py", line 17, in
setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
File "D:\stable-diffusion-webui\modules\sd_hijack_utils.py", line 28, in call
return self.__orig_func(*args, **kwargs)
File "D:\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 858, in apply_model
x_recon = self.model(x_noisy, t, **cond)
File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1212, in _call_impl
result = forward_call(*input, **kwargs)
File "D:\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 1329, in forward
out = self.diffusion_model(x, t, context=cc)
File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\cldm.py", line 150, in forward2
return forward(*args, **kwargs)
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\cldm.py", line 111, in forward
if abs(x.shape[-1] - outer.hint_cond.shape[-1] // 8) > 8:
AttributeError: 'NoneType' object has no attribute 'shape'

[Mikubill]

Check the output before Error completing request - last traceback usually just extension's hook fails because of previous error

[gsgoldma]

Loading preprocessor: segmentation, model: control_sd15_seg [fef5e48e]
Loaded state_dict from [D:\stable-diffusion-webui\extensions\sd-webui-controlnet\models\control_sd15_seg.pth]
ControlNet model control_sd15_seg [fef5e48e] loaded.
Error running process: D:\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\controlnet.py
Traceback (most recent call last):
File "D:\stable-diffusion-webui\modules\scripts.py", line 386, in process
script.process(p, *script_args)
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\controlnet.py", line 372, in process
detected_map = preprocessor(input_image, res=pres, thr_a=pthr_a, thr_b=pthr_b)
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\processor.py", line 139, in uniformer
from annotator.uniformer import apply_uniformer
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\uniformer_init_.py", line 1, in
from annotator.uniformer.mmseg.apis import init_segmentor, inference_segmentor, show_result_pyplot
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\uniformer\mmseg\apis_init_.py", line 1, in
from .inference import inference_segmentor, init_segmentor, show_result_pyplot
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\uniformer\mmseg\apis\inference.py", line 8, in
from annotator.uniformer.mmseg.models import build_segmentor
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\uniformer\mmseg\models_init_.py", line 4, in
from .decode_heads import * # noqa: F401,F403
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\uniformer\mmseg\models\decode_heads_init_.py", line 4, in
from .cc_head import CCHead
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\uniformer\mmseg\models\decode_heads\cc_head.py", line 7, in
from annotator.uniformer.mmcv.ops import CrissCrossAttention
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\uniformer\mmcv\ops_init_.py", line 10, in
from .corner_pool import CornerPool
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\uniformer\mmcv\ops\corner_pool.py", line 8, in
ext_module = ext_loader.load_ext('_ext', [
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\uniformer\mmcv\utils\ext_loader.py", line 15, in load_ext
assert hasattr(ext, fun), f'{fun} miss in module {name}'
AssertionError: top_pool_forward miss in module _ext

0%| | 0/20 [00:00<?, ?it/s]
Error completing request
Arguments: ('task(wyvhh3mpe36epb5)', 0, '', '', [], <PIL.Image.Image image mode=RGBA size=258x195 at 0x15F4CE83C40>, None, None, None, None, None, None, 20, 0, 4, 0, 1, False, False, 1, 1, 7, 1.5, 0.75, -1.0, -1.0, 0, 0, 0, False, 512, 512, 0, 0, 32, 0, '', '', '', [], 0, 0, 0, 0, 0, 0.25, False, True, False, 0, -1, False, 'keyword prompt', 'keyword1, keyword2', 'None', 'textual inversion first', True, False, 1, False, False, False, 1.1, 1.5, 100, 0.7, False, False, True, False, False, 0, 'Gustavosta/MagicPrompt-Stable-Diffusion', '', False, 7, 100, 'Constant', 0, 'Constant', 0, 4, False, 'x264', 'mci', 10, 0, False, True, True, True, 'intermediate', 'animation', False, False, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'Refresh models', True, 'segmentation', 'control_sd15_seg [fef5e48e]', 1, None, False, 'Scale to Fit (Inner Fit)', False, True, 512, 64, 64, None, '', 'Get Tags', '', '', False, False, 'Denoised', 5.0, 0.0, 0.0, False, 'mp4', 'h264', 2.0, 0.0, 0.0, False, 0.0, True, True, False, 0.9, 5, '0.0001', False, 'None', '', 0.1, False, False, False, 3, 0, False, False, 0, '', False, False, False, False, 'Auto', 0.5, 1, False, False, 4.0, 1, 1, 0, 0, 0.0, 4.0, 0.1, 0.1, 1, True, False, False, 0, False, '', 1, False, 0, 1, False, False, False, '', '

