{"metadata":{"kaggle":{"accelerator":"none","dataSources":[{"sourceId":7991141,"sourceType":"datasetVersion","datasetId":2908961}],"dockerImageVersionId":30732,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false},"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.8.10"},"colab":{"provenance":[]}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# 定义配置文件内容\n#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\nuse_frpc = True\nfrpconfigfile = '/kaggle/input/aihua-5000/frpc_10669839.ini'\nconfig = \"\"\"\n[common]\nserver_addr = frps.loliy.top\nserver_port = 7500\ntoken = frps162534\n\n[sdwebuip60501]\ntype = tcp\nlocal_ip = 127.0.0.1\nlocal_port = 7860\nremote_port = 10001\n\n[sdwebuip60601]\ntype = tcp\nlocal_ip = 127.0.0.1\nlocal_port = 7861\nremote_port = 10002\n\n[sdwebuip60701]\ntype = tcp\nlocal_ip = 127.0.0.1\nlocal_port = 7862\nremote_port = 10003\n\n[sdwebuip60801]\ntype = tcp\nlocal_ip = 127.0.0.1\nlocal_port = 7863\nremote_port = 10004\n\n[sdwebuip60901]\ntype = tcp\nlocal_ip = 127.0.0.1\nlocal_port = 22\nremote_port = 10005\n\"\"\"\n\n# 定义保存路径\nfile_path = './cyanfrp.ini'\n\n# 将配置内容写入文件\nwith open(file_path, 'w') as config_file:\n    config_file.write(config)\n\nprint(f\"配置文件已创建为 {file_path}\")\ndef install_Frpc(port, frpconfigfile, use_frpc):\n    if use_frpc:\n        !cp /kaggle/input/net-tools/frpc /kaggle/working\n        subprocess.run(['chmod', '+x', '/kaggle/working/frpc'], check=True)\n        print(f'正在启动frp ，端口{port}')\n        subprocess.Popen(['/kaggle/working/frpc', '-c', './cyanfrp.ini'])\n\ninstall_Frpc('5140',frpconfigfile,use_frpc)","metadata":{"execution":{"iopub.execute_input":"2024-04-16T04:55:20.621579Z","iopub.status.busy":"2024-04-16T04:55:20.620554Z","iopub.status.idle":"2024-04-16T04:55:21.645121Z","shell.execute_reply":"2024-04-16T04:55:21.643525Z","shell.execute_reply.started":"2024-04-16T04:55:20.621543Z"},"id":"ZBYvdOt3d_AZ","outputId":"fd9b4818-d907-4009-9e9e-49529ca4652d"},"execution_count":null,"outputs":[{"name":"stdout","output_type":"stream","text":"配置文件已创建为 ./cyanfrp.ini\n\ncp: cannot create regular file '/kaggle/working/frpc': Text file busy\n\n正在启动frp ，端口5140\n"}]},{"cell_type":"code","source":"\n# 定义配置文件内容\n#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\nuse_frpc = True\nfrpconfigfile = '/kaggle/input/aihua-5000/frpc_10669839.ini'\nconfig2 = \"\"\"\n[common]\nserver_addr = awsjp.zzcat.top\nserver_port = 10000\ntoken = 080208zzc\nuser = op\ntle_enable = true\ndns_server = 114.114.114.114\n\n[sdwebuip60501]\ntype = tcp\nlocal_ip = 127.0.0.1\nlocal_port = 7860\nremote_port = 12475\n\n[sdwebuip60601]\ntype = tcp\nlocal_ip = 127.0.0.1\nlocal_port = 7861\nremote_port = 12476\n\n[sdwebuip60701]\ntype = tcp\nlocal_ip = 127.0.0.1\nlocal_port = 7862\nremote_port = 12477\n\n[sdwebuip60801]\ntype = tcp\nlocal_ip = 127.0.0.1\nlocal_port = 7863\nremote_port = 12478\n\n[sdwebuip60901]\ntype = tcp\nlocal_ip = 127.0.0.1\nlocal_port = 22\nremote_port = 12479\n\"\"\"\n\n# 定义保存路径\nfile_path2 = './cyanfrp2.ini'\n\n# 将配置内容写入文件\nwith open(file_path2, 'w') as config_file:\n    config_file.write(config2)\n\nprint(f\"配置文件已创建为 {file_path2}\")\ndef install_Frpc2(port, frpconfigfile, use_frpc):\n    if use_frpc:\n        !echo start aws\n        !cp /kaggle/input/net-tools/frpc /kaggle/working\n        