[Bug]: controlnet
kalle07 opened this issue · comments
Checklist
- The issue exists after disabling all extensions
- The issue exists on a clean installation of webui
- The issue is caused by an extension, but I believe it is caused by a bug in the webui
- The issue exists in the current version of the webui
- The issue has not been reported before recently
- The issue has been reported before but has not been fixed yet
What happened?
openpose works
photoID works
reference dont work (console below)
depth dont work (similar error: TypeError: 'NoneType' object is not iterable)
Steps to reproduce the problem
all errors in tab "img2img"
most works in txt2img
What should have happened?
What browsers do you use to access the UI ?
No response
Sysinfo
win10
rtx4060
forge version: f0.0.17v1.8.0rc
Console logs
---
2024-05-31 15:17:13,385 - ControlNet - INFO - ControlNet Input Mode: InputMode.SIMPLE
2024-05-31 15:17:13,385 - ControlNet - INFO - Using preprocessor: reference_only
2024-05-31 15:17:13,385 - ControlNet - INFO - preprocessor resolution = 0.5
2024-05-31 15:17:13,445 - ControlNet - INFO - Current ControlNet ControlModelPatcher: Not Needed
2024-05-31 15:17:14,020 - ControlNet - INFO - ControlNet Method reference_only patched.
To load target model SDXL
Begin to load 1 model
Reuse 1 loaded models
[Memory Management] Current Free GPU Memory (MB) = 4634.16552734375
[Memory Management] Model Memory (MB) = 0.0
[Memory Management] Minimal Inference Memory (MB) = 1024.0
[Memory Management] Estimated Remaining GPU Memory (MB) = 3610.16552734375
Moving model(s) has taken 0.05 seconds
0%| | 0/16 [00:00<?, ?it/s]
Traceback (most recent call last):
File "E:\WebUI_Forge\webui\modules_forge\main_thread.py", line 37, in loop
task.work()
File "E:\WebUI_Forge\webui\modules_forge\main_thread.py", line 26, in work
self.result = self.func(*self.args, **self.kwargs)
File "E:\WebUI_Forge\webui\modules\img2img.py", line 236, in img2img_function
processed = process_images(p)
File "E:\WebUI_Forge\webui\modules\processing.py", line 752, in process_images
res = process_images_inner(p)
File "E:\WebUI_Forge\webui\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 "E:\WebUI_Forge\webui\modules\processing.py", line 1703, in sample
samples = self.sampler.sample_img2img(self, self.init_latent, x, conditioning, unconditional_conditioning, image_conditioning=self.image_conditioning)
File "E:\WebUI_Forge\webui\modules\sd_samplers_kdiffusion.py", line 197, in sample_img2img
samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
File "E:\WebUI_Forge\webui\modules\sd_samplers_common.py", line 263, in launch_sampling
return func()
File "E:\WebUI_Forge\webui\modules\sd_samplers_kdiffusion.py", line 197, in <lambda>
samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
File "e:\WebUI_Forge\system\python\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "E:\WebUI_Forge\webui\repositories\k-diffusion\k_diffusion\sampling.py", line 594, in sample_dpmpp_2m
denoised = model(x, sigmas[i] * s_in, **extra_args)
File "e:\WebUI_Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "e:\WebUI_Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "E:\WebUI_Forge\webui\modules\sd_samplers_cfg_denoiser.py", line 182, in forward
denoised = forge_sampler.forge_sample(self, denoiser_params=denoiser_params,
File "E:\WebUI_Forge\webui\modules_forge\forge_sampler.py", line 88, in forge_sample
denoised = sampling_function(model, x, timestep, uncond, cond, cond_scale, model_options, seed)
