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{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"\n## NovelAi Stable Diffusion - webui AI绘画项目 （完全免费，无需显卡）\n**torch: 2.0.0+cu118 • xformers: 0.0.19**\n\n# <span style=\"color:red; font-weight:bold;\">有问题请加qq群632428790 (917/2000)</span>\n### 急需一名宣传人员，无偿，会做B站视频就行\n## <span style=\"color:red; font-weight:bold;\"> 拿我云端倒卖的，死个妈先，臭不要脸。早点死掉</span>\n## <span style=\"color:red; font-weight:bold;\"> 若您是通过付费渠道获得的此笔记，请立即退款</span>","metadata":{}},{"cell_type":"markdown","source":"## SD云端部署脚本使用教程：https://www.kaggle.com/code/at2020dead/novelai-stable-diffusion/notebook \n## 不会代码没关系，看教程就行了","metadata":{}},{"cell_type":"markdown","source":"\n<div class=\"alert alert-block alert-info\" style=\"font-size:14px; font-family:verdana;\">\n 📌 2022年11月18日: Crtated By Yiyiooo & Loading\n</div>\n最近更新日志：\n<div class=\"alert alert-block alert-info\" style=\"font-size:14px; font-family:verdana;\">\n 2023年3月5日更新：现在支持通过下载链接上传模型了，省去了下载模型后再上传后的麻烦.（）\n</div>\n<div class=\"alert alert-block alert-info\" style=\"font-size:14px; font-family:verdana;\">\n 2023年5月15日更新：现在可以双开webui了，可以双线程跑图（GPU请选择 T4 x2 ， 将use2设置为True）\n</div>\n<div class=\"alert alert-block alert-info\" style=\"font-size:14px; font-family:verdana;\">\n 2023年5月15日更新：更新了多线程启动，启动速度更快一些\n</div>\n<div class=\"alert alert-block alert-info\" style=\"font-size:14px; font-family:verdana;\">\n 2023年6月6日更新：更新了xformers版本，生成速度更快一些\n</div>","metadata":{}},{"cell_type":"markdown","source":"# 注意事项/WARNING：\n- ### 1.将设置中的PERSISTENCE改为Files Only方便下次打开提高启动速度、\n- ### 2.检测到出现涩图会容易导致封号(听说Save Version运行不会封号？)\n- ### 3.如果不能启动，请新建一个notebook并且重新导入\n- ### 4.若出现BUG，请跟我们反馈","metadata":{}},{"cell_type":"markdown","source":"## Ai绘画模型下载站：\n## [Civitai](http://civitai.com) （C站）\n \n### [huggingface](http://huggingface.co)\n# 友情合作 \n### [pix.ink](http://pix.ink) # 片绘","metadata":{}},{"cell_type":"markdown","source":"----","metadata":{}},{"cell_type":"markdown","source":"# > <span style=\"color:green; font-weight:;\"> Webui基础配置 </span>","metadata":{}},{"cell_type":"code","source":"# True 表示是 ， False 表示否\n# 安装目录\ninstall_path=\"/kaggle/working\" #或者/kaggle\nupdata_webui = False #是否开机自动更新webui\n\n# 重置变量 会删掉sd_webui重新安装\nreLoad = True\nupdata_webui = False\n\n#清理和打包生成的图片\nzip_output=True\nclear_output=True\n#打包环境减少下次启动时\nuse_zip_venv = False\n\n# 使用huggingface保存和载入webui配置文件\nhuggingface_use = True\nhuggingface_token_file = '/kaggle/input/tenkens/hugfacetoken.txt'\nhuggiingface_repo_id = 'ACCA225/sdconfig'\n# 将会同步的文件\nyun_files = [\n'ui-config.json',\n'config.json',\n'styles.csv'\n]","metadata":{"execution":{"iopub.status.busy":"2023-07-14T11:15:24.213586Z","iopub.execute_input":"2023-07-14T11:15:24.214768Z","iopub.status.idle":"2023-07-14T11:15:24.231248Z","shell.execute_reply.started":"2023-07-14T11:15:24.214722Z","shell.execute_reply":"2023-07-14T11:15:24.229480Z"},"trusted":true},"execution_count":1,"outputs":[]},{"cell_type":"markdown","source":"------","metadata":{}},{"cell_type":"markdown","source":"# > <span style=\"color:green; font-weight:;\">插件，模型地址 （添加模型在此代码单元格修改）</span>","metadata":{}},{"cell_type":"code","source":"#模型和插件\n\n# 插件列表： git仓库地址\n# 不需要的插件在前面加 # ，插件地址之间需要用英语逗号隔开\nextensions = [\n 'https://github.com/Elldreth/loopback_scaler',\n 'https://github.com/jexom/sd-webui-depth-lib',\n 'https://github.com/AlUlkesh/stable-diffusion-webui-images-browser', #图库浏览器\n 'https://github.com/camenduru/sd-civitai-browser', #C站助手\n 'https://github.com/Mikubill/sd-webui-controlnet', #控制网插件，神器！！\n 'https://github.com/nonnonstop/sd-webui-3d-open-pose-editor', # 3D openpose，可以让你的老婆摆出你想要的姿势\n 'https://github.com/2575044704/stable-diffusion-webui-localization-zh_CN2', #汉化\n 'https://github.com/opparco/stable-diffusion-webui-two-shot', #潜变量成对\n #'https://github.com/minicacas/stable-diffusion-webui-composable-lora',\n 'https://github.com/DominikDoom/a1111-sd-webui-tagcomplete', #tag自动补全\n #'https://github.com/pkuliyi2015/multidiffusion-upscaler-for-automatic1111', #分块vae\n #'https://github.com/KohakuBlueleaf/a1111-sd-webui-locon',\n 'https://github.com/hnmr293/sd-webui-cutoff', #Cutoff\n 'https://github.com/hako-mikan/sd-webui-lora-block-weight', #Lora分层\n 'https://github.com/butaixianran/Stable-Diffusion-Webui-Civitai-Helper', #C站助手\n 'https://github.com/catppuccin/stable-diffusion-webui', #UI修改，推荐\n #'https://github.com/Nevysha/Cozy-Nest',\n 'https://github.com/Scholar01/sd-webui-mov2mov', #AI视频转视频\n 'https://github.com/toriato/stable-diffusion-webui-wd14-tagger', #WD14打标器\n 'https://github.com/KohakuBlueleaf/a1111-sd-webui-lycoris', #LyCORIS插件，Lora升级版\n 'https://github.com/deforum-art/sd-webui-deforum', #Deform，AI视频\n #'https://github.com/zanllp/sd-webui-infinite-image-browsing', #云端用不了\n 'https://github.com/vladmandic/sd-extension-system-info', #系统信息\n '\thttps://github.com/d8ahazard/sd_dreambooth_extension', #Dreambooth训练\n]\n\n# Stable Diffusion模型请放在这里（不用填模型的文件名，只填模型的目录即可）\nsd_model = [\n#'/kaggle/input/cetus-mix/',\n#'/kaggle/input/aom3ackpt',\n'/kaggle/input/9527-fp16',\n#'/kaggle/input/dalcefo-painting',\n ]\n# Stable Diffusion模型下载链接放这里\nsd_model_urls=[\n#GhostMix_v1.2\n'https://civitai.com/api/download/models/59685',\n#Counterfeit-V3.0\n'https://civitai.com/api/download/models/57618',\n'https://huggingface.co/datasets/sukaka/sd_models_fp16/resolve/main/cetusMix_Coda2.safetensors',\n'https://huggingface.co/datasets/sukaka/sd_models_fp16/resolve/main/cetusMix_Version35.safetensors',\n'https://huggingface.co/datasets/ACCC1380/private-model/resolve/main/zx-A-9-half.safetensors',\n#Null\n'https://civitai.com/api/download/models/112251',\n]\n\n# VAE模型请放在这里（不用填模型的文件名，只填模型的目录即可）\nvae_model = []\n#VAE模型下载链接放这里\nvae_model_urls=[\n'https://huggingface.co/datasets/sukaka/sd_models_fp16/resolve/main/clearvae.vae.pt',\n'https://huggingface.co/dector/vae-840000/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt',\n'https://huggingface.co/WarriorMama777/OrangeMixs/resolve/main/VAEs/orangemix.vae.pt'\n]\n\n# Lora模型的数据集路径请写在这里：\nlora_model = [\n#'/kaggle/input/lora-1',\n] \n# Lora模型下载链接放这里\nlora_model_urls=[\n#墨心\n'https://civitai.com/api/download/models/14856',\n#山楂糕\n'https://civitai.com/api/download/models/41580',\n#细节调整\n'https://civitai.com/api/download/models/62833'\n]\n# Lycoris和loha模型的数据集路径请写在这里：\nlyco_model = [\n#'/kaggle/input/lora-1',\n] \n# Lycoris和loha模型下载链接放这里\nlyco_model_urls=[\n#FilmGirl 胶片风\n'https://civitai.com/api/download/models/75069',\n#Teacher clothes 教师衣服\n\"https://civitai.com/api/download/models/65426\",\n#伪日光\n'https://civitai.com/api/download/models/71235',\n]\n\n# ControlNet模型data请放在这里：\ncn_model = [\n]\n# controlnet模型下载链接放这里\ncn_model_urls = [\n'https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11e_sd15_ip2p_fp16.safetensors',\n'https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11e_sd15_shuffle_fp16.safetensors',\n'https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11f1p_sd15_depth_fp16.safetensors',\n'https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_canny_fp16.safetensors', #硬边缘检测\n'https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_inpaint_fp16.safetensors',\n'https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_lineart_fp16.safetensors',\n'https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_mlsd_fp16.safetensors',\n'https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_normalbae_fp16.safetensors',\n'https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_openpose_fp16.safetensors', #姿态检测\n'https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_scribble_fp16.safetensors',\n'https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_softedge_fp16.safetensors',\n'https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15s2_lineart_anime_fp16.safetensors', #线稿\n'https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11u_sd15_tile_fp16.safetensors', #分块\n'https://huggingface.co/DionTimmer/controlnet_qrcode-control_v1p_sd15/resolve/main/control_v1p_sd15_qrcode.safetensors', # 艺术二维码(神器！！)