IOPaint/inpaint/model_manager.py

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new file: inpaint/__init__.py new file: inpaint/__main__.py new file: inpaint/api.py new file: inpaint/batch_processing.py new file: inpaint/benchmark.py new file: inpaint/cli.py new file: inpaint/const.py new file: inpaint/download.py new file: inpaint/file_manager/__init__.py new file: inpaint/file_manager/file_manager.py new file: inpaint/file_manager/storage_backends.py new file: inpaint/file_manager/utils.py new file: inpaint/helper.py new file: inpaint/installer.py new file: inpaint/model/__init__.py new file: inpaint/model/anytext/__init__.py new file: inpaint/model/anytext/anytext_model.py new file: inpaint/model/anytext/anytext_pipeline.py new file: inpaint/model/anytext/anytext_sd15.yaml new file: inpaint/model/anytext/cldm/__init__.py new file: inpaint/model/anytext/cldm/cldm.py new file: inpaint/model/anytext/cldm/ddim_hacked.py new file: inpaint/model/anytext/cldm/embedding_manager.py new file: inpaint/model/anytext/cldm/hack.py new file: inpaint/model/anytext/cldm/model.py new file: inpaint/model/anytext/cldm/recognizer.py new file: inpaint/model/anytext/ldm/__init__.py new file: inpaint/model/anytext/ldm/models/__init__.py new file: inpaint/model/anytext/ldm/models/autoencoder.py new file: inpaint/model/anytext/ldm/models/diffusion/__init__.py new file: inpaint/model/anytext/ldm/models/diffusion/ddim.py new file: inpaint/model/anytext/ldm/models/diffusion/ddpm.py new file: inpaint/model/anytext/ldm/models/diffusion/dpm_solver/__init__.py new file: inpaint/model/anytext/ldm/models/diffusion/dpm_solver/dpm_solver.py new file: inpaint/model/anytext/ldm/models/diffusion/dpm_solver/sampler.py new file: inpaint/model/anytext/ldm/models/diffusion/plms.py new file: inpaint/model/anytext/ldm/models/diffusion/sampling_util.py new file: inpaint/model/anytext/ldm/modules/__init__.py new file: inpaint/model/anytext/ldm/modules/attention.py new file: inpaint/model/anytext/ldm/modules/diffusionmodules/__init__.py new file: inpaint/model/anytext/ldm/modules/diffusionmodules/model.py new file: inpaint/model/anytext/ldm/modules/diffusionmodules/openaimodel.py new file: inpaint/model/anytext/ldm/modules/diffusionmodules/upscaling.py new file: inpaint/model/anytext/ldm/modules/diffusionmodules/util.py new file: inpaint/model/anytext/ldm/modules/distributions/__init__.py new file: inpaint/model/anytext/ldm/modules/distributions/distributions.py new file: inpaint/model/anytext/ldm/modules/ema.py new file: inpaint/model/anytext/ldm/modules/encoders/__init__.py new file: inpaint/model/anytext/ldm/modules/encoders/modules.py new file: inpaint/model/anytext/ldm/util.py new file: inpaint/model/anytext/main.py new file: inpaint/model/anytext/ocr_recog/RNN.py new file: inpaint/model/anytext/ocr_recog/RecCTCHead.py new file: inpaint/model/anytext/ocr_recog/RecModel.py new file: inpaint/model/anytext/ocr_recog/RecMv1_enhance.py new file: inpaint/model/anytext/ocr_recog/RecSVTR.py new file: inpaint/model/anytext/ocr_recog/__init__.py new file: inpaint/model/anytext/ocr_recog/common.py new file: inpaint/model/anytext/ocr_recog/en_dict.txt new file: inpaint/model/anytext/ocr_recog/ppocr_keys_v1.txt new file: inpaint/model/anytext/utils.py new file: inpaint/model/base.py new file: inpaint/model/brushnet/__init__.py new file: inpaint/model/brushnet/brushnet.py new file: inpaint/model/brushnet/brushnet_unet_forward.py new file: inpaint/model/brushnet/brushnet_wrapper.py new file: inpaint/model/brushnet/pipeline_brushnet.py new file: inpaint/model/brushnet/unet_2d_blocks.py new file: inpaint/model/controlnet.py new file: inpaint/model/ddim_sampler.py new file: inpaint/model/fcf.py new file: inpaint/model/helper/__init__.py new file: inpaint/model/helper/controlnet_preprocess.py new file: inpaint/model/helper/cpu_text_encoder.py new file: inpaint/model/helper/g_diffuser_bot.py new file: inpaint/model/instruct_pix2pix.py new file: inpaint/model/kandinsky.py new file: inpaint/model/lama.py new file: inpaint/model/ldm.py new file: inpaint/model/manga.py