File "E:\WebUI_Forge\webui\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 "E:\WebUI_Forge\webui\ldm_patched\modules\samplers.py", line 256, in calc_cond_uncond_batch
output = model_options['model_function_wrapper'](model.apply_model, {"input": input_x, "timestep": timestep_, "c": c, "cond_or_uncond": cond_or_uncond}).chunk(batch_chunks)
File "e:\WebUI_Forge\system\python\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "E:\WebUI_Forge\webui\extensions-builtin\sd_forge_multidiffusion\lib_multidiffusion\tiled_diffusion.py", line 428, in __call__
x_tile_out = model_function(x_tile, ts_tile, **c_tile)
File "E:\WebUI_Forge\webui\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 "e:\WebUI_Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "e:\WebUI_Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "E:\WebUI_Forge\webui\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 "E:\WebUI_Forge\webui\ldm_patched\ldm\modules\diffusionmodules\openaimodel.py", line 55, in forward_timestep_embed
x = layer(x, context, transformer_options)
File "e:\WebUI_Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "e:\WebUI_Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "E:\WebUI_Forge\webui\ldm_patched\ldm\modules\attention.py", line 620, in forward
x = block(x, context=context[i], transformer_options=transformer_options)
File "e:\WebUI_Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "e:\WebUI_Forge\system\python\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "E:\WebUI_Forge\webui\ldm_patched\ldm\modules\attention.py", line 447, in forward
return checkpoint(self._forward, (x, context, transformer_options), self.parameters(), self.checkpoint)
File "E:\WebUI_Forge\webui\ldm_patched\ldm\modules\diffusionmodules\util.py", line 194, in checkpoint
return func(*inputs)
File "E:\WebUI_Forge\webui\ldm_patched\ldm\modules\attention.py", line 504, in _forward
n = attn1_replace_patch[block_attn1](n, context_attn1, value_attn1, extra_options)
File "E:\WebUI_Forge\webui\extensions-builtin\forge_preprocessor_reference\scripts\forge_reference.py", line 172, in attn1_proc
o_c = sdp(q_c, zero_cat(k_c, k_r, dim=1), zero_cat(v_c, v_r, dim=1), transformer_options)
File "E:\WebUI_Forge\webui\extensions-builtin\forge_preprocessor_reference\scripts\forge_reference.py", line 29, in zero_cat
return torch.cat([a, b], dim=dim)
RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 1 but got size 2 for tensor number 1 in the list.
Sizes of tensors must match except in dimension 1. Expected size 1 but got size 2 for tensor number 1 in the list.
*** Error completing request
*** Arguments: ('task(mfhbttqrzlyemjk)', 0, 'boy sitting in the room', '', [], <PIL.Image.Image image mode=RGBA size=1280x720 at 0x17A11DF8910>, None, None, None, None, None, None, 20, 'DPM++ 2M Karras', 4, 0, 1, 1, 1, 3, 1.5, 0.78, 0.0, 640, 1024, 1, 0, 0, 32, 0, '', '', '', [], False, [], '', <gradio.routes.Request object at 0x0000017A51D56050>, 0, False, 1, 0.5, 4, 0, 0.5, 2, False, '', 0.8, -1, False, -1, 0, 0, 0, False, False, {'ad_model': 'face_yolov8n.pt', 'ad_model_classes': '', 'ad_tap_enable': True, 'ad_prompt': '', 'ad_negative_prompt': '', 'ad_confidence': 0.3, 'ad_mask_k_largest': 0, 'ad_mask_min_ratio': 0, 'ad_mask_max_ratio': 1, 'ad_x_offset': 0, 'ad_y_offset': 0, 'ad_dilate_erode': 4, 'ad_mask_merge_invert': 'None', 'ad_mask_blur': 4, 'ad_denoising_strength': 0.4, 'ad_inpaint_only_masked': True, 'ad_inpaint_only_masked_padding': 32, 'ad_use_inpaint_width_height': False, 'ad_inpaint_width': 512, 'ad_inpaint_height': 512, 'ad_use_steps': False, 'ad_steps': 28, 'ad_use_cfg_scale': False, 