mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
realesrgan and facexlib now download models to correct directory
- fix issue in which both realesrgan and facexlib were downloading weight files to source directory - cleaned up status reporting in load_models.py
This commit is contained in:
Lincoln Stein
parent
303431be89
commit
a1e5f17d1e
@ -1,7 +1,9 @@
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import torch
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import warnings
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import numpy as np
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import os
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from ldm.invoke.globals import Globals
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from PIL import Image
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@ -24,7 +26,7 @@ class ESRGAN():
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from realesrgan import RealESRGANer
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model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
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model_path = 'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth'
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model_path = os.path.join(Globals.root,'models/realesrgan/realesr-general-x4v3.pth')
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scale = 4
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bg_upsampler = RealESRGANer(
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@ -278,8 +278,8 @@ def download_weight_datasets(models:dict, access_token:str):
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for mod in models.keys():
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repo_id = Datasets[mod]['repo_id']
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filename = Datasets[mod]['file']
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print(os.path.join(Globals.root,Model_dir,Weights_dir))
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success = download_with_resume(
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print(os.path.join(Globals.root,Model_dir,Weights_dir), file=sys.stderr)
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success = hf_download_with_resume(
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repo_id=repo_id,
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model_dir=os.path.join(Globals.root,Model_dir,Weights_dir),
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model_name=filename,
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@ -301,7 +301,7 @@ def download_weight_datasets(models:dict, access_token:str):
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return successful
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#---------------------------------------------
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def download_with_resume(repo_id:str, model_dir:str, model_name:str, access_token:str=None)->bool:
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def hf_download_with_resume(repo_id:str, model_dir:str, model_name:str, access_token:str=None)->bool:
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model_dest = os.path.join(model_dir, model_name)
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os.makedirs(model_dir, exist_ok=True)
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@ -350,6 +350,23 @@ def download_with_resume(repo_id:str, model_dir:str, model_name:str, access_toke
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return False
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return True
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#---------------------------------------------
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def download_with_progress_bar(model_url:str, model_dest:str, label:str='the'):
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try:
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print(f'Installing {label} model file {model_url}...',end='',file=sys.stderr)
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if not os.path.exists(model_dest):
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os.makedirs(os.path.dirname(model_dest), exist_ok=True)
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print('',file=sys.stderr)
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request.urlretrieve(model_url,model_dest,ProgressBar(os.path.basename(model_dest)))
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print('...downloaded successfully', file=sys.stderr)
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else:
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print('...exists', file=sys.stderr)
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except Exception:
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print('...download failed')
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print(f'Error downloading {label} model')
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print(traceback.format_exc())
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#---------------------------------------------
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def update_config_file(successfully_downloaded:dict,opt:dict):
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config_file = opt.config_file or Default_config_file
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@ -421,6 +438,7 @@ def download_bert():
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#---------------------------------------------
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def download_from_hf(model_class:object, model_name:str):
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print('',file=sys.stderr) # to prevent tqdm from overwriting
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return model_class.from_pretrained(model_name,
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cache_dir=os.path.join(Globals.root,Model_dir,model_name),
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resume_download=True
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@ -428,34 +446,23 @@ def download_from_hf(model_class:object, model_name:str):
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#---------------------------------------------
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def download_clip():
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print('Installing CLIP model (ignore deprecation errors)...',end='',file=sys.stderr)
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print('Installing CLIP model (ignore deprecation errors)...',file=sys.stderr)
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version = 'openai/clip-vit-large-patch14'
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print('Tokenizer...',file=sys.stderr, end='')
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download_from_hf(CLIPTokenizer,version)
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print('Text model...',file=sys.stderr, end='')
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download_from_hf(CLIPTextModel,version)
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print('...success',file=sys.stderr)
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#---------------------------------------------
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def download_realesrgan():
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print('Installing models from RealESRGAN and facexlib (ignore deprecation errors)...',end='',file=sys.stderr)
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try:
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from realesrgan import RealESRGANer
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from realesrgan.archs.srvgg_arch import SRVGGNetCompact
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from facexlib.utils.face_restoration_helper import FaceRestoreHelper