\n]\n\n# Hypernetworks超网络模型路径请放在这里：\nhypernetworks_model = []\n#Hypernetworks超网络模型下载链接请放在这里\nhypernetworks_model_urls = []\n\n#放大算法路径请放在这里\nESRGAN = []\n#放大算法链接请放在这里\nESRGAN_urls = [\n'https://huggingface.co/FacehugmanIII/4x_foolhardy_Remacri/resolve/main/4x_foolhardy_Remacri.pth',\n'https://huggingface.co/konohashinobi4/4xAnimesharp/resolve/main/4x-AnimeSharp.pth',\n'https://huggingface.co/lokCX/4x-Ultrasharp/resolve/main/4x-UltraSharp.pth',\n]\n\n# embeddings（pt文件）请放在这里:\nembeddings_model = [\n'/kaggle/input/bad-embedding',\n] \n# embeddings（pt文件）下载链接请放在这里:\nembeddings_model_urls=[\n'https://huggingface.co/datasets/sukaka/sd_configs/resolve/main/%E4%BA%BA%E4%BD%93%E4%BF%AE%E6%AD%A3/EasyNegative.pt',\n'https://huggingface.co/datasets/sukaka/sd_configs/resolve/main/%E4%BA%BA%E4%BD%93%E4%BF%AE%E6%AD%A3/bad-artist-anime.pt',\n'https://huggingface.co/datasets/sukaka/sd_configs/resolve/main/%E4%BA%BA%E4%BD%93%E4%BF%AE%E6%AD%A3/bad-hands-5.pt',\n'https://huggingface.co/datasets/sukaka/sd_configs/resolve/main/%E4%BA%BA%E4%BD%93%E4%BF%AE%E6%AD%A3/bad_prompt_version2.pt',\n'https://huggingface.co/datasets/sukaka/sd_configs/resolve/main/%E4%BA%BA%E4%BD%93%E4%BF%AE%E6%AD%A3/bad-image-v2-39000.pt',\n'https://huggingface.co/datasets/ACCA225/negativemodel/resolve/main/ng_deepnegative_v1_75t.pt',\n'https://huggingface.co/datasets/ACCA225/negativemodel/resolve/main/badhand-v4.pt',\n]\n\n#script文件导入\nscripts = []\n#script文件下载链接导入\nscripts_urls = [\n#'https://huggingface.co/datasets/sukaka/sd_configs/resolve/main/repositories/k-diffusion/k_diffusion/sampling.py'\n]\n\n#tag词库文件导入\ntags = []\n#tag词库文件下载链接导入\ntags_urls=[\n\"https://huggingface.co/datasets/sukaka/sd_configs/resolve/main/danbooru.zh_CN.csv\",\n]\n","metadata":{"execution":{"iopub.status.busy":"2023-07-14T11:15:24.238992Z","iopub.execute_input":"2023-07-14T11:15:24.239752Z","iopub.status.idle":"2023-07-14T11:15:24.259466Z","shell.execute_reply.started":"2023-07-14T11:15:24.239715Z","shell.execute_reply":"2023-07-14T11:15:24.258400Z"},"trusted":true},"execution_count":2,"outputs":[]},{"cell_type":"markdown","source":"------","metadata":{}},{"cell_type":"markdown","source":"# > <span style=\"color:green; font-weight:;\"> 内网穿透，Webui启动参数设置</span>","metadata":{}},{"cell_type":"code","source":"#ngrok穿透\nngrok_use = True\nngrokTokenFile='/kaggle/input/tenkens/Authtoken.txt' # 非必填 存放ngrokToken的文件的路径\n#Frp 内网穿透\nuse_frpc = False\nfrpconfigfile = '/kaggle/input/tenkens/7860.ini' # 非必填 frp 配置文件，本地端口 7860\n#ready-squids-thank.loca.lt 内网穿透 (推荐)\nlocaltunnel = True\n# 启动时默认加载的模型名称 填模型名称，名称建议带上文件名后缀\nusedCkpt = 'zx-A-9-half.safetensors'\n\n'''\n可选的启动参数见笔记的最底部附录！！！！这里与秋叶的启动器不同的是，这里的启动参数需要你自己填上去，附录中每个启动参数都有对应作用\n'''\n#启动参数（args）\nargs = [\n '--share', #开启公网访问\n '--xformers', # 强制使用 xformers 优化\n '--lowram', #低内存优化\n '--no-hashing', #取消哈希计算值\n '--disable-nan-check',\n '--enable-insecure-extension-access',\n '--disable-console-progressbars',\n '--enable-console-prompts',\n '--no-gradio-queue',\n '--no-half-vae', #VAE开启全精度\n '--api', #搭建QQ画图机器人或者开AI画图网站接入SD要开启这个\n #'--listen', # 在Kaggle里没用\n f'--lyco-dir {install_path}/stable-diffusion-webui/models/lyco',\n]\n\n\n","metadata":{"execution":{"iopub.status.busy":"2023-07-14T11:15:24.261775Z","iopub.execute_input":"2023-07-14T11:15:24.262636Z","iopub.status.idle":"2023-07-14T11:15:24.273105Z","shell.execute_reply.started":"2023-07-14T11:15:24.262593Z","shell.execute_reply":"2023-07-14T11:15:24.271990Z"},"trusted":true},"execution_count":3,"outputs":[]},{"cell_type":"markdown","source":"-------","metadata":{}},{"cell_type":"markdown","source":"# > <span style=\"color:green; font-weight:;\">Webui 双开设置</span>","metadata":{}},{"cell_type":"code","source":"use2 = False #是否开启两个webui， Kaggle的GPU选项必须是 T4 x2， 使用两张卡一起跑图","metadata":{"execution":{"iopub.status.busy":"2023-07-14T11:15:24.289174Z","iopub.execute_input":"2023-07-14T11:15:24.290024Z","iopub.status.idle":"2023-07-14T11:15:24.296670Z","shell.execute_reply.started":"2023-07-14T11:15:24.289968Z","shell.execute_reply":"2023-07-14T11:15:24.295587Z"},"trusted":true},"execution_count":4,"outputs":[]},{"cell_type":"code","source":"'''\nuse2必须设置为True下列配置才生效\n'''\n#ngrok穿透\nngrok_use1 = True\nngrokTokenFile1='/kaggle/input/tenkens/Authtoken1.txt' # 非必填 存放ngrokToken的文件的路径\n#Frp 内网穿透\nuse_frpc1 = False\nfrpconfigfile1 = '/kaggle/input/tenkens/7861.ini' # 非必填 frp 配置文件，本地端口 7860\n\n#第二个webui使用的模型\nusedCkpt1 = 'cetusMix_Coda2.safetensors'\n\n#启动参数\nargs1 = [\n '--share',\n '--xformers',\n '--lowram',\n '--no-hashing',\n '--disable-nan-check',\n '--enable-insecure-extension-access',\n '--disable-console-progressbars',\n '--enable-console-prompts',\n '--no-gradio-queue',\n '--no-half-vae',\n '--api',\n f'--lyco-dir {install_path}/stable-diffusion-webui/models/lyco',\n]","metadata":{"execution":{"iopub.status.busy":"2023-07-14T11:15:24.372736Z","iopub.execute_input":"2023-07-14T11:15:24.373443Z","iopub.status.idle":"2023-07-14T11:15:24.383850Z","shell.execute_reply.started":"2023-07-14T11:15:24.373404Z","shell.execute_reply":"2023-07-14T11:15:24.382867Z"},"trusted":true},"execution_count":5,"outputs":[]},{"cell_type":"markdown","source":"# > <span style=\"color:green; font-weight:;\">功能函数，请勿更改</span>","metadata":{}},{"cell_type":"code","source":"#使用的库\nfrom pathlib import Path\nimport subprocess\nimport pandas as pd\nimport shutil\nimport os\nimport time\nimport re\nimport gc\nimport requests\nimport zipfile\nimport threading\nimport time\nimport socket\nfrom concurrent.futures import ProcessPoolExecutor\nos.environ['install_path'] = install_path","metadata":{"execution":{"iopub.status.busy":"2023-07-14T11:15:24.386041Z","iopub.execute_input":"2023-07-14T11:15:24.387160Z","iopub.status.idle":"2023-07-14T11:15:24.409051Z","shell.execute_reply.started":"2023-07-14T11:15:24.387117Z","shell.execute_reply":"2023-07-14T11:15:24.407833Z"},"trusted":true},"execution_count":6,"outputs":[]},{"cell_type":"code","source":"#功能函数，内存优化\ndef libtcmalloc():\n if os.path.exists('/kaggle/temp'):\n os.chdir('/kaggle')\n os.chdir('temp')\n os.environ[\"LD_PRELOAD\"] = \"libtcmalloc.so\"\n print('内存优化已安装')\n else:\n \n if use_frpc:\n !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/datasets/ACCA225/Frp/resolve/main/frpc -d /kaggle/working/frpc -o frpc\n os.system('pip install -q pyngrok ')\n os.chdir('/kaggle')\n os.makedirs('temp', exist_ok=True)\n os.chdir('temp')\n os.system('wget -qq http://launchpadlibrarian.net/367274644/libgoogle-perftools-dev_2.5-2.2ubuntu3_amd64.deb')\n os.system('wget -qq https://launchpad.net/ubuntu/+source/google-perftools/2.5-2.2ubuntu3/+build/14795286/+files/google-perftools_2.5-2.2ubuntu3_all.deb')\n os.system('wget -qq https://launchpad.net/ubuntu/+source/google-perftools/2.5-2.2ubuntu3/+build/14795286/+files/libtcmalloc-minimal4_2.5-2.2ubuntu3_amd64.deb')\n os.system('wget -qq https://launchpad.net/ubuntu/+source/google-perftools/2.5-2.2ubuntu3/+build/14795286/+files/libgoogle-perftools4_2.5-2.2ubuntu3_amd64.deb')\n os.system('apt install -qq libunwind8-dev -y')\n !dpkg -i *.deb\n os.environ[\"LD_PRELOAD\"] = \"libtcmalloc.so\"\n !rm *.deb\n print('内存优化已安装')","metadata":{"execution":{"iopub.status.busy":"2023-07-14T11:15:24.413221Z","iopub.execute_input":"2023-07-14T11:15:24.416514Z","iopub.status.idle":"2023-07-14T11:15:24.438241Z","shell.execute_reply.started":"2023-07-14T11:15:24.416481Z","shell.execute_reply":"2023-07-14T11:15:24.437067Z"},"trusted":true},"execution_count":7,"outputs":[]},{"cell_type":"markdown","source":"-------------------","metadata":{}},{"cell_type":"markdown","source":"# > <span style=\"color:green; font-weight:;\">下载函数，请勿更改</span>","metadata":{}},{"cell_type":"code","source":" import os\n import re\n def putDownloadFile(url:str,distDir:str,file_name:str=None):\n if re.match(r'^[^:]+:(https?