add load local model
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@ -52,6 +52,10 @@ SD_CONTROLNET_HELP = """
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Run Stable Diffusion 1.5 inpainting model with Canny ControlNet control.
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Run Stable Diffusion 1.5 inpainting model with Canny ControlNet control.
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"""
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"""
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SD_LOCAL_MODEL_HELP = """
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Load Stable Diffusion 1.5 model(ckpt/safetensors) from local path.
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"""
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LOCAL_FILES_ONLY_HELP = """
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LOCAL_FILES_ONLY_HELP = """
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Use local files only, not connect to Hugging Face server. (sd/paint_by_example)
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Use local files only, not connect to Hugging Face server. (sd/paint_by_example)
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"""
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"""
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12
lama_cleaner/installer.py
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12
lama_cleaner/installer.py
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@ -0,0 +1,12 @@
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import subprocess
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import sys
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def install(package):
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subprocess.check_call([sys.executable, "-m", "pip", "install", package])
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def install_plugins_package():
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install("rembg")
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install("realesrgan")
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install("gfpgan")
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@ -1,3 +1,5 @@
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import gc
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import PIL.Image
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import PIL.Image
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import cv2
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import cv2
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import numpy as np
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import numpy as np
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@ -31,6 +33,37 @@ class CPUTextEncoderWrapper:
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return self.torch_dtype
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return self.torch_dtype
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def load_from_local_model(local_model_path, torch_dtype, disable_nsfw):
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from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
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load_pipeline_from_original_stable_diffusion_ckpt,
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)
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from diffusers.pipelines.stable_diffusion import StableDiffusionInpaintPipeline
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logger.info(f"Converting {local_model_path} to diffusers pipeline")
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pipe = load_pipeline_from_original_stable_diffusion_ckpt(
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local_model_path,
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num_in_channels=9,
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from_safetensors=local_model_path.endswith("safetensors"),
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device="cpu",
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)
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inpaint_pipe = StableDiffusionInpaintPipeline(
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vae=pipe.vae,
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text_encoder=pipe.text_encoder,
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tokenizer=pipe.tokenizer,
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unet=pipe.unet,
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scheduler=pipe.scheduler,
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safety_checker=None if disable_nsfw else pipe.safety_checker,
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feature_extractor=None if disable_nsfw else pipe.safety_checker,
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requires_safety_checker=not disable_nsfw,
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)
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del pipe
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gc.collect()
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return inpaint_pipe.to(torch_dtype)
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class SD(DiffusionInpaintModel):
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class SD(DiffusionInpaintModel):
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pad_mod = 8
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pad_mod = 8
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min_size = 512
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min_size = 512
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@ -43,6 +76,7 @@ class SD(DiffusionInpaintModel):
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model_kwargs = {
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model_kwargs = {
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"local_files_only": kwargs.get("local_files_only", kwargs["sd_run_local"])
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"local_files_only": kwargs.get("local_files_only", kwargs["sd_run_local"])
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}
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}
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disable_nsfw = False
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if kwargs["disable_nsfw"] or kwargs.get("cpu_offload", False):
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if kwargs["disable_nsfw"] or kwargs.get("cpu_offload", False):
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logger.info("Disable Stable Diffusion Model NSFW checker")
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logger.info("Disable Stable Diffusion Model NSFW checker")
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model_kwargs.update(
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model_kwargs.update(
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@ -52,15 +86,24 @@ class SD(DiffusionInpaintModel):
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requires_safety_checker=False,
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requires_safety_checker=False,
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)
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)
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)
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)
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disable_nsfw = True
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use_gpu = device == torch.device("cuda") and torch.cuda.is_available()
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use_gpu = device == torch.device("cuda") and torch.cuda.is_available()
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torch_dtype = torch.float16 if use_gpu and fp16 else torch.float32
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torch_dtype = torch.float16 if use_gpu and fp16 else torch.float32
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if kwargs.get("sd_local_model_path", None):
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self.model = load_from_local_model(
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kwargs["sd_local_model_path"],
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torch_dtype=torch_dtype,
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disable_nsfw=disable_nsfw,
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)
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else:
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self.model = StableDiffusionInpaintPipeline.from_pretrained(
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self.model = StableDiffusionInpaintPipeline.from_pretrained(
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self.model_id_or_path,
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self.model_id_or_path,
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revision="fp16" if use_gpu and fp16 else "main",
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revision="fp16" if use_gpu and fp16 else "main",
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torch_dtype=torch_dtype,
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torch_dtype=torch_dtype,
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use_auth_token=kwargs["hf_access_token"],
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use_auth_token=kwargs["hf_access_token"],
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**model_kwargs
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**model_kwargs,
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)
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)
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# https://huggingface.co/docs/diffusers/v0.7.0/en/api/pipelines/stable_diffusion#diffusers.StableDiffusionInpaintPipeline.enable_attention_slicing
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# https://huggingface.co/docs/diffusers/v0.7.0/en/api/pipelines/stable_diffusion#diffusers.StableDiffusionInpaintPipeline.enable_attention_slicing
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@ -38,6 +38,7 @@ def parse_args():
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"--sd-cpu-textencoder", action="store_true", help=SD_CPU_TEXTENCODER_HELP
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"--sd-cpu-textencoder", action="store_true", help=SD_CPU_TEXTENCODER_HELP
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)
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)
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parser.add_argument("--sd-controlnet", action="store_true", help=SD_CONTROLNET_HELP)
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parser.add_argument("--sd-controlnet", action="store_true", help=SD_CONTROLNET_HELP)
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parser.add_argument("--sd-local-model-path", default=None, help=SD_LOCAL_MODEL_HELP)
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parser.add_argument(
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parser.add_argument(
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"--local-files-only", action="store_true", help=LOCAL_FILES_ONLY_HELP
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"--local-files-only", action="store_true", help=LOCAL_FILES_ONLY_HELP
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)
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)
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@ -112,6 +113,10 @@ def parse_args():