'ad_cfg_scale': 7, 'ad_use_checkpoint': False, 'ad_checkpoint': 'Use same checkpoint', 'ad_use_vae': False, 'ad_vae': 'Use same VAE', 'ad_use_sampler': False, 'ad_sampler': 'DPM++ 2M Karras', 'ad_scheduler': 'Use same scheduler', 'ad_use_noise_multiplier': False, 'ad_noise_multiplier': 1, 'ad_use_clip_skip': False, 'ad_clip_skip': 1, 'ad_restore_face': False, 'ad_controlnet_model': 'None', 'ad_controlnet_module': 'None', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, {'ad_model': 'None', 'ad_model_classes': '', 'ad_tap_enable': True, 'ad_prompt': '', 'ad_negative_prompt': '', 'ad_confidence': 0.3, 'ad_mask_k_largest': 0, 'ad_mask_min_ratio': 0, 'ad_mask_max_ratio': 1, 'ad_x_offset': 0, 'ad_y_offset': 0, 'ad_dilate_erode': 4, 'ad_mask_merge_invert': 'None', 'ad_mask_blur': 4, 'ad_denoising_strength': 0.4, 'ad_inpaint_only_masked': True, 'ad_inpaint_only_masked_padding': 32, 'ad_use_inpaint_width_height': False, 'ad_inpaint_width': 512, 'ad_inpaint_height': 512, 'ad_use_steps': False, 'ad_steps': 28, 'ad_use_cfg_scale': False, 'ad_cfg_scale': 7, 'ad_use_checkpoint': False, 'ad_checkpoint': 'Use same checkpoint', 'ad_use_vae': False, 'ad_vae': 'Use same VAE', 'ad_use_sampler': False, 'ad_sampler': 'DPM++ 2M Karras', 'ad_scheduler': 'Use same scheduler', 'ad_use_noise_multiplier': False, 'ad_noise_multiplier': 1, 'ad_use_clip_skip': False, 'ad_clip_skip': 1, 'ad_restore_face': False, 'ad_controlnet_model': 'None', 'ad_controlnet_module': 'None', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, {'ad_model': 'None', 'ad_model_classes': '', 'ad_tap_enable': True, 'ad_prompt': '', 'ad_negative_prompt': '', 'ad_confidence': 0.3, 'ad_mask_k_largest': 0, 'ad_mask_min_ratio': 0, 'ad_mask_max_ratio': 1, 'ad_x_offset': 0, 'ad_y_offset': 0, 'ad_dilate_erode': 4, 'ad_mask_merge_invert': 'None', 'ad_mask_blur': 4, 'ad_denoising_strength': 0.4, 'ad_inpaint_only_masked': True, 'ad_inpaint_only_masked_padding': 32, 'ad_use_inpaint_width_height': False, 'ad_inpaint_width': 512, 'ad_inpaint_height': 512, 'ad_use_steps': False, 'ad_steps': 28, 'ad_use_cfg_scale': False, 'ad_cfg_scale': 7, 'ad_use_checkpoint': False, 'ad_checkpoint': 'Use same checkpoint', 'ad_use_vae': False, 'ad_vae': 'Use same VAE', 'ad_use_sampler': False, 'ad_sampler': 'DPM++ 2M Karras', 'ad_scheduler': 'Use same scheduler', 'ad_use_noise_multiplier': False, 'ad_noise_multiplier': 1, 'ad_use_clip_skip': False, 'ad_clip_skip': 1, 'ad_restore_face': False, 'ad_controlnet_model': 'None', 'ad_controlnet_module': 'None', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, {'ad_model': 'None', 'ad_model_classes': '', 'ad_tap_enable': True, 'ad_prompt': '', 'ad_negative_prompt': '', 'ad_confidence': 0.3, 'ad_mask_k_largest': 0, 'ad_mask_min_ratio': 0, 'ad_mask_max_ratio': 1, 'ad_x_offset': 0, 'ad_y_offset': 0, 'ad_dilate_erode': 4, 'ad_mask_merge_invert': 'None', 'ad_mask_blur': 4, 'ad_denoising_strength': 0.4, 'ad_inpaint_only_masked': True, 'ad_inpaint_only_masked_padding': 32, 'ad_use_inpaint_width_height': False, 'ad_inpaint_width': 512, 'ad_inpaint_height': 512, 'ad_use_steps': False, 'ad_steps': 28, 'ad_use_cfg_scale': False, 'ad_cfg_scale': 7, 'ad_use_checkpoint': False, 'ad_checkpoint': 'Use same checkpoint', 'ad_use_vae': False, 'ad_vae': 'Use same VAE', 'ad_use_sampler': False, 'ad_sampler': 'DPM++ 2M Karras', 'ad_scheduler': 'Use same scheduler', 'ad_use_noise_multiplier': False, 'ad_noise_multiplier': 1, 'ad_use_clip_skip': False, 'ad_clip_skip': 1, 'ad_restore_face': False, 'ad_controlnet_model': 'None', 'ad_controlnet_module': 