|ftps?)://', url, flags=0):\n file_name = re.findall(r'^[^:]+:',url)[0][:-1]\n url = url[len(file_name)+1:]\n if not re.match(r'^(https?|ftps?)://',url):\n return\n file_name = re.sub(r'\\s+','_',file_name or '')\n dir = str(hash(url)).replace('-','')\n down_dir = f'{install_path}/down_cache/{dir}'\n !mkdir -p {down_dir}\n return [url,file_name,distDir,down_dir]\n\n def get_file_size_in_gb(file_path):\n size_in_bytes = Path(file_path).stat().st_size\n size_in_gb = size_in_bytes / (1024 ** 3)\n return '%.2f' % size_in_gb\n \n\n def startDownloadFiles(download_list):\n print('下载列表:\\n','\\n'.join([f'{item[0]} -> {item[2]}/{item[1]}' for item in download_list]))\n dist_list = []\n for dow_f in download_list:\n !mkdir -p {dow_f[3]}\n print('下载 名称：',dow_f[1],'url：',dow_f[0])\n output_file = f' -O {dow_f[3]}/{dow_f[1]}'\n if len(os.listdir(dow_f[3])) > 0:\n continue\n os.system(f\"wget {dow_f[0]} --tries=3 --timeout=60 -P {dow_f[3]} {output_file if len(dow_f[1]) > 0 else ''} -o {install_path}/down_cache/log.log\")\n if len(os.listdir(dow_f[3])) == 0:\n print('下载出错：',dow_f[0])\n continue\n file_name = os.listdir(dow_f[3])[0]\n !mkdir -p {dow_f[2]}\n down_file_path = f'{dow_f[3]}/{file_name}'\n if Path(down_file_path).is_symlink():\n down_file_path = os.readlink(down_file_path)\n print('文件真实地址：'+down_file_path)\n if not Path(down_file_path).exists():\n print('文件异常')\n continue\n print(f'文件大小：{get_file_size_in_gb(down_file_path)}G')\n dist_path = f'{dow_f[2]}/{file_name}'\n dist_path = dist_path.replace('%20',' ').strip().replace(' ','_')\n print(f'移动文件 {down_file_path} -> {dist_path}')\n os.system(f'ln -f \"{down_file_path}\" \"{dist_path}\"')\n if dow_f[2] not in dist_list:\n dist_list.append(dow_f[2])\n for dist_dir in dist_list:\n print(dist_dir,os.listdir(dist_dir))\n","metadata":{"execution":{"iopub.status.busy":"2023-07-14T11:15:24.439762Z","iopub.execute_input":"2023-07-14T11:15:24.440347Z","iopub.status.idle":"2023-07-14T11:15:24.484768Z","shell.execute_reply.started":"2023-07-14T11:15:24.440313Z","shell.execute_reply":"2023-07-14T11:15:24.483635Z"},"trusted":true},"execution_count":8,"outputs":[]},{"cell_type":"markdown","source":"### > <span style=\"color:green; font-weight:;\">SD download & venv Download ： version: v1.4.0 • python: 3.10.6 • torch: 2.0.1+cu118 • xformers: 0.0.20</span>","metadata":{}},{"cell_type":"code","source":"\ndef unzip_file(src: str, dest: str = '/kaggle/outputs'):\n if os.path.exists(src):\n with zipfile.ZipFile(src, 'r') as zip_ref:\n for member in zip_ref.namelist():\n filename = os.path.basename(member)\n if not filename:\n continue\n dest_file = os.path.join(dest, filename)\n if os.path.exists(dest_file):\n os.remove(dest_file)\n zip_ref.extract(member, dest)\n\ndef webui_config_download(yun_files, huggiingface_repo_id):\n %cd $install_path/stable-diffusion-webui/\n for yun_file in yun_files:\n url = f'https://huggingface.co/datasets/{huggiingface_repo_id}/resolve/main/{yun_file}'\n response = requests.head(url)\n if response.status_code == 200:\n result = subprocess.run(['wget', '-O', yun_file, url, '-q'], capture_output=True)\n if result.returncode != 0:\n print(f'Error: Failed to download {yun_file} from {url}')\n else:\n print(f'Error: Invalid URL {url}')\n \ndef venv_install():\n %cd /opt/conda/envs\n if os.path.exists('venv'):\n print('环境已安装')\n else:\n %cd /kaggle/working/\n if not os.path.exists('venv.tar.gz'):\n print('Downloading venv')\n !wget https://huggingface.co/datasets/sukaka/venv_ai_drow/resolve/main/sd_webui/sd_webui_torch201_cu118_xf20.tar.gz -O venv.tar.gz\n print('successfully downloaded venv.tar.gz')\n %cd /opt/conda/envs/\n !mkdir venv\n %cd venv\n print('installing venv')\n os.system('apt -y install -qq pigz > /dev/null 2>&1')\n !pigz -dc -p 5 /kaggle/working/venv.tar.gz | tar xf -\n !source /opt/conda/bin/activate venv\n print('环境安装完毕')\n\n\ndef install_webui():\n %cd $install_path\n if reLoad:\n !rm -rf stable-diffusion-webui\n if Path(\"stable-diffusion-webui\").exists():\n if updata_webui:\n %cd $install_path/stable-diffusion-webui/\n !git pull\n else:\n os.system('git clone https://github.com/PNuwa/stable-diffusion-webui.git > /dev/null 2>&1')\n %cd $install_path/stable-diffusion-webui/\n with open('launch.py', 'r') as f:\n content = f.read()\n with open('launch.py', 'w') as f:\n f.write('import ssl\\n')\n f.write('ssl._create_default_https_context = ssl._create_unverified_context\\n')\n f.write(content)\n if huggingface_use:\n webui_config_download(yun_files, huggiingface_repo_id)\n \n unzip_file('/kaggle/working/图片.zip')\n install_extensions(install_path, extensions)\n download_model()\n link_models()","metadata":{"execution":{"iopub.status.busy":"2023-07-14T11:15:24.487882Z","iopub.execute_input":"2023-07-14T11:15:24.488748Z","iopub.status.idle":"2023-07-14T11:15:24.646139Z","shell.execute_reply.started":"2023-07-14T11:15:24.488585Z","shell.execute_reply":"2023-07-14T11:15:24.645078Z"},"trusted":true},"execution_count":9,"outputs":[]},{"cell_type":"markdown","source":"### > <span style=\"color:green; font-weight:;\">旧版下载代码</span>","metadata":{}},{"cell_type":"code","source":"from concurrent.futures import ThreadPoolExecutor\n# 安装插件，下载和同步模型\ndef install_extensions(install_path, extensions):\n print('安装插件，此处出现红条是正常的')\n os.chdir(os.path.join(install_path, 'stable-diffusion-webui'))\n os.makedirs('extensions', exist_ok=True)\n os.chdir('extensions')\n\n def clone_repo(ex):\n repo_name = ex.split('/')[-1]\n if not os.path.exists(repo_name):\n os.system('git clone ' + ex)\n\n with ThreadPoolExecutor(max_workers=4) as executor:\n executor.map(clone_repo, extensions)\n \ndef download_link(link, target_folder):\n if link.startswith('https://huggingface.co/'):\n filename = re.search(r'[^/]+$', link).group(0)\n return f'aria2c --console-log-level=error -q -c -x 16 -s 16 -k 1M -d \"{target_folder}\" -o \"{filename}\" \"{link}\"'\n else:\n return f'aria2c --console-log-level=error -q -c -x 16 -s 16 -k 1M --remote-time -d \"{target_folder}\" \"{link}\"'\n\ndef download_links(links, target_folder):\n tasks = []\n for link in links:\n tasks.append(download_link(link, target_folder))\n return tasks\n\ndef download_links_all(tasks):\n with ThreadPoolExecutor(max_workers=5) as executor:\n for task in tasks:\n executor.submit(os.system, task)\n \n# 下载模型文件\ndef download_model():\n os.chdir('/kaggle')\n os.makedirs('models', exist_ok=True)\n os.chdir('models')\n os.makedirs('VAE', exist_ok=True)\n os.makedirs('Stable-diffusion', exist_ok=True)\n os.makedirs('Lora', exist_ok=True)\n os.makedirs('cn-model', exist_ok=True)\n os.makedirs('hypernetworks', exist_ok=True)\n os.makedirs('ESRGAN', exist_ok=True)\n os.makedirs('lyco', exist_ok=True)\n tasks = []\n tasks.extend(download_links(vae_model_urls, 'VAE'))\n tasks.extend(download_links(sd_model_urls, 'Stable-diffusion'))\n tasks.extend(download_links(lora_model_urls, 'Lora'))\n tasks.extend(download_links(cn_model_urls, 'cn-model'))\n tasks.extend(download_links(hypernetworks_model_urls, 'hypernetworks'))\n tasks.extend(download_links(ESRGAN_urls, 'ESRGAN'))\n