Render these video formats:

', '

Animation Parameters

', '

Prompt Template, applied to each keyframe below

', '

Keyframe Format:
Time (s) | Desnoise | Zoom (/s) | X Shift (pix/s) | Y shift (pix/s) | Positive Prompts | Negative Prompts | Seed

', '10.0', '15', False, False, True, '1.0', '', '', '', 0.4, '0', '0', False, False, 0.1, 0.5, True, False, '', '', 0, 384, 0, True, True, True, 1, '\n

Combinations

\n Choose a number of terms from a list, in this case we choose two artists\n {2$$artist1|artist2|artist3}\n If $$ is not provided, then 1$$ is assumed.\n

\n\n

Wildcards

\n

Available wildcards

\n

\n

\n
\n WILDCARD_DIR: scripts/wildcards
\n You can add more wildcards by creating a text file with one term per line and name is mywildcards.txt. Place it in scripts/wildcards. mywildcards will then become available.\n ', None, '', 'outputs', 1, '', 0, '', True, False, False, False, 670, False, False, True, '

\n
• CFG Scale should be 2 or lower.
\n

\n', True, True, '', '', True, 50, True, 1, 0, False, 1, 0, '#000000', True, False, 0, 256, 0, False, None, '', 0.2, 0.1, 1, 1, False, True, True, False, False, False, False, '', 1, True, 100, 4, 1, 4, 0.09, True, 1, 0, 7, False, False, True, 50, 0, 0, 'Show/Hide Canvas', 0, '

Recommended settings: Sampling Steps: 80-100, Sampler: Euler a, Denoising strength: 0.8

', 128, 8, ['left', 'right', 'up', 'down'], 1, 0.05, 8, True, 16, 'Median cut', 8, True, True, 16, 'PNN', True, 128, 4, 0, ['left', 'right', 'up', 'down'], False, None, None, '', '', '', '', 'Auto rename', {'label': 'Upload avatars config'}, 'Open outputs directory', 'Export to WebUI style', True, {'label': 'Presets'}, {'label': 'QC preview'}, '', [], 'Select', 'QC scan', 'Show pics', None, False, False, 'positive', 'comma', 0, False, False, '', 0, 0, 0, False, 0, False, False, False, '', '', '

Will upscale the image by the selected scale factor; use width and height sliders to set tile size

', 64, 0, 2, 'Positive', 0, ', ', True, 32, '', '', 100, 0, 0, True, '

If you like my work, please consider showing your support on Patreon. Thank you! ❤

', 'svg', True, True, False, 0.5, '

Will upscale the image to selected with and height

', 512, 8, 32, True, 16, 0.25, 32, 0, True, True, True, '', 24, 24, 0, 10, '00:00:00', '00:00:00', False, '', 0, 1, 10, True, 1, False, 1, 0, 0, False, 0, False, False, False, 0, False, False, 0, 1, '', 0, '', 0, '', True, False, False, False, 0, False, 'Not set', True, True, '', '', '', '', '', 1.3, 'Not set', 'Not set', 1.3, 'Not set', 1.3, 'Not set', 1.3, 1.3, 'Not set', 1.3, 'Not set', 1.3, 'Not set', 1.3, 'Not set', 1.3, 'Not set', 1.3, 'Not set', False, 'None', True, True, '', False, 1, 'Both ▦', False, '', False, True, False, False, False, False, 0, False, '', '', '', 'generateMasksTab', 1, 4, 2.5, 30, 1.03, 1, 1, 5, 0.5, 5, False, True, '