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RealESRGANer(
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scale=4,
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model_path='https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth',
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model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
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)
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FaceRestoreHelper(1, det_model='retinaface_resnet50')
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print('...success',file=sys.stderr)
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except Exception:
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print('Error loading ESRGAN:')
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print(traceback.format_exc())
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print('Installing models from RealESRGAN...',file=sys.stderr)
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model_url = 'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth'
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model_dest = os.path.join(Globals.root,'models/realesrgan/realesr-general-x4v3.pth')
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download_with_progress_bar(model_url, model_dest, 'RealESRGAN')
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def download_gfpgan():
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print('Installing GFPGAN models...',end='',file=sys.stderr)
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print('Installing GFPGAN models...',file=sys.stderr)
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for model in (
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[
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'https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth',
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@ -471,35 +478,18 @@ def download_gfpgan():
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],
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):
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model_url,model_dest = model[0],os.path.join(Globals.root,model[1])
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try:
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if not os.path.exists(model_dest):
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print(f'Downloading gfpgan model file {model_url}...',end='')
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os.makedirs(os.path.dirname(model_dest), exist_ok=True)
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request.urlretrieve(model_url,model_dest,ProgressBar(os.path.basename(model_dest)))
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print('...success')
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except Exception:
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print('Error loading GFPGAN:')
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print(traceback.format_exc())
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print('...success',file=sys.stderr)
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download_with_progress_bar(model_url, model_dest, 'GFPGAN weights')
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#---------------------------------------------
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def download_codeformer():
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print('Installing CodeFormer model file...',end='',file=sys.stderr)
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try:
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model_url = 'https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth'
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model_dest = os.path.join(Globals.root,'models/codeformer/codeformer.pth')
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if not os.path.exists(model_dest):
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print('Downloading codeformer model file...')
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os.makedirs(os.path.dirname(model_dest), exist_ok=True)
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request.urlretrieve(model_url,model_dest,ProgressBar(os.path.basename(model_dest)))
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except Exception:
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print('Error loading CodeFormer:')
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print(traceback.format_exc())
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print('...success',file=sys.stderr)
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print('Installing CodeFormer model file...',file=sys.stderr)
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model_url = 'https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth'
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model_dest = os.path.join(Globals.root,'models/codeformer/codeformer.pth')
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download_with_progress_bar(model_url, model_dest, 'CodeFormer')
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#---------------------------------------------
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def download_clipseg():
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print('Installing clipseg model for text-based masking...',end='')
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print('Installing clipseg model for text-based masking...',end='', file=sys.stderr)
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import zipfile
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try:
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model_url = 'https://owncloud.gwdg.de/index.php/s/ioHbRzFx6th32hn/download'
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@ -528,11 +518,11 @@ def download_clipseg():
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except Exception:
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print('Error installing clipseg model:')
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print(traceback.format_exc())
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print('...success')
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print('...success',file=sys.stderr)
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#-------------------------------------
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def download_safety_checker():
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print('Installing safety model for NSFW content detection...',end='',file=sys.stderr)
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print('Installing safety model for NSFW content detection...',file=sys.stderr)
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try:
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from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
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from transformers import AutoFeatureExtractor
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@ -541,7 +531,9 @@ def download_safety_checker():
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print(traceback.format_exc())
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return
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safety_model_id = "CompVis/stable-diffusion-safety-checker"
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print('AutoFeatureExtractor...', end='',file=sys.stderr)
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download_from_hf(AutoFeatureExtractor,safety_model_id)
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print('StableDiffusionSafetyChecker...', end='',file=sys.stderr)
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download_from_hf(StableDiffusionSafetyChecker,safety_model_id)
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print('...success',file=sys.stderr)
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