tasks.extend(download_links(lyco_model_urls, 'lyco'))\n tasks.extend(download_links(embeddings_model_urls, f'{install_path}/stable-diffusion-webui/embeddings'))\n tasks.extend(download_links(scripts_urls, f'{install_path}/stable-diffusion-webui/scripts'))\n tasks.extend(download_links(tags_urls, f'{install_path}/stable-diffusion-webui/extensions/a1111-sd-webui-tagcomplete/tags'))\n download_links_all(tasks)\n\ndef create_symlinks(folder_paths, target_dir):\n # Create target directory if it doesn't exist\n if not os.path.exists(target_dir):\n os.makedirs(target_dir)\n # Remove broken symlinks in target directory\n for filename in os.listdir(target_dir):\n target_path = os.path.join(target_dir, filename)\n if os.path.islink(target_path) and not os.path.exists(target_path):\n os.unlink(target_path)\n # Create new symlinks\n for source_path in folder_paths:\n if not os.path.exists(source_path):\n continue\n if os.path.isdir(source_path):\n for filename in os.listdir(source_path):\n source_file_path = os.path.join(source_path, filename)\n target_file_path = os.path.join(target_dir, filename)\n if not os.path.exists(target_file_path):\n os.symlink(source_file_path, target_file_path)\n print(f'Created symlink for {filename} in {target_dir}')\n else:\n filename = os.path.basename(source_path)\n target_file_path = os.path.join(target_dir, filename)\n if not os.path.exists(target_file_path):\n os.symlink(source_path, target_file_path)\n print(f'Created symlink for {filename} in {target_dir}')\n\n# 链接模型文件\ndef link_models():\n cn_model.append('/kaggle/models/cn-model')\n vae_model.append('/kaggle/models/VAE')\n sd_model.append('/kaggle/models/Stable-diffusion')\n lora_model.append('/kaggle/models/Lora')\n hypernetworks_model.append('/kaggle/models/hypernetworks')\n ESRGAN.append('/kaggle/models/ESRGAN')\n lyco_model.append('/kaggle/models/lyco')\n \n create_symlinks(vae_model,f'{install_path}/stable-diffusion-webui/models/VAE')\n create_symlinks(sd_model,f'{install_path}/stable-diffusion-webui/models/Stable-diffusion')\n create_symlinks(lora_model,f'{install_path}/stable-diffusion-webui/models/Lora')\n create_symlinks(cn_model,f'{install_path}/stable-diffusion-webui/extensions/sd-webui-controlnet/models')\n create_symlinks(embeddings_model,f'{install_path}/stable-diffusion-webui/embeddings')\n create_symlinks(hypernetworks_model,f'{install_path}/stable-diffusion-webui/models/hypernetworks')\n create_symlinks(ESRGAN,f'{install_path}/stable-diffusion-webui/models/ESRGAN')\n create_symlinks(tags,f'{install_path}/stable-diffusion-webui/extensions/a1111-sd-webui-tagcomplete/tags')\n create_symlinks(scripts,f'{install_path}/stable-diffusion-webui/scripts')\n create_symlinks(lyco_model,f'{install_path}/stable-diffusion-webui/models/lyco')\n","metadata":{"execution":{"iopub.status.busy":"2023-07-14T11:15:24.648483Z","iopub.execute_input":"2023-07-14T11:15:24.649845Z","iopub.status.idle":"2023-07-14T11:15:24.683972Z","shell.execute_reply.started":"2023-07-14T11:15:24.649795Z","shell.execute_reply":"2023-07-14T11:15:24.682656Z"},"trusted":true},"execution_count":10,"outputs":[]},{"cell_type":"markdown","source":"----","metadata":{}},{"cell_type":"markdown","source":"### > <span style=\"color:green; font-weight:;\">Ngrok，FRP内网穿透</span>","metadata":{}},{"cell_type":"code","source":"# 功能函数：内网穿透\n#ngrok\ndef ngrok_start(ngrokTokenFile: str, port: int, address_name: str, should_run: bool):\n if not should_run:\n print('Skipping ngrok start')\n return\n if Path(ngrokTokenFile).exists():\n with open(ngrokTokenFile, encoding=\"utf-8\") as nkfile:\n ngrokToken = nkfile.readline()\n print('use nrgok')\n from pyngrok import conf, ngrok\n conf.get_default().auth_token = ngrokToken\n conf.get_default().monitor_thread = False\n ssh_tunnels = ngrok.get_tunnels(conf.get_default())\n if len(ssh_tunnels) == 0:\n ssh_tunnel = ngrok.connect(port, bind_tls=True)\n print(f'{address_name}：' + ssh_tunnel.public_url)\n else:\n print(f'{address_name}：' + ssh_tunnels[0].public_url)\n else:\n print('skip start ngrok')\n\n#Frp内网穿透 \nimport subprocess\n\ndef install_Frpc(port, frpconfigfile, use_frpc):\n if use_frpc:\n subprocess.run(['chmod', '+x', '/kaggle/working/frpc/frpc'], check=True)\n print(f'正在启动frp ，端口{port}')\n subprocess.Popen(['/kaggle/working/frpc/frpc', '-c', frpconfigfile])\n","metadata":{"execution":{"iopub.status.busy":"2023-07-14T11:15:24.686225Z","iopub.execute_input":"2023-07-14T11:15:24.687357Z","iopub.status.idle":"2023-07-14T11:15:24.699927Z","shell.execute_reply.started":"2023-07-14T11:15:24.687315Z","shell.execute_reply":"2023-07-14T11:15:24.698836Z"},"trusted":true},"execution_count":11,"outputs":[]},{"cell_type":"markdown","source":"--------------","metadata":{}},{"cell_type":"markdown","source":"# > <span style=\"color:green; font-weight:;\">SD-webui启动函数</span>","metadata":{}},{"cell_type":"code","source":"def iframe_thread_1(port):\n while True:\n time.sleep(0.5)\n sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n result = sock.connect_ex(('127.0.0.1', port))\n if result == 0:\n break\n sock.close()\n p = subprocess.Popen([\"lt\", \"--port\", \"{}\".format(port)], stdout=subprocess.PIPE)\n for line in p.stdout:\n print(line.decode(), end='')\n result = subprocess.run(['curl', 'ipv4.icanhazip.com'], capture_output=True, text=True)\n print('你的公网IP地址是', result.stdout.strip())\n print('或者直接从gradio公网链接进入Webui')\n \ndef start_webui_1():\n if use2:\n install_Frpc('7861',frpconfigfile1,use_frpc1)\n ngrok_start(ngrokTokenFile1,7861,'第二个webui',ngrok_use1)\n !sleep 90\n threading.Thread(target=iframe_thread_1, daemon=True, args=(7861,)).start()\n %cd $install_path/stable-diffusion-webui\n args1.append(f'--ckpt=models/Stable-diffusion/{usedCkpt1}')\n !/opt/conda/envs/venv/bin/python3 launch.py {' '.join(args1)} --port 7861 --device-id=1\n pass\n\ndef start_webui_0():\n threading.Thread(target=iframe_thread, daemon=True, args=(7860,)).start()\n %cd $install_path\n install_Frpc('7860',frpconfigfile,use_frpc)\n ngrok_start(ngrokTokenFile,7860,'第一个webui',ngrok_use)\n %cd $install_path/stable-diffusion-webui\n !mkdir models/lyco\n args.append(f'--ckpt=models/Stable-diffusion/{usedCkpt}')\n !/opt/conda/envs/venv/bin/python3 launch.py {' '.join(args)} --help\n\ndef iframe_thread(port):\n while True:\n time.sleep(0.5)\n sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n result = sock.connect_ex(('127.0.0.1', port))\n if result == 0:\n break\n sock.close()\n p = subprocess.Popen([\"lt\", \"--port\", \"{}\".format(port)], stdout=subprocess.PIPE)\n for line in p.stdout:\n print(line.decode(), end='')\n result = subprocess.run(['curl', 'ipv4.icanhazip.com'], capture_output=True, text=True)\n print('你的公网IP地址是', result.stdout.strip())\n print('或者直接从gradio公网链接进入Webui')\n \ndef start_webui():\n with ProcessPoolExecutor() as executor:\n futures = []\n for func in [start_webui_0, start_webui_1]:\n futures.append(executor.submit(func))\n time.sleep(1)\n for future in futures:\n future.result()","metadata":{"execution":{"iopub.status.busy":"2023-07-14T11:15:24.702997Z","iopub.execute_input":"2023-07-14T11:15:24.704510Z","iopub.status.idle":"2023-07-14T11:15:24.802992Z","shell.execute_reply.started":"2023-07-14T11:15:24.704465Z","shell.execute_reply":"2023-07-14T11:15:24.801709Z"},"trusted":true},"execution_count":12,"outputs":[]},{"cell_type":"code","source":"def main():\n startTicks = time.time()\n if localtunnel:\n !npm install -g localtunnel\n os.system('apt-get update')\n os.system('apt -y install -qq aria2')\n with ProcessPoolExecutor() as executor:\n futures = []\n for func in [install_webui, venv_install,libtcmalloc]:\n