Recommended settings: Use from inpaint tab, inpaint at full res ON, denoise <0.5

', 'None', 30, 4, 0, 0, False, 'None', '
', 'None', 30, 4, 0, 0, 4, 0.4, True, 32, '

Deforum v0.5-webui-beta

', '

This script is deprecated. Please use the full Deforum extension instead.
\nUpdate instructions:

', '

github.com/deforum-art/deforum-for-automatic1111-webui/blob/automatic1111-webui/README.md

', '

discord.gg/deforum

', None, True, None, None, False, False, 0, True, 384, 384, False, 2, True, True, False, False, '', '', '', False, False, False, False, 50, '0', False, '', False, False, False, 1 2 3
0 , False, 512, 512, 0.2, True, True, True, False, True, False, True, True, 'Create in UI', False, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', True, False, 'D:\stable-diffusion-webui\extensions\sd-webui-riffusion\outputs', 'Refresh Inline Audio (Last Batch)', None, None, None, None, None, None, None, None, False, 4.0, '', 10.0, 'Linear', 3, False, True, 30.0, True, False, False, 0, 0.0, 'Lanczos', 1, True, 10.0, True, 30.0, True, 0.0, 'Lanczos', 1, 0, 0, 512, 512, False, False, True, True, True, False, True, 1, False, False, 2.5, 4, 0, False, 0, 1, False, False, 'u2net', False, False, False, False, '{inspiration}', None, 'linear', 'lerp', 'token', 'random', '30', 'fixed', 1, '8', None, 'Lanczos', 2, 0, 0, 'mp4', 10.0, 0, '', True, False, False, 'Euler a', 0.95, 0.75, 'zero', 'pos', 'linear', 0.01, 0.0, 0.75, None, 'Lanczos', 1, 0, 0, '

Will upscale the image depending on the selected target size type

', 512, 0, 8, 32, 16, 0.25, 32, 0, True, 0, False, 8, 0, 0, 2048, 2048, 2, '', '', False, '', 127, False, 30, 9999, 1, 10, 0.25, True, False, '1', '', True, '', '', '', '', '', '', '', '', '', '', '', 'None', 0.3, 60) {}
Traceback (most recent call last):
File "D:\stable-diffusion-webui\modules\call_queue.py", line 56, in f
res = list(func(*args, **kwargs))
File "D:\stable-diffusion-webui\modules\call_queue.py", line 37, in f
res = func(*args, **kwargs)
File "D:\stable-diffusion-webui\modules\img2img.py", line 169, in img2img
processed = process_images(p)
File "D:\stable-diffusion-webui\modules\processing.py", line 486, in process_images
res = process_images_inner(p)
File "D:\stable-diffusion-webui\modules\processing.py", line 628, in process_images_inner
samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, prompts=prompts)
File "D:\stable-diffusion-webui\modules\processing.py", line 1044, in sample
samples = self.sampler.sample_img2img(self, self.init_latent, x, conditioning, unconditional_conditioning, image_conditioning=self.image_conditioning)
File "D:\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 302, in sample_img2img
samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
File "D:\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 221, in launch_sampling
return func()
File "D:\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 302, in
samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "D:\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\sampling.py", line 145, in sample_euler_ancestral
denoised = model(x, sigmas[i] * s_in, **extra_args)
File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "D:\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 116, in forward
x_out = self.inner_model(x_in, sigma_in, cond={"c_crossattn": [cond_in], "c_concat": [image_cond_in]})
File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "D:\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 112, in forward
eps = self.get_eps(input * c_in, self.sigma_to_t(sigma), **kwargs)
File "D:\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 138, in get_eps
return self.inner_model.apply_model(*args, **kwargs)
File "D:\stable-diffusion-webui\modules\sd_hijack_utils.py", line 17, in
setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
File "D:\stable-diffusion-webui\modules\sd_hijack_utils.py", line 28, in call
return self.__orig_func(*args, **kwargs)
File "D:\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 858, in apply_model
x_recon = self.model(x_noisy, t, **cond)
File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "D:\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 1329, in forward
out = self.diffusion_model(x, t, context=cc)
File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\cldm.py", line 161, in forward2
return forward(*args, **kwargs)
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\cldm.py", line 122, in forward
if abs(x.shape[-1] - outer.hint_cond.shape[-1] // 8) > 8:
AttributeError: 'NoneType' object has no attribute 'shape'

[ClashSAN]

what happens when you startup webui and try it?