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action="store_true",
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action="store_true",
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help=GIF_HELP,
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help=GIF_HELP,
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)
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)
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parser.add_argument(
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"--install-plugins-package",
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action="store_true",
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)
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#########
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#########
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# useless args
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# useless args
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@ -129,6 +134,11 @@ def parse_args():
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# collect system info to help debug
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# collect system info to help debug
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dump_environment_info()
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dump_environment_info()
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if args.install_plugins_package:
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from lama_cleaner.installer import install_plugins_package
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install_plugins_package()
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exit()
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if args.config_installer:
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if args.config_installer:
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if args.installer_config is None:
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if args.installer_config is None:
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@ -165,6 +175,16 @@ def parse_args():
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if args.model not in SD15_MODELS:
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if args.model not in SD15_MODELS:
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logger.warning(f"--sd_controlnet only support {SD15_MODELS}")
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logger.warning(f"--sd_controlnet only support {SD15_MODELS}")
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if args.sd_local_model_path and args.model == "sd1.5":
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if not os.path.exists(args.sd_local_model_path):
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parser.error(
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f"invalid --sd-local-model-path: {args.sd_local_model_path} not exists"
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)
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if not os.path.isfile(args.sd_local_model_path):
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parser.error(
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f"invalid --sd-local-model-path: {args.sd_local_model_path} is a directory"
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)
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os.environ["U2NET_HOME"] = DEFAULT_MODEL_DIR
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os.environ["U2NET_HOME"] = DEFAULT_MODEL_DIR
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if args.model_dir and args.model_dir is not None:
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if args.model_dir and args.model_dir is not None:
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if os.path.isfile(args.model_dir):
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if os.path.isfile(args.model_dir):
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@ -1,10 +1,12 @@
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#!/usr/bin/env python3
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#!/usr/bin/env python3
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import os
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os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
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import imghdr
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import imghdr
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import io
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import io
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import logging
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import logging
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import multiprocessing
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import multiprocessing
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import os
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import random
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import random
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import time
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import time
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from pathlib import Path
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from pathlib import Path
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@ -527,6 +529,7 @@ def main(args):
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disable_nsfw=args.sd_disable_nsfw or args.disable_nsfw,
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disable_nsfw=args.sd_disable_nsfw or args.disable_nsfw,
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sd_cpu_textencoder=args.sd_cpu_textencoder,
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sd_cpu_textencoder=args.sd_cpu_textencoder,
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sd_run_local=args.sd_run_local,
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sd_run_local=args.sd_run_local,
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sd_local_model_path=args.sd_local_model_path,
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local_files_only=args.local_files_only,
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local_files_only=args.local_files_only,
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cpu_offload=args.cpu_offload,
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cpu_offload=args.cpu_offload,
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enable_xformers=args.sd_enable_xformers or args.enable_xformers,
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enable_xformers=args.sd_enable_xformers or args.enable_xformers,
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@ -1,3 +1,6 @@
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import os
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os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
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from pathlib import Path
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from pathlib import Path
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import pytest
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import pytest
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@ -202,3 +205,37 @@ def test_runway_sd_1_5_cpu_offload(sd_device, strategy, sampler):
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mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
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mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
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)
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)
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@pytest.mark.parametrize("sd_device", ["cuda", "mps"])
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@pytest.mark.parametrize("sampler", [SDSampler.uni_pc])
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def test_local_file_path(sd_device, sampler):
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if sd_device == "cuda" and not torch.cuda.is_available():
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return
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sd_steps = 1 if sd_device == "cpu" else 50
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model = ModelManager(
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name="sd1.5",
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device=torch.device(sd_device),
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hf_access_token="",
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sd_run_local=True,
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disable_nsfw=True,
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sd_cpu_textencoder=False,
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cpu_offload=True,
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sd_local_model_path="/Users/cwq/data/models/sd-v1-5-inpainting.ckpt",
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)
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cfg = get_config(
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HDStrategy.ORIGINAL,
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prompt="a fox sitting on a bench",
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sd_steps=sd_steps,
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)
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cfg.sd_sampler = sampler
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name = f"device_{sd_device}_{sampler}"
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assert_equal(
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model,
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cfg,
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f"sd_local_model_{name}.png",
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img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
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mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
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)
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@ -6,9 +6,11 @@ set PATH=C:\Windows\System32;%PATH%
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@call conda-unpack
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@call conda-unpack
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@call conda install -y cudatoolkit=11.3
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@call conda install -y -c conda-forge cudatoolkit=11.7
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@call pip install torch==1.12.1+cu113 --extra-index-url https://download.pytorch.org/whl/cu113
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@call pip install torch==1.13.1+cu117 --extra-index-url https://download.pytorch.org/whl/cu117
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@call pip install xformers
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@call pip3 install -U lama-cleaner
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@call pip3 install -U lama-cleaner
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@call lama-cleaner --install-plugins-package
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@call lama-cleaner --config-installer --installer-config %0\..\installer_config.json
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@call lama-cleaner --config-installer --installer-config %0\..\installer_config.json
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