futures.append(executor.submit(func))\n time.sleep(0.5)\n for future in futures:\n future.result()\n libtcmalloc()\n ticks = time.time()\n print(\"加载耗时:\",(ticks - startTicks),\"s\")\n start_webui()","metadata":{"ExecutionIndicator":{"show":false},"tags":[],"execution":{"iopub.status.busy":"2023-07-14T11:15:24.808362Z","iopub.execute_input":"2023-07-14T11:15:24.811976Z","iopub.status.idle":"2023-07-14T11:15:24.825316Z","shell.execute_reply.started":"2023-07-14T11:15:24.811927Z","shell.execute_reply":"2023-07-14T11:15:24.824077Z"},"trusted":true},"execution_count":13,"outputs":[]},{"cell_type":"markdown","source":"-------------","metadata":{}},{"cell_type":"markdown","source":"# > <span style=\"color:green; font-weight:;\">打包图片上传到HuggingFace (可选)</span>","metadata":{}},{"cell_type":"code","source":"#功能函数，清理打包上传\nfrom pathlib import Path\nfrom huggingface_hub import HfApi, login\n\ndef zip_venv():\n !pip install conda-pack\n !rm -rf /kaggle/working/venv.tar.gz\n !conda pack -n venv -o /kaggle/working/venv.tar.gz --compress-level 0\n\ndef hugface_upload(huggingface_token_file, yun_files, repo_id):\n if Path(huggingface_token_file).exists():\n with open(huggingface_token_file, encoding=\"utf-8\") as nkfile:\n hugToken = nkfile.readline()\n if hugToken != '':\n # 使用您的 Hugging Face 访问令牌登录\n login(token=hugToken)\n # 实例化 HfApi 类\n api = HfApi()\n print(\"HfApi 类已实例化\")\n %cd $install_path/stable-diffusion-webui\n # 使用 upload_file() 函数上传文件\n print(\"开始上传文件...\")\n for yun_file in yun_files:\n if Path(yun_file).exists():\n response = api.upload_file(\n path_or_fileobj=yun_file,\n path_in_repo=yun_file,\n repo_id=repo_id,\n repo_type=\"dataset\"\n )\n print(\"文件上传完成\")\n print(f\"响应: {response}\")\n else:\n print(f'Error: File {yun_file} does not exist')\n else:\n print(f'Error: File {huggingface_token_file} does not exist')\n\ndef clean_folder(folder_path):\n if not os.path.exists(folder_path):\n return\n for filename in os.listdir(folder_path):\n file_path = os.path.join(folder_path, filename)\n if os.path.isfile(file_path):\n os.remove(file_path)\n elif os.path.isdir(file_path):\n shutil.rmtree(file_path)\n\ndef zip_clear_updata():\n if zip_output:\n output_folder = '/kaggle/outputs/'\n if os.path.exists(output_folder):\n shutil.make_archive('/kaggle/working/图片', 'zip', output_folder)\n print('图片已压缩到output')\n else:\n print(f'文件夹 {output_folder} 不存在，跳过压缩操作')\n if clear_output:\n %cd /kaggle/outputs/\n clean_folder('img2img-images')\n clean_folder('txt2img-images')\n clean_folder('img2img-grids')\n clean_folder('txt2img-grids')\n clean_folder('extras-images')\n print('清理完毕')\n if huggingface_use == True:\n hugface_upload(huggingface_token_file,yun_files,huggiingface_repo_id)\n if use_zip_venv == True:\n zip_venv()","metadata":{"execution":{"iopub.status.busy":"2023-07-14T11:15:24.833798Z","iopub.execute_input":"2023-07-14T11:15:24.834791Z","iopub.status.idle":"2023-07-14T11:15:25.116926Z","shell.execute_reply.started":"2023-07-14T11:15:24.834750Z","shell.execute_reply":"2023-07-14T11:15:25.115929Z"},"trusted":true},"execution_count":14,"outputs":[]},{"cell_type":"markdown","source":"# > <span style=\"color:red; font-weight:;\">执行区域，输出结果在此处看</span>","metadata":{}},{"cell_type":"markdown","source":"# > <span style=\"color:red; font-weight:;\">如果报错了，请反馈给群主</span>","metadata":{}},{"cell_type":"code","source":"'''\n执行函数\n'''\n# 启动的输出日志，部署结果在此处看\nmain()","metadata":{"_kg_hide-input":true,"_kg_hide-output":false,"execution":{"iopub.status.busy":"2023-07-14T11:15:25.121716Z","iopub.execute_input":"2023-07-14T11:15:25.124112Z"},"trusted":true},"execution_count":null,"outputs":[{"name":"stdout","text":"\u001b[K\u001b[?25hm##################\u001b[0m) ⠸ reify:yargs: \u001b[32;40mhttp\u001b[0m \u001b[35mfetch\u001b[0m GET 200 https://registry.npmjs.o\u001b[0m\u001b[Kmjs.or\u001b[0m\u001b[K\nadded 22 packages in 1s\n\n3 packages are looking for funding\n run `npm fund` for details\n\u001b[37;40mnpm\u001b[0m \u001b[0m\u001b[36;40mnotice\u001b[0m\u001b[35m\u001b[0m \n\u001b[0m\u001b[37;40mnpm\u001b[0m \u001b[0m\u001b[36;40mnotice\u001b[0m\u001b[35m\u001b[0m New \u001b[33mminor\u001b[39m version of npm available! \u001b[31m9.5.0\u001b[39m -> \u001b[32m9.8.0\u001b[39m\n\u001b[0m\u001b[37;40mnpm\u001b[0m \u001b[0m\u001b[36;40mnotice\u001b[0m\u001b[35m\u001b[0m Changelog: \u001b[36mhttps://github.com/npm/cli/releases/tag/v9.8.0\u001b[39m\n\u001b[0m\u001b[37;40mnpm\u001b[0m \u001b[0m\u001b[36;40mnotice\u001b[0m\u001b[35m\u001b[0m Run \u001b[32mnpm install -g [email protected]\u001b[39m to update!\n\u001b[0m\u001b[37;40mnpm\u001b[0m \u001b[0m\u001b[36;40mnotice\u001b[0m\u001b[35m\u001b[0m \n\u001b[0mGet:1 http://packages.cloud.google.com/apt gcsfuse-focal InRelease [5002 B]\nGet:2 https://packages.cloud.google.com/apt cloud-sdk InRelease [6361 B]\nGet:3 https://packages.cloud.google.com/apt google-fast-socket InRelease [5015 B]\nGet:4 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64 InRelease [1581 B]\nGet:5 http://security.ubuntu.com/ubuntu jammy-security InRelease [110 kB]\nHit:6 http://archive.ubuntu.com/ubuntu jammy InRelease\nGet:7 http://archive.ubuntu.com/ubuntu jammy-updates InRelease [119 kB]\nGet:8 https://packages.cloud.google.com/apt cloud-sdk/main amd64 Packages [478 kB]\nGet:9 http://archive.ubuntu.com/ubuntu jammy-backports InRelease [108 kB]\nGet:10 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64 Packages [415 kB]\nGet:11 http://security.ubuntu.com/ubuntu jammy-security/multiverse amd64 Packages [44.0 kB]\nGet:12 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 Packages [1005 kB]\nGet:13 http://security.ubuntu.com/ubuntu jammy-security/restricted amd64 Packages [705 kB]\nGet:14 http://security.ubuntu.com/ubuntu jammy-security/main amd64 Packages [713 kB]\nGet:15 http://security.ubuntu.com/ubuntu jammy-security/universe amd64 Packages [949 kB]\nGet:16 http://archive.ubuntu.com/ubuntu jammy-updates/restricted amd64 Packages [730 kB]\nGet:17 http://archive.ubuntu.com/ubuntu jammy-updates/multiverse amd64 Packages [49.8 kB]\nGet:18 http://archive.ubuntu.com/ubuntu jammy-updates/universe amd64 Packages [1205 kB]\nGet:19 http://archive.ubuntu.com/ubuntu jammy-backports/universe amd64 Packages [25.6 kB]\nFetched 6675 kB in 2s (2964 kB/s)\nReading package lists...\n","output_type":"stream"},{"name":"stderr","text":"W: http://packages.cloud.google.com/apt/dists/gcsfuse-focal/InRelease: Key is stored in legacy trusted.gpg keyring (/etc/apt/trusted.gpg), see the DEPRECATION section in apt-key(8) for details.\nW: https://packages.cloud.google.com/apt/dists/google-fast-socket/InRelease: Key is stored in legacy trusted.gpg keyring (/etc/apt/trusted.gpg), see the DEPRECATION section in apt-key(8) for details.\n\nWARNING: apt does not have a stable CLI interface. Use with caution in scripts.\n\n","output_type":"stream"},{"name":"stdout","text":"The following additional packages will be installed:\n libaria2-0 libc-ares2 libssh2-1\nThe following NEW packages will be installed:\n aria2 libaria2-0 libc-ares2 libssh2-1\n","output_type":"stream"},{"name":"stderr","text":"dpkg-preconfigure: unable to re-open stdin: No such file or directory\n","output_type":"stream"},{"name":"stdout","text":"0 upgraded, 4 newly installed, 0 to remove and 15 not upgraded.\nNeed to get 1622 kB of archives.\nAfter this operation, 5817 kB of additional disk space will be used.\nSelecting previously unselected package libc-ares2:amd64.\n(Reading database ... 113701 files and directories currently installed.)\nPreparing to unpack .../libc-ares2_1.18.1-1ubuntu0.22.04.2_amd64.deb ...