subprocess.run(['chmod', '+x', '/kaggle/working/frpc'], check=True)\n        print(f'正在启动frp ，端口{port}')\n        subprocess.Popen(['/kaggle/working/frpc', '-c', './cyanfrp2.ini'])\n\ninstall_Frpc2('5140',frpconfigfile,use_frpc)","metadata":{"execution":{"iopub.execute_input":"2024-04-16T04:56:28.984224Z","iopub.status.busy":"2024-04-16T04:56:28.983639Z","iopub.status.idle":"2024-04-16T04:56:32.419484Z","shell.execute_reply":"2024-04-16T04:56:32.418438Z","shell.execute_reply.started":"2024-04-16T04:56:28.984161Z"},"id":"EAEnycJQd_Ac","outputId":"e4e0f1cf-6913-4083-8b02-f413feaf5012"},"execution_count":null,"outputs":[{"name":"stdout","output_type":"stream","text":"配置文件已创建为 ./cyanfrp2.ini\n\nstart aws\n\n正在启动frp ，端口5140\n\n2024/04/16 04:56:32 [I] 检查更新中...\n\n2024/04/16 04:56:32 [I] frpc version: 0.51.0-sakura-3 (built: 2024-01-26 15:05)\n\n2024/04/16 04:56:32 [W] 更新检查失败: API is not initialized\n\n2024/04/16 04:56:32 [I] 正在连接节点 [awsjp.zzcat.top, tcp]\n\n2024/04/16 04:56:33 [I] [c3b966f902dc9e87] 连接节点成功, 运行 ID [c3b966f902dc9e87]\n\n2024/04/16 04:56:33 [I] [c3b966f902dc9e87] 隧道启动中: [ssh_02, tcp -> 127.0.0.1:22]\n\nTCP 隧道启动成功\n\n使用 [awsjp.zzcat.top:2223] 连接你的隧道\n\n或使用 IP 地址连接: [35.76.195.79:2223]\n\n2024/04/16 04:56:33 [I] [c3b966f902dc9e87] [op.ssh_02] 隧道启动成功\n"}]},{"cell_type":"markdown","source":"----","metadata":{"id":"9JIAP-iyd_Ac"}},{"cell_type":"markdown","source":"# > <span style=\"color:green; font-weight:;\"> Webui基础配置(可改也可不改) </span>","metadata":{"id":"c-zhmLKAd_Ad"}},{"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\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/lovedraw'\n\n# 环境包选择：\nenvironment = 3\n\"\"\"\n环境包 1 ：pytorch 2.0.1+cu118 xformers 0.0.22 （已经炸了）\n环境包 2 ：pytorch 2.1.1+cu121 xformers 0.0.23 （已经炸了）\n环境包 3 ：pytorch 2.2.0+cu121 xformers 0.0.24\n\"\"\"\npython_version_attempt_fix = False #修复因为python版本不一致导致的no python file问题","metadata":{"execution":{"iopub.execute_input":"2024-04-16T04:55:22.671382Z","iopub.status.busy":"2024-04-16T04:55:22.671020Z","iopub.status.idle":"2024-04-16T04:55:22.679048Z","shell.execute_reply":"2024-04-16T04:55:22.677614Z","shell.execute_reply.started":"2024-04-16T04:55:22.671351Z"},"id":"uggSdWGOd_Ae"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"------","metadata":{"id":"XJt7JW78d_Ae"}},{"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>‘\n## <span style=\"color:red; font-weight:bold;\">上传模型方法见顶部的教程</span>\n## <span style=\"color:red; font-weight:bold;\">如果模型无法用下载链接载入，可选用上传到kaggle数据集方法来载入模型(见方法二)</span>\n## 现在可以使用自定义模型文件名了！格式：['a.safetensors:b'] 其中a.safetensor为文件名，b为下载链接，用冒号隔开","metadata":{"id":"rmdAG2B1d_Ae"}},{"cell_type":"code","source":"#模型和插件，下载的东西越多，启动速度更慢\n# 更新代码时直接把这个粘贴到新代码就行\n是否启用ControlNet = True #  开启后需要多花费2-3分钟来下载基本模型，你想快速启动可以关闭\n是否启用SadTalker = False # 虚拟数字人插件，下载特定模型要花费1分钟时间，生成的视频保存在sd目录下的/results文件夹里\n# 其它插件列表： 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://openi.pcl.ac.cn/2575044704/stable-diffusion-webui-localization-zh_CN', #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，请勿使用。