new file: inpaint/model/mat.py new file: inpaint/model/mi_gan.py new file: inpaint/model/opencv2.py new file: inpaint/model/original_sd_configs/__init__.py new file: inpaint/model/original_sd_configs/sd_xl_base.yaml new file: inpaint/model/original_sd_configs/sd_xl_refiner.yaml new file: inpaint/model/original_sd_configs/v1-inference.yaml new file: inpaint/model/original_sd_configs/v2-inference-v.yaml new file: inpaint/model/paint_by_example.py new file: inpaint/model/plms_sampler.py new file: inpaint/model/power_paint/__init__.py new file: inpaint/model/power_paint/pipeline_powerpaint.py new file: inpaint/model/power_paint/power_paint.py new file: inpaint/model/power_paint/power_paint_v2.py new file: inpaint/model/power_paint/powerpaint_tokenizer.py
2024-08-20 21:17:33 +02:00
from typing import List, Dict
import torch
from loguru import logger
import numpy as np
from inpaint.download import scan_models
from inpaint.helper import switch_mps_device
from inpaint.model import models, ControlNet, SD, SDXL
from inpaint.model.brushnet.brushnet_wrapper import BrushNetWrapper
from inpaint.model.power_paint.power_paint_v2 import PowerPaintV2
from inpaint.model.utils import torch_gc, is_local_files_only
from inpaint.schema import InpaintRequest, ModelInfo, ModelType
class ModelManager:
def __init__(self, name: str, device: torch.device, **kwargs):
self.name = name
self.device = device
self.kwargs = kwargs
self.available_models: Dict[str, ModelInfo] = {}
self.scan_models()
self.enable_controlnet = kwargs.get("enable_controlnet", False)
controlnet_method = kwargs.get("controlnet_method", None)
if (
controlnet_method is None
and name in self.available_models
and self.available_models[name].support_controlnet
):
controlnet_method = self.available_models[name].controlnets[0]
self.controlnet_method = controlnet_method
self.enable_brushnet = kwargs.get("enable_brushnet", False)
self.brushnet_method = kwargs.get("brushnet_method", None)
self.enable_powerpaint_v2 = kwargs.get("enable_powerpaint_v2", False)
self.model = self.init_model(name, device, **kwargs)
@property
def current_model(self) -> ModelInfo:
return self.available_models[self.name]
def init_model(self, name: str, device, **kwargs):
logger.info(f"Loading model: {name}")
if name not in self.available_models:
raise NotImplementedError(
f"Unsupported model: {name}. Available models: {list(self.available_models.keys())}"
)
model_info = self.available_models[name]
kwargs = {
**kwargs,
"model_info": model_info,
"enable_controlnet": self.enable_controlnet,
"controlnet_method": self.controlnet_method,
"enable_brushnet": self.enable_brushnet,
"brushnet_method": self.brushnet_method,
}
if model_info.support_controlnet and self.enable_controlnet:
return ControlNet(device, **kwargs)
if model_info.support_brushnet and self.enable_brushnet:
return BrushNetWrapper(device, **kwargs)
if model_info.support_powerpaint_v2 and self.enable_powerpaint_v2:
return PowerPaintV2(device, **kwargs)
if model_info.name in models:
return models[name](device, **kwargs)
if model_info.model_type in [
ModelType.DIFFUSERS_SD_INPAINT,
ModelType.DIFFUSERS_SD,
]:
return SD(device, **kwargs)
if model_info.model_type in [
ModelType.DIFFUSERS_SDXL_INPAINT,
ModelType.DIFFUSERS_SDXL,
]:
return SDXL(device, **kwargs)
raise NotImplementedError(f"Unsupported model: {name}")
@torch.inference_mode()
def __call__(self, image, mask, config: InpaintRequest):
"""
Args:
image: [H, W, C] RGB
mask: [H, W, 1] 255 means area to repaint
config:
Returns:
BGR image
"""
if config.enable_controlnet:
self.switch_controlnet_method(config)
if config.enable_brushnet:
self.switch_brushnet_method(config)
self.enable_disable_powerpaint_v2(config)
self.enable_disable_lcm_lora(config)
return self.model(image, mask, config).astype(np.uint8)
def scan_models(self) -> List[ModelInfo]:
available_models = scan_models()
self.available_models = {it.name: it for it in available_models}
return available_models
def switch(self, new_name: str):
if new_name == self.name:
return
old_name = self.name
old_controlnet_method = self.controlnet_method