\nUnpacking libc-ares2:amd64 (1.18.1-1ubuntu0.22.04.2) ...\nSelecting previously unselected package libssh2-1:amd64.\nPreparing to unpack .../libssh2-1_1.10.0-3_amd64.deb ...\nUnpacking libssh2-1:amd64 (1.10.0-3) ...\nSelecting previously unselected package libaria2-0:amd64.\nPreparing to unpack .../libaria2-0_1.36.0-1_amd64.deb ...\nUnpacking libaria2-0:amd64 (1.36.0-1) ...\nSelecting previously unselected package aria2.\nPreparing to unpack .../aria2_1.36.0-1_amd64.deb ...\nUnpacking aria2 (1.36.0-1) ...\nSetting up libc-ares2:amd64 (1.18.1-1ubuntu0.22.04.2) ...\nSetting up libssh2-1:amd64 (1.10.0-3) ...\nSetting up libaria2-0:amd64 (1.36.0-1) ...\nSetting up aria2 (1.36.0-1) ...\nProcessing triggers for man-db (2.10.2-1) ...\nProcessing triggers for libc-bin (2.35-0ubuntu3.1) ...\n/kaggle/working\n/opt/conda/envs\n/kaggle/working\nDownloading venv\n--2023-07-14 11:15:40-- https://huggingface.co/datasets/sukaka/venv_ai_drow/resolve/main/sd_webui/sd_webui_torch201_cu118_xf20.tar.gz\nResolving huggingface.co (huggingface.co)... 65.8.49.24, 65.8.49.53, 65.8.49.38, ...\nConnecting to huggingface.co (huggingface.co)|65.8.49.24|:443... connected.\nHTTP request sent, awaiting response... 302 Found\nLocation: 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[following]\n--2023-07-14 11:15:40-- https://cdn-lfs.huggingface.co/repos/93/61/936160f9623602ad97a9fe4c639531b59f4fe39854fcc22d75692344fb5dfbe2/609336a63928c38f99b0f842dd5d08e1bf255a8add61cbe82301ca5611831b34?response-content-disposition=attachment%3B+filename*%3DUTF-8%27%27sd_webui_torch201_cu118_xf20.tar.gz%3B+filename%3D%22sd_webui_torch201_cu118_xf20.tar.gz%22%3B&response-content-type=application%2Fgzip&Expires=1689588811&Policy=eyJTdGF0ZW1lbnQiOlt7IkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTY4OTU4ODgxMX19LCJSZXNvdXJjZSI6Imh0dHBzOi8vY2RuLWxmcy5odWdnaW5nZmFjZS5jby9yZXBvcy85My82MS85MzYxNjBmOTYyMzYwMmFkOTdhOWZlNGM2Mzk1MzFiNTlmNGZlMzk4NTRmY2MyMmQ3NTY5MjM0NGZiNWRmYmUyLzYwOTMzNmE2MzkyOGMzOGY5OWIwZjg0MmRkNWQwOGUxYmYyNTVhOGFkZDYxY2JlODIzMDFjYTU2MTE4MzFiMzQ%7EcmVzcG9uc2UtY29udGVudC1kaXNwb3NpdGlvbj0qJnJlc3BvbnNlLWNvbnRlbnQtdHlwZT0qIn1dfQ__&Signature=MGqvX1JPryNNeLwh4GgXAlE%7EAQurHAGBWIj7yvUyPaT3aDe65Qx1%7EbszMpm9QSkrRRGJeOhYPu5mRcdf%7ERyyL2gip4N9frfJZaRuz4BNWEJWDsyi8Igrwe7MwphJJWHz1XnXlYOLpb2uuhuOpM%7EAR8E58efbnLHcTQpWh1GDfUdApaXr8kCzWGV-o7x-HrnFn2yikhjoufOKfIqONa8VsBDhCwVaYm%7EEh5CQB1rqWCjhIGQOnmXfIg59ZKGn0aBCrxJAiLRB3NgGr7zm8FPSDdlrAG5wNtWQiMHsYC4pd%7EW4yLQBLV4JDvLumuY8jkltjD3WB0%7ED5l082tDgqfVGIQ__&Key-Pair-Id=KVTP0A1DKRTAX\nResolving cdn-lfs.huggingface.co (cdn-lfs.huggingface.co)... 54.230.18.124, 54.230.18.21, 54.230.18.98, ...\nConnecting to cdn-lfs.huggingface.co (cdn-lfs.huggingface.co)|54.230.18.124|:443... connected.\nHTTP request sent, awaiting response... 200 OK\nLength: 2912904935 (2.7G) [application/gzip]\nSaving to: ‘venv.tar.gz’\n\nvenv.tar.gz 16%[==> ] 467.73M 179MB/s /kaggle/working/stable-diffusion-webui\n/kaggle/working/stable-diffusion-webui\nvenv.tar.gz 27%[====> ] 761.38M 203MB/s eta 12s 安装插件，此处出现红条是正常的\nvenv.tar.gz 28%[====> ] 788.91M 199MB/s eta 10s ","output_type":"stream"},{"name":"stderr","text":"Cloning into 'loopback_scaler'...\nCloning into 'sd-civitai-browser'...\nCloning into 'sd-webui-depth-lib'...\nCloning into 'stable-diffusion-webui-images-browser'...\n","output_type":"stream"},{"name":"stdout","text":"venv.tar.gz 31%[=====> ] 885.44M 168MB/s eta 11s ","output_type":"stream"},{"name":"stderr","text":"Cloning into 'sd-webui-controlnet'...\nCloning into 'sd-webui-3d-open-pose-editor'...\nCloning into 'stable-diffusion-webui-localization-zh_CN2'...\n","output_type":"stream"},{"name":"stdout","text":"venv.tar.gz 33%[=====> ] 935.87M 156MB/s eta 11s ","output_type":"stream"},{"name":"stderr","text":"Cloning into 'stable-diffusion-webui-two-shot'...\n","output_type":"stream"},{"name":"stdout","text":"venv.tar.gz 35%[======> ] 987.44M 144MB/s eta 11s ","output_type":"stream"},{"name":"stderr","text":"Cloning into 'a1111-sd-webui-tagcomplete'...\n","output_type":"stream"},{"name":"stdout","text":"venv.tar.gz 36%[======> ] 1.00G 119MB/s eta 11s ","output_type":"stream"},{"name":"stderr","text":"Cloning into 'sd-webui-cutoff'...\n","output_type":"stream"},{"name":"stdout","text":"venv.tar.gz 39%[======> ] 1.08G 96.6MB/s eta 11s ","output_type":"stream"},{"name":"stderr","text":"Cloning into 'sd-webui-lora-block-weight'...\n","output_type":"stream"},{"name":"stdout","text":"venv.tar.gz 41%[=======> ] 1.13G 95.6MB/s eta 11s ","output_type":"stream"},{"name":"stderr","text":"Cloning into 'Stable-Diffusion-Webui-Civitai-Helper'...\n","output_type":"stream"},{"name":"stdout","text":"venv.tar.gz 43%[=======> ] 1.17G 98.0MB/s eta 11s ","output_type":"stream"},{"name":"stderr","text":"Cloning into 'stable-diffusion-webui'...\nCloning into 'sd-webui-mov2mov'...\n","output_type":"stream"},{"name":"stdout","text":"venv.tar.gz 46%[========> ] 1.25G 103MB/s eta 11s ","output_type":"stream"},{"name":"stderr","text":"Cloning into 'stable-diffusion-webui-wd14-tagger'...\nCloning into 'a1111-sd-webui-lycoris'...\nCloning into 'sd-webui-deforum'...\n","output_type":"stream"},{"name":"stdout","text":"venv.tar.gz 66%[============> ] 1.81G 138MB/s eta 7s ","output_type":"stream"},{"name":"stderr","text":"Cloning into 'sd-extension-system-info'...\n","output_type":"stream"},{"name":"stdout","text":"venv.tar.gz 70%[=============> ] 1.92G 135MB/s eta 6s ","output_type":"stream"},{"name":"stderr","text":"Cloning into 'sd_dreambooth_extension'...\n","output_type":"stream"},{"name":"stdout","text":"venv.tar.gz 71%[=============> ] 1.95G 129MB/s eta 6s ","output_type":"stream"}]},{"cell_type":"code","source":"#跑图结束，手动执行，清理图片并打包到output方便下载,同时同步配置文件\nzip_clear_updata()","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 第一次部署好之后可以直接手动执行下面这个代码块极速启动","metadata":{}},{"cell_type":"code","source":"# 要第一次部署好之后并且右边的PERSISTENCE设置为Files Only才能单击运行这个代码块，只需要30秒就能加载完毕\nstart_webui()","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 使用帮助\n## kaggle账号\n- 注册账号需要手机号，国内手机号也行，如果点击注册后没反应，估计是需要梯子，用于人机验证\n- 注册后点此笔记的 **Copy & Edit** 按钮就进到编辑界面\n\n## **准备工作**\n1. 右侧面板 **Settings/ACCELERATOR** 需要选择GPU **P100 或 T4x2** 这两据说有差异，但我用起来差不多\n2. 右侧面板 **Settings/LANGUAGE** 需要选择Python\n2. 右侧面板 **Settings/PERSISTENCE** 建议选择 Files only **作用是保存Outpot目录内的文件**\n3. 右侧面板 **Settings/ENVIRONMENT** 建议不改这个配置，使用当前默认值就行\n4. 右侧面板 **Settings/INTERNET** 需要打开 用于联网，没网跑不起来的啊\n\n## **启动**\n#### 启动方式一 **直接点击页面上边的 RunAll**\n- 在没有关闭电源的情况下，后几次点击RunAll的输出在页面上端 （其实没有必要了，之前不知道代码块可以收起，很烦滚动到页面底端才能看见输出）\n- 手机端可能会出现页面上边的工具栏不显示的情况，左侧菜单按钮里也有相关的操作\n- 长时间不操作页面会导致脚本停止 （应该是40分钟吧）\n\n#### 启动方式二 **使用页面上边的 Save Version 后台运行**\n- 后台运行不用担心长时间不操作脚本停止\n- Version Type 选择 **Save & Run All**\n- 在Save Version弹窗里需要选择使用**GPU**环境 （Advanced Settings 里最后一个选项）\n- 后台运行的输出的图片可以在运行结束后下载（但是保存时间有限制，我就经常下不到，不够问题不大，喜欢的图在生成后就下载了）\n- 如果你需要下载运行后的图片，请不要把安装目录修改到 /kaggle/working 这个目录下，因为没有写打包功能，下载只能下载整个输出目录，也就是 /kaggle/working 目录\n\n## 访问\n- 如果你使用了ngrok或者frpc，可以访问你这两对应的地址\n- 如果你不知道你的ngrok或者frpc的地址可以在控制台（页面最下方Console）的输出里面查看\n- 使用Run All方式启动，控制台在启动完成后会输出访问网址，网址内容包含**gradio.live**，可以在页面中搜索快速找到\n- 如果使用Save Verson的方式启动，点击左下角的**View Active Events**点击刚刚启动的脚步，在**Log**里找访问网址\n- 一般情况下第一次启动此脚本需要等待kaggle下载模型文件，进度在页面上方\n- 第二次及以后（不增加新的文件）需要3到5分钟\n\n## **增加模型**\n# 方法一：\n通过下载连接下载到Kaggle\nKaggle的宽带很快，300MB/s，不到30秒就下好大模型了\n# 方法二：\n1. 先创建数据集，也就是dataset\n2. 创建时需要添加文件，选择自己的模型文件就行\n3. 同类型文件放相同的数据集里面，一个数据集也不要太大\n4. 可以在dataset搜索其他人上传的模型\n5. 通过右侧的 **Add Data** 按钮选择已经上传的模型文件或者别人上传的模型文件\n - input 下面的列表就是模型文件，可以点击名称后面的复制按钮复制路径\n6. 