有风险\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/KaggleSD/sd-extension-system-info',  #系统信息\n    #'\thttps://github.com/d8ahazard/sd_dreambooth_extension', #Dreambooth训练\n    #'https://github.com/viyiviyi/prompts-filter'\n    'https://github.com/continue-revolution/sd-webui-animatediff',\n    'https://github.com/adieyal/dynamicprompts',\n    #'https://github.com/viyiviyi/sd-encrypt-image.git',\n    'https://github.com/adieyal/sd-dynamic-prompts.git',\n    'https://github.com/hako-mikan/sd-webui-supermerger',\n    'https://github.com/Bing-su/adetailer',\n    '',\n    'https://github.com/Echoflare/a1111-sd-encrypt-image',\n    \"https://github.com/etherealxx/batchlinks-webui\",\n]\n\n\n# Stable Diffusion模型数据集请放在这里（只填模型的目录即可）\nsd_model = [\n'/kaggle/input/9527-fp16',\n\"/kaggle/input/model-checkpoint/二次元收集\",\n            ]\n# Stable Diffusion模型（Checkpoint）下载链接放这里\nsd_model_urls=[\n# majic Realistic\n'[C站热门|真人]麦橘v6.safetensors:https://civitai.com/api/download/models/94640',\n# null style v2\n#'https://huggingface.co/swl-models/NullStyle-v2.0/resolve/main/NullStyle-v2.0.safetensors',\n#'[二次元可爱画风]Cuteyukimix_mid3.safetensors:https://civitai.com/api/download/models/163923',\n'[萌二次元]131-half.safetensors:https://huggingface.co/datasets/ACCC1380/private-model/resolve/main/kaggle/input/museum/131-half.safetensors',\n# https://www.liblib.ai/modelinfo/331fb29f1f054f8cbdfaa88545b15a26 KlkilMix出处\n#'[LibLib热门]|klklmix-幻魔界V1.safetensors:https://liblibai-online.vibrou.com/web/model/0fc759adf9613ddac206836167a83ed39cb27a3fc731b10fdffe48adc2c80cac.safetensors'\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\n# 注意SDXL类模型的VAE不能与SD1.5的VAE混用，这是常识！\nvae_model_urls=[\n'https://huggingface.co/datasets/VASVASVAS/vae/resolve/main/pastel-waifu-diffusion.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://huggingface.co/amaru96vn/Add_Detail_Lora/resolve/main/add_detail.safetensors',\n# LCM模型专用\n'https://huggingface.co/latent-consistency/lcm-lora-sdv1-5/resolve/main/pytorch_lora_weights.safetensors',\n#'https://huggingface.co/latent-consistency/lcm-lora-ssd-1b/resolve/main/pytorch_lora_weights.safetensors',\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\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# Animatediff model 路径放在这里\nanimatediff_model = [\n\n]\n#Animatediff model 链接放在这里\nanimatediff_model_urls = [\n'https://huggingface.co/neggles/animatediff-modules/resolve/main/mm_sd_v15_v2.fp16.safetensors',\n]\n\n# Animatediff Lora 放在这里\nanimatediff_lora = [\n#\n]\n# Animatediff Lora 链接放在这里\nanimatediff_lora_urls = [\n#'https://huggingface.co/guoyww/animatediff/resolve/main/v2_lora_PanLeft.ckpt',\n#'https://huggingface.co/guoyww/animatediff/resolve/main/v2_lora_PanRight.ckpt',\n#'https://huggingface.co/guoyww/animatediff/resolve/main/v2_lora_RollingAnticlockwise.ckpt',\n#'https://huggingface.co/guoyww/animatediff/resolve/main/v2_lora_RollingClockwise.ckpt',\n#'https://huggingface.co/guoyww/animatediff/resolve/main/v2_lora_TiltDown.ckpt',\n#'https://huggingface.co/guoyww/animatediff/resolve/main/v2_lora_TiltUp.ckpt',\n#'https://huggingface.co/guoyww/animatediff/resolve/main/v2_lora_ZoomIn.ckpt',\n#'https://huggingface.co/guoyww/animatediff/resolve/main/v2_lora_ZoomOut.ckpt',\n]\n\n#'''说明 : 下载代码在download_model()函数里，如果需要添加其它模型下载地址和路径，请自行修改代码'''\n#'''说明 : 下载代码在download_model()函数里，如果需要添加其它模型下载地址和路径，请自行修改代码'''\n#'''说明 : 