'None', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, None, False, '0', '0', 'inswapper_128.onnx', 'CodeFormer', 1, True, 'None', 1, 1, False, True, 1, 0, 0, False, 0.5, True, False, 'CUDA', False, 0, 'None', '', None, False, False, 0.5, 0, ControlNetUnit(input_mode=<InputMode.SIMPLE: 'simple'>, use_preview_as_input=False, batch_image_dir='', batch_mask_dir='', batch_input_gallery=[], batch_mask_gallery=[], generated_image=array([[[191, 173, 159],
*** [191, 173, 159],
*** [191, 173, 159],
*** ...,
*** [216, 214, 202],
*** [214, 210, 199],
*** [211, 207, 196]],
***
*** [[191, 173, 159],
*** [191, 173, 159],
*** [191, 173, 159],
*** ...,
*** [219, 217, 205],
*** [217, 213, 202],
*** [214, 210, 199]],
***
*** [[191, 173, 159],
*** [191, 173, 159],
*** [191, 173, 159],
*** ...,
*** [223, 221, 209],
*** [221, 217, 206],
*** [218, 214, 203]],
***
*** ...,
***
*** [[221, 204, 196],
*** [218, 201, 193],
*** [212, 195, 187],
*** ...,
*** [202, 179, 161],
*** [218, 192, 177],
*** [224, 196, 182]],
***
*** [[217, 197, 190],
*** [206, 186, 179],
*** [188, 169, 162],
*** ...,
*** [224, 201, 183],
*** [226, 200, 185],
*** [205, 179, 164]],
***
*** [[213, 190, 184],
*** [197, 174, 168],
*** [172, 152, 145],
*** ...,
*** [193, 170, 152],
*** [173, 147, 132],
*** [154, 128, 113]]], dtype=uint8), mask_image=None, hr_option='Both', enabled=True, module='reference_only', model='None', weight=1, image={'image': array([[[191, 173, 159],
*** [191, 173, 159],
*** [191, 173, 159],
*** ...,
*** [216, 214, 202],
*** [214, 210, 199],
*** [211, 207, 196]],
***
*** [[191, 173, 159],
*** [191, 173, 159],
*** [191, 173, 159],
*** ...,
*** [219, 217, 205],
*** [217, 213, 202],
*** [214, 210, 199]],
***
*** [[191, 173, 159],
*** [191, 173, 159],
*** [191, 173, 159],
*** ...,
*** [223, 221, 209],
*** [221, 217, 206],
*** [218, 214, 203]],
***
*** ...,
***
*** [[221, 204, 196],
*** [218, 201, 193],
*** [212, 195, 187],
*** ...,
*** [202, 179, 161],
*** [218, 192, 177],
*** [224, 196, 182]],
***
*** [[217, 197, 190],
*** [206, 186, 179],
*** [188, 169, 162],
*** ...,
*** [224, 201, 183],
*** [226, 200, 185],
*** [205, 179, 164]],
***
*** [[213, 190, 184],
*** [197, 174, 168],
*** [172, 152, 145],
*** ...,
*** [193, 170, 152],
*** [173, 147, 132],
*** [154, 128, 113]]], dtype=uint8), 'mask': array([[[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
***
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
***
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
***
*** ...,
***
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
***
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
***
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]]], dtype=uint8)}, resize_mode='Crop and Resize', processor_res=0.5, threshold_a=0.5, threshold_b=0.5, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='ControlNet is more important', save_detected_map=True), ControlNetUnit(input_mode=<InputMode.SIMPLE: 'simple'>, use_preview_as_input=False, batch_image_dir='', batch_mask_dir='', batch_input_gallery=[], batch_mask_gallery=[], generated_image=array([[[ 9, 9, 9],