将模型路径放在配置里的对应配置里即可，支持文件夹和文件路径，参考\n - 如果目录里还有子目录也是需要加载的，可以用*表示子目录 例子：比如Loras目录下还有角色、画风、涩涩的文件夹，那路径里写成 '/kaggle/input/Loras/*'就可以加载子目录里面的文件了\n - 模型加载使用的文件链接方式，如果你融模型的时候新模型名字和原有模型名字一样，会出现不能修改只读文件的错误\n - 同理，直接对模型做编辑的工具可能也会出现相同的错误\n \n \n- **为了提高启动速度，导致切换模型过程较慢，点击切换模型后进度条大概率会一直存在，但模型在1分半左右基本能加载完。** \n- **受到kaggle内存大小的影响，切换多个模型后大概率爆内存导致停止运行**\n \n**下边的配置项都写了对应配置的作用和使用说明，不理解的话也不用改，用默认的就好**\n\n## 下载文件\n#### 方式一\n- 在浏览器直接下 比如你需要下载的文件路径在 /kaggle/stable-diffusion-webui/models/Lora/dow_a.safetensors\n - 比如你需要下载的文件路径在 /kaggle/stable-diffusion-webui/models/Lora/dow_a.safetensors\n - 你的访问地址是 https://123123123.gradio.live\n - 则可以在浏览器输入 https://123123123.gradio.live/file=/kaggle/stable-diffusion-webui/models/Lora/dow_a.safetensors 下载你的文件\n \n#### 方式二\n- 复制到Output目录下载 仅支持使用Run All方式运行的\n - 比如你需要下载的文件路径在 /kaggle/stable-diffusion-webui/models/Lora/dow_a.safetensors\n - 先停止笔记本（不是关机，是停止）\n - 然后新建一个代码块，在里面输入 !cp -f /kaggle/stable-diffusion-webui/models/Lora/dow_a.safetensors /kaggle/working/\n - 就可以在右侧列表的Output目录看见复制出来的文件，点击下载即可\n \n#### 方式三\n- 开启链接输出目录的配置 （配置在第二个代码块，通过搜索**配置文件链接**快速查找）\n - 此方法会把已知的三个训练输出目录链接到Output目录下，直接去下载即可（两种启动方式都可以用）\n - 如果有新的目录需要链接，可以参考着自己写或者联系我\n \n#### 方式四\n- 将安装目录改到输出目录（配置在第二个代码块，通过搜索**安装目录**快速查找）\n - 此方式会把所有文件都放在安装目录，找到并下载即可\n - 如果使用这个方式，右侧的设置里**PERSISTENCE**这个设置项建议选No pensistence。如果选其他项，可能会出现关机特别慢的情况，因为需要上传输出目录的文件。\n\n## **一些可能没用的说明**\n- 配置说明 **True或者False**表示布尔值 **True**表示“**是**” **False**表示“**否**” 只有这两个值\n- 配置说明 **[]** 表示数组，里面可以存放内容，每个内容需要用**英语(半角)逗号**隔开\n- 配置说明 **''或者\"\"** 英语(半角)的双引号或者单引号包裹的内容是**字符串**，比如放在数组里面的路径就需要是一个字符串\n- 配置说明 **#** **#** 后面的内容是**注释**，是帮助性内容，对整个代码的执行不会有影响\n\n## **一些常见的错误**\n 1.Run All后白屏：可能是开了网页自动翻译导致，请重试\n 2.跑到一半出错了：更新到最新版本重新导入，下载地址 https://huggingface.co/datasets/ACCA225/Kaggle-Stable-Diffusion ， 如果还是出问题了，请联系管理员\n # 群号码：632428790","metadata":{}},{"cell_type":"markdown","source":"-----------------","metadata":{}},{"cell_type":"markdown","source":"# > <span style=\"color:green; font-weight:;\">附录：Webui启动参数</span>","metadata":{}},{"cell_type":"code","source":"def useless():\n -h, --help 显示此帮助消息并退出\n --update-all-extensions\n launch.py 参数：在启动程序时下载所有扩展的更新\n --skip-python-version-check\n launch.py 参数：不检查Python版本\n --skip-torch-cuda-test\n launch.py 参数：不检查CUDA是否能正常工作\n --reinstall-xformers launch.py 参数：安装适当版本的xformers，即使您已经安装了某个版本\n --reinstall-torch launch.py 参数：安装适当版本的torch，即使您已经安装了某个版本\n --update-check launch.py 参数：在启动时检查更新\n --test-server launch.py 参数：配置用于测试的服务器\n --skip-prepare-environment\n launch.py 参数：跳过所有环境准备步骤\n --skip-install launch.py 参数：跳过软件包的安装\n --data-dir DATA_DIR 存储所有用户数据的基本路径\n --config CONFIG 构建模型的配置文件路径\n --ckpt CKPT 稳定扩散模型的检查点路径；如果指定了此参数，该检查点将添加到检查点列表并加载\n --ckpt-dir CKPT_DIR 包含稳定扩散检查点的目录路径\n --vae-dir VAE_DIR 包含VAE文件的目录路径\n --gfpgan-dir GFPGAN_DIR\n GFPGAN目录\n --gfpgan-model GFPGAN_MODEL\n GFPGAN模型文件名\n --no-half 不将模型切换为16位浮点数\n --no-half-vae 不将VAE模型切换为16位浮点数\n --no-progressbar-hiding\n 不在gradio UI中隐藏进度条（因为它会减慢浏览器中的硬件加速）\n --max-batch-count MAX_BATCH_COUNT\n UI的最大批次计数值\n --embeddings-dir EMBEDDINGS_DIR\n 文本反演的嵌入目录（默认为embeddings）\n --textual-inversion-templates-dir TEXTUAL_INVERSION_TEMPLATES_DIR\n 包含文本反演模板的目录路径\n --hypernetwork-dir HYPERNETWORK_DIR\n 超网络目录\n --localizations-dir LOCALIZATIONS_DIR\n 本地化目录\n --allow-code 允许从Web界面执行自定义脚本\n --medvram 启用稳定扩散模型的优化，以牺牲一些速度以实现低VRM使用率\n --lowvram 启用稳定扩散模型的优化，以牺牲大量速度以实现非常低的VRM使用率\n --lowram 将稳定扩散检查点权重加载到VRAM而不是RAM中\n --always-batch-cond-uncond\n 禁用条件/非条件批处理，该批处理可通过--medvram或--lowvram来节省内存\n --unload-gfpgan 无任何操作。\n --precision {full,autocast}\n 在此精度下进行评估\n --upcast-sampling 上升采样。对于--no-half没有影响。通常与--no-half相比，产生类似的结果，性能更好，同时使用更少的内存。\n --share 对gradio使用share=True，并使UI可以通过其网站访问\n --ngrok NGROK ngrok的认证令牌，替代gradio --share\n --ngrok-region NGROK_REGION\n 无任何操作。\n --ngrok-options NGROK_OPTIONS\n 以JSON格式传递给ngrok的选项，例如：\n '{\"authtoken_from_env\":true,\n \"basic_auth\":\"user:password\",\n \"oauth_provider\":\"google\",\n \"oauth_allow_emails\":\"[email protected]\"}'\n --enable-insecure-extension-access\n 禁用其他选项，启用扩展选项\n --codeformer-models-path CODEFORMER_MODELS_PATH\n 包含codeformer模型文件的目录路径。\n --gfpgan-models-path GFPGAN_MODELS_PATH\n 包含GFPGAN模型文件的目录路径。\n --esrgan-models-path ESRGAN_MODELS_PATH\n 包含ESRGAN模型文件的目录路径。\n --bsrgan-models-path BSRGAN_MODELS_PATH\n 包含BSRGAN模型文件的目录路径。\n --realesrgan-models-path REALESRGAN_MODELS_PATH\n 包含RealESRGAN模型文件的目录路径。\n --clip-models-path CLIP_MODELS_PATH\n 包含CLIP模型文件的目录路径。\n --xformers 启用xformers的交叉注意力层\n --force-enable-xformers\n 启用xformers的交叉注意力层，无论检查代码是否认为您可以运行它；如果此操作无法正常工作，请不要提交错误报告\n --xformers-flash-attention\n 启用具有Flash Attention的xformers，以提高可重现性（仅适用于SD2.x或变体）\n --deepdanbooru 无任何操作。\n --opt-split-attention\n 首选Doggettx的交叉注意力层优化，用于自动选择优化方式\n --opt-sub-quad-attention\n 首选内存高效的次二次交叉注意力层优化，用于自动选择优化方式\n --sub-quad-q-chunk-size SUB_QUAD_Q_CHUNK_SIZE\n 用于次二次交叉注意力层优化的查询块大小\n --sub-quad-kv-chunk-size SUB_QUAD_KV_CHUNK_SIZE\n 用于次二次交叉注意力层优化的kv块大小\n --sub-quad-chunk-threshold SUB_QUAD_CHUNK_THRESHOLD\n 用于次二次交叉注意力层优化的VRAM阈值的百分比，以使用块处理\n --opt-split-attention-invokeai\n 首选InvokeAI的交叉注意力层优化，用于自动选择优化方式\n --opt-split-attention-v1\n 首选旧版本的分割注意力优化，用于自动选择优化方式\n --opt-sdp-attention 首选缩放点积交叉注意力层优化，用于自动选择优化方式；需要PyTorch 2.*\n --opt-sdp-no-mem-attention\n 首选没有内存高效注意力的缩放点积交叉注意力层优化，用于自动选择优化方式，使图像生成具有确定性；需要PyTorch 2.*\n --disable-opt-split-attention\n 首选不进行交叉注意力层优化，用于自动选择优化方式\n --disable-nan-check 不检查生成的图像/潜空间是否包含NaN；在没有检查点的情况下运行时很有用\n --use-cpu USE_CPU [USE_CPU ...]\n 使用CPU作为指定模块的torch设备\n --listen 使用0.0.0.0作为服务器名称启动gradio，以响应网络请求\n --port PORT 使用给定的服务器端口启动gradio，对于<1024的端口，您需要root/admin权限，默认为7860（如果可用）\n --show-negative-prompt\n 无任何操作。\n --ui-config-file UI_CONFIG_FILE\n 用于ui配置的文件名\n --hide-ui-dir-config 隐藏Web界面中的目录配置\n --freeze-settings 禁用编辑设置\n --ui-settings-file UI_SETTINGS_FILE\n 用于ui设置的文件名\n --gradio-debug 使用--debug选项启动gradio\n --gradio-auth GRADIO_AUTH\n 设置gradio的身份验证，格式为“username:password”；或者使用逗号分隔多个，例如“u1:p1,u2:p2,u3:p3”\n --gradio-auth-path GRADIO_AUTH_PATH\n 设置gradio的身份验证文件路径，例如“/path/to/auth/file”，与--gradio-auth具有相同的身份验证格式\n --gradio-img2img-tool GRADIO_IMG2IMG_TOOL\n 无任何操作。\n --gradio-inpaint-tool GRADIO_INPAINT_TOOL\n 无任何操作。\n --gradio-allowed-path GRADIO_ALLOWED_PATH\n 将路径添加到gradio的allowed_paths，使其可以从中提供文件\n --opt-channelslast 将稳定扩散的内存类型更改为channels last\n --styles-file STYLES_FILE\n 用于样式的文件名\n --autolaunch 启动后在系统的默认浏览器中打开Web界面的URL\n --theme THEME 使用浅色或深色主题启动UI\n --use-textbox-seed 在UI中使用文本框作为种子（没有上/下箭头，但可以输入长种子）\n --disable-console-progressbars\n 不将进度条输出到控制台\n --enable-console-prompts\n 使用txt2img和img2img生成时，在控制台打印提示\n --vae-path VAE_PATH 用作VAE的检查点；设置此参数会禁用与VAE相关的所有设置\n --disable-safe-unpickle\n 禁用检查PyTorch模型是否包含恶意代码\n --api 使用api=True同时启动API和Web界面（仅使用--nowebui启动API）\n --api-auth API_AUTH 设置API的身份验证，格式为“username:password”；或者使用逗号分隔多个，例如“u1:p1,u2:p2,u3:p3”\n --api-log 使用api-log=True启用所有API请求的日志记录\n --nowebui 使用api=True启动API而不是Web界面\n --ui-debug-mode 不加载模型，快速启动UI\n --device-id DEVICE_ID\n 选择要使用的默认CUDA设备（在之前需要导出CUDA_VISIBLE_DEVICES=0,1等）\n --administrator 管理员权限\n --cors-allow-origins CORS_ALLOW_ORIGINS\n 以逗号分隔的列表形式的允许CORS源（无空格）\n --cors-allow-origins-regex CORS_ALLOW_ORIGINS_REGEX\n 单个正则表达式形式的允许CORS源\n --tls-keyfile TLS_KEYFILE\n 部分启用TLS，需要--tls-certfile才能完全工作\n --tls-certfile TLS_CERTFILE\n 部分启用TLS，需要--tls-keyfile才能完全工作\n --disable-tls-verify 通过此参数启用使用自签名证书。\n --server-name SERVER_NAME\n 设置服务器的主机名\n --gradio-queue 无任何操作。