mirror of
https://github.com/invoke-ai/InvokeAI
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96 lines
3.2 KiB
Python
96 lines
3.2 KiB
Python
#!/usr/bin/env python3
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# Copyright (c) 2022 Lincoln D. Stein (https://github.com/lstein)
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# Before running stable-diffusion on an internet-isolated machine,
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# run this script from one with internet connectivity. The
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# two machines must share a common .cache directory.
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from transformers import CLIPTokenizer, CLIPTextModel
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import clip
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from transformers import BertTokenizerFast
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import sys
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import transformers
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import os
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import warnings
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import urllib.request
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transformers.logging.set_verbosity_error()
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# this will preload the Bert tokenizer fles
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print('preloading bert tokenizer...')
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tokenizer = BertTokenizerFast.from_pretrained('bert-base-uncased')
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print('...success')
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# this will download requirements for Kornia
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print('preloading Kornia requirements (ignore the deprecation warnings)...')
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with warnings.catch_warnings():
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warnings.filterwarnings('ignore', category=DeprecationWarning)
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import kornia
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print('...success')
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version = 'openai/clip-vit-large-patch14'
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print('preloading CLIP model (Ignore the deprecation warnings)...')
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sys.stdout.flush()
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tokenizer = CLIPTokenizer.from_pretrained(version)
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transformer = CLIPTextModel.from_pretrained(version)
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print('\n\n...success')
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# In the event that the user has installed GFPGAN and also elected to use
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# RealESRGAN, this will attempt to download the model needed by RealESRGANer
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gfpgan = False
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try:
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from realesrgan import RealESRGANer
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gfpgan = True
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except ModuleNotFoundError:
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pass
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if gfpgan:
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print('Loading models from RealESRGAN and facexlib')
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try:
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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')
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except Exception:
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import traceback
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print('Error loading ESRGAN:')
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print(traceback.format_exc())
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try:
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import urllib.request
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model_url = 'https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth'
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model_dest = 'src/gfpgan/experiments/pretrained_models/GFPGANv1.4.pth'
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if not os.path.exists(model_dest):
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print('downloading gfpgan model file...')
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urllib.request.urlretrieve(model_url,model_dest)
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except Exception:
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import traceback
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print('Error loading GFPGAN:')
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print(traceback.format_exc())
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print('...success')
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print('preloading CodeFormer model file...')
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try:
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import urllib.request
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model_url = 'https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth'
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model_dest = 'ldm/dream/restoration/codeformer/weights/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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urllib.request.urlretrieve(model_url,model_dest)
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except Exception:
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import traceback
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print('Error loading CodeFormer:')
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print(traceback.format_exc())
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print('...success')
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