self.name = new_name
if (
self.available_models[new_name].support_controlnet
and self.controlnet_method
not in self.available_models[new_name].controlnets
):
self.controlnet_method = self.available_models[new_name].controlnets[0]
try:
# TODO: enable/disable controlnet without reload model
del self.model
torch_gc()
self.model = self.init_model(
new_name, switch_mps_device(new_name, self.device), **self.kwargs
)
except Exception as e:
self.name = old_name
self.controlnet_method = old_controlnet_method
logger.info(f"Switch model from {old_name} to {new_name} failed, rollback")
self.model = self.init_model(
old_name, switch_mps_device(old_name, self.device), **self.kwargs
)
raise e
def switch_brushnet_method(self, config):
if not self.available_models[self.name].support_brushnet:
return
if (
self.enable_brushnet
and config.brushnet_method
and self.brushnet_method != config.brushnet_method
):
old_brushnet_method = self.brushnet_method
self.brushnet_method = config.brushnet_method
self.model.switch_brushnet_method(config.brushnet_method)
logger.info(
f"Switch Brushnet method from {old_brushnet_method} to {config.brushnet_method}"
)
elif self.enable_brushnet != config.enable_brushnet:
self.enable_brushnet = config.enable_brushnet
self.brushnet_method = config.brushnet_method
pipe_components = {
"vae": self.model.model.vae,
"text_encoder": self.model.model.text_encoder,
"unet": self.model.model.unet,
}
if hasattr(self.model.model, "text_encoder_2"):
pipe_components["text_encoder_2"] = self.model.model.text_encoder_2
self.model = self.init_model(
self.name,
switch_mps_device(self.name, self.device),
pipe_components=pipe_components,
**self.kwargs,
)
if not config.enable_brushnet:
logger.info("BrushNet Disabled")
else:
logger.info("BrushNet Enabled")
def switch_controlnet_method(self, config):
if not self.available_models[self.name].support_controlnet:
return
if (
self.enable_controlnet
and config.controlnet_method
and self.controlnet_method != config.controlnet_method
):
old_controlnet_method = self.controlnet_method
self.controlnet_method = config.controlnet_method
self.model.switch_controlnet_method(config.controlnet_method)
logger.info(
f"Switch Controlnet method from {old_controlnet_method} to {config.controlnet_method}"
)
elif self.enable_controlnet != config.enable_controlnet:
self.enable_controlnet = config.enable_controlnet
self.controlnet_method = config.controlnet_method
pipe_components = {
"vae": self.model.model.vae,
"text_encoder": self.model.model.text_encoder,
"unet": self.model.model.unet,
}
if hasattr(self.model.model, "text_encoder_2"):
pipe_components["text_encoder_2"] = self.model.model.text_encoder_2
self.model = self.init_model(
self.name,
switch_mps_device(self.name, self.device),
pipe_components=pipe_components,
**self.kwargs,
)
if not config.enable_controlnet:
logger.info("Disable controlnet")
else:
logger.info(f"Enable controlnet: {config.controlnet_method}")
def enable_disable_powerpaint_v2(self, config: InpaintRequest):
if not self.available_models[self.name].support_powerpaint_v2:
return
if self.enable_powerpaint_v2 != config.enable_powerpaint_v2:
self.enable_powerpaint_v2 = config.enable_powerpaint_v2
pipe_components = {"vae": self.model.model.vae}
self.model = self.init_model(
self.name,
switch_mps_device(self.name, self.device),
pipe_components=pipe_components,
**self.kwargs,
)
if config.enable_powerpaint_v2:
logger.info("Enable PowerPaintV2")
else:
logger.info("Disable PowerPaintV2")
def enable_disable_lcm_lora(self, config: InpaintRequest):
if self.available_models[self.name].support_lcm_lora:
# TODO: change this if load other lora is supported
lcm_lora_loaded = bool(self.model.model.get_list_adapters())
if config.sd_lcm_lora:
if not lcm_lora_loaded:
logger.info("Load LCM LORA")
self.model.model.load_lora_weights(
self.model.lcm_lora_id,
weight_name="pytorch_lora_weights.safetensors",
local_files_only=is_local_files_only(),
)
else:
logger.info("Enable LCM LORA")
self.model.model.enable_lora()
else:
if lcm_lora_loaded:
logger.info("Disable LCM LORA")
self.model.model.disable_lora()