TypeError: StableDiffusionControlNetPipeline.prepare_image() missing 1 required positional argument: 'do_classifier_free_guidance' #8
Description
pipe.to('cuda')
# generate image
generator = torch.manual_seed(0)
new_image = pipe(
text_prompt,
num_inference_steps=20,
generator=generator,
image=image,
control_image=canny_image,
controlnet_conditioning_scale = 0.5,
mask_image=mask_image
).images[0]
new_image.save('output/canny_result.png')
Thanks for your great work, by running the above code in notebook, I get some issues:
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ in <module>:5 │
│ │
│ 2 │
│ 3 # generate image │
│ 4 generator = torch.manual_seed(0) │
│ ❱ 5 new_image = pipe( │
│ 6 │ text_prompt, │
│ 7 │ num_inference_steps=20, │
│ 8 │ generator=generator, │
│ │
│ d:\App\miniconda\envs\aigc\lib\site-packages\torch\autograd\grad_mode.py:27 in decorate_context │
│ │
│ 24 │ │ @functools.wraps(func) │
│ 25 │ │ def decorate_context(*args, **kwargs): │
│ 26 │ │ │ with self.clone(): │
│ ❱ 27 │ │ │ │ return func(*args, **kwargs) │
│ 28 │ │ return cast(F, decorate_context) │
│ 29 │ │
│ 30 │ def _wrap_generator(self, func): │
│ │
│ c:\Users\Arthur\Downloads\ControlNetInpaint-main\ControlNetInpaint-main\src\pipeline_stable_diff │
│ usion_controlnet_inpaint.py:394 in __call__ │
│ │
│ 391 │ │ ) │
│ 392 │ │ │
│ 393 │ │ # 4. Prepare image │
│ ❱ 394 │ │ control_image = self.prepare_image( │
│ 395 │ │ │ control_image, │
│ 396 │ │ │ width, │
│ 397 │ │ │ height, │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
TypeError: StableDiffusionControlNetPipeline.prepare_image() missing 1 required positional argument:
'do_classifier_free_guidance'