It might be relating to switching from a module, but try generating again (or even a third time afterward)

[gsgoldma]

what happens when you startup webui and try it?

It might be relating to switching from a module, but try generating again (or even a third time afterward)

i actually got it to work for a couple minutes, but there was a bug that it only accepted the first mask i drew, and everytime i changed it, it still reverted back to the same mask. when i refresh the webui to try again, the error came back.

[jbluew]

Removing mmcv-full fixed this for me. See #70 . I didn't figure out which extension it was related to, that I was using.

[gsgoldma]

when you run it, do you do it in inpaint or img2img?
not sure exactly the right steps to take with it

[jbluew]

Either way works for me, but you can run in txt2img as well. I did notice that Denoising Strength affects the output when running in img2img group of tabs, but I'm not sure if I'm understanding it correctly, and every few hours the tool is changing, heheh.

[gsgoldma]

I got it to work partially but not really. It wont make a segment map, even with the preprocessor, I get this error but it still makes an image.
i can get it to 'work' if i choose none as a preprocessor, make an image, and then choose segmentation as the preprocessor. but it doesnt make a segment map. if i draw something on the image (in the bottom control net extension area) it will only show my drawing part, if I don't include any drawing, it just uses the actual image itself, not a segmentation map of it.: (I ended the generation early)

30%|████████████ | 6/20 [00:07<00:18, 1.30s/it]
Error running process: D:\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\controlnet.py
Traceback (most recent call last):
File "D:\stable-diffusion-webui\modules\scripts.py", line 386, in process
script.process(p, *script_args)
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\controlnet.py", line 372, in process
detected_map = preprocessor(input_image, res=pres, thr_a=pthr_a, thr_b=pthr_b)
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\processor.py", line 139, in uniformer
from annotator.uniformer import apply_uniformer
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\uniformer_init_.py", line 1, in
from annotator.uniformer.mmseg.apis import init_segmentor, inference_segmentor, show_result_pyplot
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\uniformer\mmseg\apis_init_.py", line 1, in
from .inference import inference_segmentor, init_segmentor, show_result_pyplot
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\uniformer\mmseg\apis\inference.py", line 8, in
from annotator.uniformer.mmseg.models import build_segmentor
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\uniformer\mmseg\models_init_.py", line 4, in
from .decode_heads import * # noqa: F401,F403
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\uniformer\mmseg\models\decode_heads_init_.py", line 4, in
from .cc_head import CCHead
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\uniformer\mmseg\models\decode_heads\cc_head.py", line 7, in
from annotator.uniformer.mmcv.ops import CrissCrossAttention
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\uniformer\mmcv\ops_init_.py", line 10, in
from .corner_pool import CornerPool
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\uniformer\mmcv\ops\corner_pool.py", line 8, in
ext_module = ext_loader.load_ext('_ext', [
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\annotator\uniformer\mmcv\utils\ext_loader.py", line 15, in load_ext
assert hasattr(ext, fun), f'{fun} miss in module {name}'
AssertionError: top_pool_forward miss in module _ext

[jbluew]

All i had to do was go into "stable-diffusion-webui\venv\Lib\site-packages" and delete the "mmcv" and "mmcv_full-1.7.0.dist-info" folders and restart webui. I'm on windows.

[gsgoldma]

All i had to do was go into "stable-diffusion-webui\venv\Lib\site-packages" and delete the "mmcv" and "mmcv_full-1.7.0.dist-info" folders and restart webui. I'm on windows.

will that make a problem for the extension that required those two?

[jbluew]

I wouldn't surprised if it did, but at least you'll know which one uses it.

[gsgoldma]

I wouldn't surprised if it did, but at least you'll know which one uses it.

it was ddetailer.

[marcsyp]

ddetailer is a great extension -- it would be nice to have consistency between the two extensions so that they can work together...