\n --no-gradio-queue 禁用gradio队列；导致网页使用HTTP请求而不是Websockets；在早期版本中是默认设置\n --skip-version-check 不检查torch和xformers的版本\n --no-hashing 禁用检查点的sha256哈希，以提高加载性能\n --no-download-sd-model\n 即使在--ckpt-dir中找不到模型，也不下载SD1.5模型\n --subpath SUBPATH 自定义gradio的子路径，与反向代理一起使用\n --add-stop-route 添加/_stop路由以停止服务器","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"---------------","metadata":{}},{"cell_type":"markdown","source":"## 以下代码以后可能有用，全部由Yiyiooo编写","metadata":{}},{"cell_type":"code","source":"# def initKaggleConfig():\n# if Path('~/.kaggle/kaggle.json').exists():\n# return True\n# if Path(kaggleApiTokenFile).exists():\n# !mkdir -p ~/.kaggle/\n# os.system('cp '+kaggleApiTokenFile+' ~/.kaggle/kaggle.json')\n# !chmod 600 ~/.kaggle/kaggle.json\n# return True\n# print('缺少kaggle的apiToken文件，访问：https://www.kaggle.com/你的kaggle用户名/account 获取')\n# return False\n\n# def getUserName():\n# if not initKaggleConfig(): return\n# import kaggle\n# return kaggle.KaggleApi().read_config_file()['username']\n\n# def createOrUpdateDataSet(path:str,datasetName:str):\n# if not initKaggleConfig(): return\n# print('创建或更新数据集 '+datasetName)\n# import kaggle\n# os.system('mkdir -p $install_path/kaggle_cache')\n# os.system('rm -rf $install_path/kaggle_cache/*')\n# datasetDirPath = install_path+'/kaggle_cache/'+datasetName\n# os.system('mkdir -p '+datasetDirPath)\n# os.system('cp -f '+path+' '+datasetDirPath+'/')\n# username = getUserName()\n# print(\"kaggle username:\"+username)\n# datasetPath = username+'/'+datasetName\n# datasetList = kaggle.api.dataset_list(mine=True,search=datasetPath)\n# print(datasetList)\n# if len(datasetList) == 0 or datasetPath not in [str(d) for d in datasetList]: # 创建 create\n# os.system('kaggle datasets init -p' + datasetDirPath)\n# metadataFile = datasetDirPath+'/dataset-metadata.json'\n# os.system('sed -i s/INSERT_TITLE_HERE/'+ datasetName + '/g ' + metadataFile)\n# os.system('sed -i s/INSERT_SLUG_HERE/'+ datasetName + '/g ' + metadataFile)\n# os.system('cat '+metadataFile)\n# os.system('kaggle datasets create -p '+datasetDirPath)\n# print('create database done')\n# else:\n# kaggle.api.dataset_metadata(datasetPath,datasetDirPath)\n# kaggle.api.dataset_create_version(datasetDirPath, 'auto update',dir_mode='zip')\n# print('upload database done')\n\n# def downloadDatasetFiles(datasetName:str,outputPath:str):\n# if not initKaggleConfig(): return\n# print('下载数据集文件 '+datasetName)\n# import kaggle\n# username = getUserName()\n# datasetPath = username+'/'+datasetName\n# datasetList = kaggle.api.dataset_list(mine=True,search=datasetPath)\n# if datasetPath not in [str(d) for d in datasetList]:\n# return False\n# os.system('mkdir -p '+outputPath)\n# kaggle.api.dataset_download_files(datasetPath,path=outputPath,unzip=True)\n# return True\n","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# ~~绕过 os.systen 的限制执行命令~~","metadata":{}},{"cell_type":"code","source":"\n# def run(shell:str,shellName=''):\n# if shellName == '': shellName = str(time.time())\n# !mkdir -p $install_path/run_cache\n# with open(install_path+'/run_cache/run_cache.'+shellName+'.sh','w') as sh:\n# sh.write(shell)\n# !bash {install_path}/run_cache/run_cache.{shellName}.sh\n\n# 连接多个路径字符串 让路径在shell命令中能正常的执行\n# def pathJoin(*paths:str):\n# pathStr = ''\n# for p in paths:\n# pathStr += '\"'+p+'\"'\n# pathStr = '\"*\"'.join(pathStr.split('*'))\n# pathStr = '\"$\"'.join(pathStr.split('$'))\n# pathStr = '\"(\"'.join(pathStr.split('('))\n# pathStr = '\")\"'.join(pathStr.split(')'))\n# pathStr = '\"{\"'.join(pathStr.split('{'))\n# pathStr = '\"}\"'.join(pathStr.split('}'))\n# pathStr = re.sub(r'\"\"','',pathStr)\n# pathStr = re.sub(r'\\*{2,}','\"',pathStr)\n# pathStr = re.sub(r'/{2,}','/',pathStr)\n# pathStr = re.sub(r'/\\./','/',pathStr)\n# return pathStr\n\n# 判断路径是不是一个文件或者可能指向一些文件\n# def pathIsFile(path):\n# if Path(path).is_file():\n# return True\n# if re.search(r'\\.(ckpt|safetensors|png|jpg|txt|pt|pth|json|yaml|\\*)$',path):\n# return True\n# return False\n\n# def echoToFile(content:str,path:str):\n# with open(path,'w') as sh:\n# sh.write(content)\n\n# ngrok\n# def startNgrok(ngrokToken:str,ngrokLocalPort:int):\n# from pyngrok import conf, ngrok\n# try:\n# conf.get_default().auth_token = ngrokToken\n# conf.get_default().monitor_thread = False\n# ssh_tunnels = ngrok.get_tunnels(conf.get_default())\n# if len(ssh_tunnels) == 0:\n# ssh_tunnel = ngrok.connect(ngrokLocalPort)\n# print('address：'+ssh_tunnel.public_url)\n# else:\n# print('address：'+ssh_tunnels[0].public_url)\n# except:\n# print('启动ngrok出错')\n \n# def startFrpc(name,configFile):\n# run(f'''\n# cd $install_path/frpc/\n# $install_path/frpc/frpc {configFile}\n# ''',name)\n \n# def installProxyExe():\n# if useFrpc:\n# print('安装frpc')\n# !mkdir -p $install_path/frpc\n# if Path(frpcExePath).exists():\n# os.system(f'cp -f -n {frpcExePath} $install_path/frpc/frpc')\n# else:\n# !wget \"https://huggingface.co/datasets/ACCA225/Frp/resolve/main/frpc\" -O $install_path/frpc/frpc\n \n# for ssl in frpcSSLFFlies:\n# if Path(ssl).exists():\n# os.system('cp -f -n '+pathJoin(ssl,'/*')+' $install_path/frpc/')\n# !chmod +x $install_path/frpc/frpc\n# !$install_path/frpc/frpc -v\n# if useNgrok:\n# %pip install pyngrok\n \n# def startProxy():\n# if useNgrok:\n# startNgrok(ngrokToken,webuiPort)\n# if useFrpc:\n# startFrpc('frpc_proxy',frpcStartArg)\n\n \n# def zipPath(path:str,zipName:str,format='tar'):\n# if path.startswith('$install_path'):\n# path = path.replace('$install_path',install_path)\n# if path.startswith('$output_path'):\n# path = path.replace('$install_path',output_path)\n# if not path.startswith('/'):\n# path = pathJoin(install_path,'/stable-diffusion-webui','/',path)\n# if Path(path).exists():\n# if 'tar' == format:\n# os.system('tar -cf $output_path/'+ zipName +'.tar -C '+ path +' . ')\n# elif 'gz' == format:\n# os.system('tar -czf $output_path/'+ zipName +'.tar.gz -C '+ path +' . ')\n# return\n# print('指定的目录不存在：'+path)\n","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"~~下载文件的判断逻辑~~","metadata":{}},{"cell_type":"code","source":"# import os\n# import re\n# # 加入文件到下载列表\n# def putDownloadFile(url:str,distDir:str,file_name:str=None):\n# if re.match(r'^[^:]+:(https?|ftps?)://', url, flags=0):\n# file_name = re.findall(r'^[^:]+:',url)[0][:-1]\n# url = url[len(file_name)+1:]\n# if not re.match(r'^(https?|ftps?)://',url):\n# return\n# file_name = re.sub(r'\\s+','_',file_name or '')\n# dir = str(hash(url)).replace('-','')\n# down_dir = f'{install_path}/down_cache/{dir}'\n# !mkdir -p {down_dir}\n# return [url,file_name,distDir,down_dir]\n\n# def get_file_size_in_gb(file_path):\n# size_in_bytes = Path(file_path).stat().st_size\n# size_in_gb = size_in_bytes / (1024 ** 3)\n# return '%.2f' % size_in_gb\n \n# # 下载文件\n# def startDownloadFiles(download_list):\n# print('下载列表:\\n','\\n'.join([f'{item[0]} -> {item[2]}/{item[1]}' for item in download_list]))\n# dist_list = []\n# for dow_f in download_list:\n# !mkdir -p {dow_f[3]}\n# print('下载 名称：',dow_f[1],'url：',dow_f[0])\n# output_file = f' -O {dow_f[3]}/{dow_f[1]}'\n# if len(os.listdir(dow_f[3])) > 0:\n# continue\n# os.system(f\"wget {dow_f[0]} --tries=3 --timeout=60 -P {dow_f[3]} {output_file if len(dow_f[1]) > 0 else ''} -o {install_path}/down_cache/log.log\")\n# if len(os.listdir(dow_f[3])) == 0:\n# print('下载出错：',dow_f[0])\n# continue\n# file_name = os.listdir(dow_f[3])[0]\n# !mkdir -p {dow_f[2]}\n# down_file_path = f'{dow_f[3]}/{file_name}'\n# if Path(down_file_path).is_symlink():\n# down_file_path = os.readlink(down_file_path)\n# print('文件真实地址：'+down_file_path)\n# if not Path(down_file_path).exists():\n# print('文件异常')\n# continue\n# print(f'文件大小：{get_file_size_in_gb(down_file_path)}G')\n# dist_path = f'{dow_f[2]}/{file_name}'\n# dist_path = dist_path.replace('%20',' ').strip().replace(' ','_')\n# print(f'移动文件 {down_file_path} -> {dist_path}')\n# os.system(f'ln -f \"{down_file_path}\" \"{dist_path}\"')\n# if dow_f[2] not in dist_list:\n# dist_list.append(dow_f[2])\n# for dist_dir in dist_list:\n# print(dist_dir,os.listdir(dist_dir))\n","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"###### ？","metadata":{}}]} |