*** [ 9, 9, 9],
*** [ 9, 9, 9],
*** ...,
*** [ 34, 34, 34],
*** [ 33, 33, 33],
*** [ 32, 32, 32]],
***
*** [[ 9, 9, 9],
*** [ 9, 9, 9],
*** [ 10, 10, 10],
*** ...,
*** [ 34, 34, 34],
*** [ 33, 33, 33],
*** [ 32, 32, 32]],
***
*** [[ 10, 10, 10],
*** [ 10, 10, 10],
*** [ 10, 10, 10],
*** ...,
*** [ 35, 35, 35],
*** [ 34, 34, 34],
*** [ 33, 33, 33]],
***
*** ...,
***
*** [[248, 248, 248],
*** [249, 249, 249],
*** [249, 249, 249],
*** ...,
*** [195, 195, 195],
*** [195, 195, 195],
*** [195, 195, 195]],
***
*** [[250, 250, 250],
*** [250, 250, 250],
*** [251, 251, 251],
*** ...,
*** [196, 196, 196],
*** [196, 196, 196],
*** [196, 196, 196]],
***
*** [[250, 250, 250],
*** [251, 251, 251],
*** [251, 251, 251],
*** ...,
*** [197, 197, 197],
*** [197, 197, 197],
*** [197, 197, 197]]], dtype=uint8), mask_image=None, hr_option='Both', enabled=False, module='depth_midas', model='t2i-adapter_diffusers_xl_depth_midas [9c183166]', weight=1, image={'image': array([[[191, 173, 159],
*** [191, 173, 159],
*** [191, 173, 159],
*** ...,
*** [216, 214, 202],
*** [214, 210, 199],
*** [211, 207, 196]],
***
*** [[191, 173, 159],
*** [191, 173, 159],
*** [191, 173, 159],
*** ...,
*** [219, 217, 205],
*** [217, 213, 202],
*** [214, 210, 199]],
***
*** [[191, 173, 159],
*** [191, 173, 159],
*** [191, 173, 159],
*** ...,
*** [223, 221, 209],
*** [221, 217, 206],
*** [218, 214, 203]],
***
*** ...,
***
*** [[221, 204, 196],
*** [218, 201, 193],
*** [212, 195, 187],
*** ...,
*** [202, 179, 161],
*** [218, 192, 177],
*** [224, 196, 182]],
***
*** [[217, 197, 190],
*** [206, 186, 179],
*** [188, 169, 162],
*** ...,
*** [224, 201, 183],
*** [226, 200, 185],
*** [205, 179, 164]],
***
*** [[213, 190, 184],
*** [197, 174, 168],
*** [172, 152, 145],
*** ...,
*** [193, 170, 152],
*** [173, 147, 132],
*** [154, 128, 113]]], dtype=uint8), 'mask': array([[[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
***
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
***
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
***
*** ...,
***
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
***
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],
***
*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]]], dtype=uint8)}, resize_mode='Crop and Resize', processor_res=512, threshold_a=0.5, threshold_b=0.5, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), ControlNetUnit(input_mode=<InputMode.SIMPLE: 'simple'>, use_preview_as_input=False, batch_image_dir='', batch_mask_dir='', batch_input_gallery=[], batch_mask_gallery=[], generated_image=None, mask_image=None, hr_option='Both', enabled=False, module='None', model='None', weight=1, image=None, resize_mode='Crop and Resize', processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), False, 7, 1, 'Constant', 0, 'Constant', 0, 1, 'enable', 'MEAN', 'AD', 1, False, 1.01, 1.02, 0.99, 0.95, False, 0.5, 2, False, 256, 2, 0, False, False, 3, 2, 0, 0.35, True, 'bicubic', 'bicubic', False, 0, 'anisotropic', 0, 'reinhard', 100, 0, 'subtract', 0, 0, 'gaussian', 'add', 0, 100, 127, 0, 'hard_clamp', 5, 0, 'None', 'None', True, 'MultiDiffusion', 768, 768, 64, 4, False, False, False, '* `CFG Scale` should be 2 or lower.', True, True, '', '', True, 50, True, 1, 0, False, 4, 0.5, 'Linear', 'None', '<p style="margin-bottom:0.75em">Recommended settings: Sampling Steps: 80-100, Sampler: Euler a, Denoising strength: 0.8</p>', 128, 8, ['left', 'right', 'up', 'down'], 1, 0.05, 128, 4, 0, ['left', 'right', 'up', 'down'], False, False, 'positive', 'comma', 0, False, False, 'start', '', '<p style="margin-bottom:0.75em">Will upscale the image by the selected scale factor; use width and height sliders to set tile size</p>', 64, 0, 2, 1, '', [], 0, '', [], 0, '', [], True, False, False, False, False, False, False, 0, False) {}
Traceback (most recent call last):
File "E:\WebUI_Forge\webui\modules\call_queue.py", line 57, in f
res = list(func(*args, **kwargs))
TypeError: 'NoneType' object is not iterable
---Additional information
No response
Hello ?!?
BIG BUG