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Added Support of Xlabs controlnet to FluxControlNetInpaintPipeline #9770

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Merged
merged 6 commits into from
Oct 25, 2024
Merged

Added Support of Xlabs controlnet to FluxControlNetInpaintPipeline #9770

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c3b722e
added xlabs support
SahilCarterr Oct 25, 2024
a3ff6d9
Merge branch 'huggingface:main' into flux_controlnet_inpaint
SahilCarterr Oct 25, 2024
df4ef65
make style
SahilCarterr Oct 25, 2024
73e4165
Merge branch 'flux_controlnet_inpaint' of https://github.com/SahilCar…
SahilCarterr Oct 25, 2024
5ae9a50
Merge branch 'main' into flux_controlnet_inpaint
SahilCarterr Oct 25, 2024
262a64d
Merge branch 'main' into flux_controlnet_inpaint
SahilCarterr Oct 25, 2024
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61 changes: 34 additions & 27 deletions src/diffusers/pipelines/flux/pipeline_flux_controlnet_inpainting.py
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Original file line number Diff line number Diff line change
Expand Up @@ -930,19 +930,22 @@ def __call__(
)
height, width = control_image.shape[-2:]

# vae encode
control_image = self.vae.encode(control_image).latent_dist.sample()
control_image = (control_image - self.vae.config.shift_factor) * self.vae.config.scaling_factor

# pack
height_control_image, width_control_image = control_image.shape[2:]
control_image = self._pack_latents(
control_image,
batch_size * num_images_per_prompt,
num_channels_latents,
height_control_image,
width_control_image,
)
# xlab controlnet has a input_hint_block and instantx controlnet does not
controlnet_blocks_repeat = False if self.controlnet.input_hint_block is None else True
if self.controlnet.input_hint_block is None:
# vae encode
control_image = self.vae.encode(control_image).latent_dist.sample()
control_image = (control_image - self.vae.config.shift_factor) * self.vae.config.scaling_factor

# pack
height_control_image, width_control_image = control_image.shape[2:]
control_image = self._pack_latents(
control_image,
batch_size * num_images_per_prompt,
num_channels_latents,
height_control_image,
width_control_image,
)

# set control mode
if control_mode is not None:
Expand All @@ -952,7 +955,9 @@ def __call__(
elif isinstance(self.controlnet, FluxMultiControlNetModel):
control_images = []

for control_image_ in control_image:
# xlab controlnet has a input_hint_block and instantx controlnet does not
controlnet_blocks_repeat = False if self.controlnet.nets[0].input_hint_block is None else True
for i, control_image_ in enumerate(control_image):
control_image_ = self.prepare_image(
image=control_image_,
width=width,
Expand All @@ -964,19 +969,20 @@ def __call__(
)
height, width = control_image_.shape[-2:]

# vae encode
control_image_ = self.vae.encode(control_image_).latent_dist.sample()
control_image_ = (control_image_ - self.vae.config.shift_factor) * self.vae.config.scaling_factor

# pack
height_control_image, width_control_image = control_image_.shape[2:]
control_image_ = self._pack_latents(
control_image_,
batch_size * num_images_per_prompt,
num_channels_latents,
height_control_image,
width_control_image,
)
if self.controlnet.nets[0].input_hint_block is None:
# vae encode
control_image_ = self.vae.encode(control_image_).latent_dist.sample()
control_image_ = (control_image_ - self.vae.config.shift_factor) * self.vae.config.scaling_factor

# pack
height_control_image, width_control_image = control_image_.shape[2:]
control_image_ = self._pack_latents(
control_image_,
batch_size * num_images_per_prompt,
num_channels_latents,
height_control_image,
width_control_image,
)

control_images.append(control_image_)

Expand Down Expand Up @@ -1125,6 +1131,7 @@ def __call__(
img_ids=latent_image_ids,
joint_attention_kwargs=self.joint_attention_kwargs,
return_dict=False,
controlnet_blocks_repeat=controlnet_blocks_repeat,
)[0]

# compute the previous noisy sample x_t -> x_t-1
Expand Down
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