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Qing
2023-12-24 15:32:27 +08:00
parent 0e5e16ba20
commit 371db2d771
31 changed files with 441 additions and 439 deletions
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26
lama_cleaner/model/controlnet.py
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@@ -17,14 +17,6 @@ from lama_cleaner.model.helper.cpu_text_encoder import CPUTextEncoderWrapper
from lama_cleaner.model.utils import get_scheduler
from lama_cleaner.schema import Config, ModelInfo, ModelType
# 为了兼容性
controlnet_name_map = {
"control_v11p_sd15_canny": "lllyasviel/control_v11p_sd15_canny",
"control_v11p_sd15_openpose": "lllyasviel/control_v11p_sd15_openpose",
"control_v11p_sd15_inpaint": "lllyasviel/control_v11p_sd15_inpaint",
"control_v11f1p_sd15_depth": "lllyasviel/control_v11f1p_sd15_depth",
}
class ControlNet(DiffusionInpaintModel):
name = "controlnet"
@@ -49,9 +41,6 @@ class ControlNet(DiffusionInpaintModel):
fp16 = not kwargs.get("no_half", False)
model_info: ModelInfo = kwargs["model_info"]
sd_controlnet_method = kwargs["sd_controlnet_method"]
sd_controlnet_method = controlnet_name_map.get(
sd_controlnet_method, sd_controlnet_method
)
self.model_info = model_info
self.sd_controlnet_method = sd_controlnet_method
@@ -113,12 +102,6 @@ class ControlNet(DiffusionInpaintModel):
**model_kwargs,
)
# https://huggingface.co/docs/diffusers/v0.7.0/en/api/pipelines/stable_diffusion#diffusers.StableDiffusionInpaintPipeline.enable_attention_slicing
self.model.enable_attention_slicing()
# https://huggingface.co/docs/diffusers/v0.7.0/en/optimization/fp16#memory-efficient-attention
if kwargs.get("enable_xformers", False):
self.model.enable_xformers_memory_efficient_attention()
if kwargs.get("cpu_offload", False) and use_gpu:
logger.info("Enable sequential cpu offload")
self.model.enable_sequential_cpu_offload(gpu_id=0)
@@ -162,10 +145,6 @@ class ControlNet(DiffusionInpaintModel):
scheduler = get_scheduler(config.sd_sampler, scheduler_config)
self.model.scheduler = scheduler
if config.sd_mask_blur != 0:
k = 2 * config.sd_mask_blur + 1
mask = cv2.GaussianBlur(mask, (k, k), 0)[:, :, np.newaxis]
img_h, img_w = image.shape[:2]
control_image = self._get_control_image(image, mask)
mask_image = PIL.Image.fromarray(mask[:, :, -1], mode="L")
@@ -190,8 +169,3 @@ class ControlNet(DiffusionInpaintModel):
output = (output * 255).round().astype("uint8")
output = cv2.cvtColor(output, cv2.COLOR_RGB2BGR)
return output
@staticmethod
def is_downloaded() -> bool:
# model will be downloaded when app start, and can't switch in frontend settings
return True