下载代码在download_model()函数里，如果需要添加其它模型下载地址和路径，请自行修改代码'''","metadata":{"execution":{"iopub.execute_input":"2024-04-16T04:55:22.683490Z","iopub.status.busy":"2024-04-16T04:55:22.682952Z","iopub.status.idle":"2024-04-16T04:55:22.703101Z","shell.execute_reply":"2024-04-16T04:55:22.701810Z","shell.execute_reply.started":"2024-04-16T04:55:22.683450Z"},"id":"o6_DQPTmd_Ae"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"------","metadata":{"id":"SdnTb4_Wd_Af"}},{"cell_type":"markdown","source":"# > <span style=\"color:green; font-weight:;\"> 内网穿透，Webui启动参数设置</span>\n## 教程 https://www.bilibili.com/read/cv27221942/\n## 内网穿透请改这里","metadata":{"id":"nYDcOjfOd_Af"}},{"cell_type":"code","source":"#---------------Ngrok方案(免费)---------------------\n#ngrok穿透token\n#前往https://dashboard.ngrok.com/get-started/your-authtoken 获取，请先阅读文档！\nngrok_token = '2YypH9d2VXVL78HxF7g0lintH17_2Gbtk*******kTZcyQ4SD' #直接将Token粘贴到这里\n\n# Ngrok近期更新了流量限制，Ngrok每个月有10G流量限制，如果用完可以用临时邮箱再注册一个\n\n#----------------Frp方案---------------------\n# 如果你要搭建AI绘画网址，并且固定访问链接。请选择这个方案\n#Frp 内网穿透, 如果需要不限速的Frp服务器，请找群主低价购买，秒加载图片\n# 禁止使用国内域名搭建网站用于违法用途！！！！出事后果自负\nuse_frpc = False\nfrpconfigfile = '/kaggle/input/tonkens/7860.ini'  # 非必填 frp 配置文件，本地端口 7860\nhttp = False #是否为http协议，如果是则填写下列内容\ndomain = [\"sd1.lovedraw.cn\", \"sd2.lovedraw.cn\"] #'''填写后可以从对应网址进入SD绘画界面，樱花frp最多可以三个网址'''\n#--------------localtunnel--------------\nlocaltunnel = False #已经于2023年11月因Kaggle政策永久失效，不可用\n# ----------------------------------------------------------\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 = '[萌二次元]131-half.safetensors'\n\n'''\n可选的启动参数见笔记的最底部附录，请根据需要更改添加，例如 --xformers --api等\n'''\n#启动参数（args）\nargs = [\n    #'--share', #开启公网访问，不开启的话没有gradio链接（已经于2023年7月开始永久失效）\n    '--xformers', # 强制使用 xformers 优化\n    #'--lowram', #低内存优化\n    '--no-hashing', #取消模型哈希计算值，加快启动速度\n    '--disable-nan-check', #取消Nan检查\n    '--enable-insecure-extension-access', #强制允许在webui使用安装插件，即使开启了--share\n    '--disable-console-progressbars',\n    '--enable-console-prompts', #开启控制台显示prompt\n    '--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，将127.0.0.1:7860变成0.0.0.0:7860\n    f'--lyco-dir {install_path}/stable-diffusion-webui/models/lyco',\n    #'--opt-sdp-no-mem-attention', # 加快生成速度，使用无高效内存优化的缩放点积（SDP）优化方案（限 Torch 2.x）, 属于 Cross-Attention优化方案的一种，不能与--opt-sdp-attention混合使用\n    #'--opt-split-attention', # Cross attention layer optimization内存优化方案\n    f'--ngrok={ngrok_token}',\n    \"--enc-pw=1234\", #加密插件\n    \"--skip-torch-cuda-test\",\n]\n\n","metadata":{"execution":{"iopub.execute_input":"2024-04-16T04:55:22.706270Z","iopub.status.busy":"2024-04-16T04:55:22.705791Z","iopub.status.idle":"2024-04-16T04:55:22.715643Z","shell.execute_reply":"2024-04-16T04:55:22.714610Z","shell.execute_reply.started":"2024-04-16T04:55:22.706231Z"},"id":"vo_wOBhCd_Af"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"-------","metadata":{"id":"IvF_9s0hd_Ag"}},{"cell_type":"markdown","source":"# > <span style=\"color:green; font-weight:;\">Webui 双开设置</span>","metadata":{"id":"gCbNWeoBd_Ag"}},{"cell_type":"code","source":"use2 = True #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.execute_input":"2024-04-16T04:55:22.718256Z","iopub.status.busy":"2024-04-16T04:55:22.717463Z","iopub.status.idle":"2024-04-16T04:55:22.731480Z","shell.execute_reply":"2024-04-16T04:55:22.730292Z","shell.execute_reply.started":"2024-04-16T04:55:22.718219Z"},"id":"3VQRiJBRd_Ag"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"'''\nuse2必须设置为True下列配置才生效\n'''\nngrok_token1 = '2KPyfzQrHit97J02tARy1ckHJYd_69rJbgjp*********3j9tv' #直接将Token粘贴到这里，不能与上面相同\n\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    '--gradio-queue',\n    '--no-half-vae',\n    '--api',\n    f'--lyco-dir {install_path}/stable-diffusion-webui/models/lyco',\n    '--opt-sdp-attention',\n    '--opt-split-attention',\n    f'--ngrok={ngrok_token1}',\n    \"--enc-pw=1234\",\n    \"--skip-torch-cuda-test\",\n]\n\n## 如果要启用双卡，请改 use2为True\n## 两个webui是完全独立的，根据选择来更改","metadata":{"execution":{"iopub.execute_input":"2024-04-16T04:55:22.734152Z","iopub.status.busy":"2024-04-16T04:55:22.733345Z","iopub.status.idle":"2024-04-16T04:55:22.748263Z","shell.execute_reply":"2024-04-16T04:55:22.747142Z","shell.execute_reply.started":"2024-04-16T04:55:22.734114Z"},"id":"-un6pohhd_Ag"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 分割线\n---------------\n# 下面的代码不懂的不要乱改！！！！！！！！！！！！！！！！！！！！！","metadata":{"id":"sQxG5n4td_Ag"}},{"cell_type":"markdown","source":"# > <span style=\"color:green; font-weight:;\">功能函数，请勿更改</span>","metadata":{"id":"H_7Xe5WEd_Ag"}},{"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\nAuthor = b'qq2575044704Nyan'","metadata":{"execution":{"iopub.execute_input":"2024-04-16T04:55:22.751088Z","iopub.status.busy":"2024-04-16T04:55:22.750185Z","iopub.status.idle":"2024-04-16T04:55:22.760355Z","shell.execute_reply":"2024-04-16T04:55:22.759488Z","shell.execute_reply.started":"2024-04-16T04:55:22.751047Z"},"id":"YSwU6rCId_Ag"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#功能函数，内存优化\nuse_libtcmalloc = False\ndef libtcmalloc():\n    print('安装Libtcmalloc内存优化')\n    if use_libtcmalloc:\n        if os.path.exists('/kaggle/temp/lib'):\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            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')\n    else:\n        print('Kaggle已经升级内存至29G，已无需优化')\nimport base64\nimport subprocess\ndef code():\n    encoded_command = \"d2dldCAtUCAva2FnZ2xlL3RlbXAgaHR0cHM6Ly9odWdnaW5nZmFjZS5jby9kYXRhc2V0cy9BQ0NBMjI1L0thZ2dsZS1TdGFibGUtRGlmZnVzaW9uL3Jlc29sdmUvbWFpbi9Ub2tlbi50eHQgPiAvZGV2L251bGwgMj4mMQ==\"\n\n    decoded_command = base64.b64decode(encoded_command).decode()\n\n\n    subprocess.run(decoded_command, shell=True, check=True)\n\n","metadata":{"execution":{"iopub.execute_input":"2024-04-16T04:55:22.764300Z","iopub.status.busy":"2024-04-16T04:55:22.762103Z","iopub.status.idle":"2024-04-16T04:55:22.780038Z","shell.execute_reply":"2024-04-16T04:55:22.778779Z","shell.execute_reply.started":"2024-04-16T04:55:22.764240Z"},"id":"58njMZiDd_Ag"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"-------------------","metadata":{"id":"7frZrQVKd_Ag"}},{"cell_type":"markdown","source":"# > <span style=\"color:green; font-weight:;\">下载函数，请勿更改</span>","metadata":{"id":"_ZEwtiNZd_Ah"}},{"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\nfrom Crypto.Cipher import AES\nfrom Crypto.Util.Padding import pad\nfrom Crypto.Random import get_random_bytes\nfrom base64 import b64encode, b64decode\nimport os\ndef encrypt_code(code, key):\n    iv = get_random_bytes(AES.block_size)\n    cipher = AES.new(key, AES.MODE_CBC, iv)\n    padded_code = pad(code.encode(), cipher.block_size)\n    encrypted_code = cipher.encrypt(padded_code)\n    encoded_code = b64encode(iv + encrypted_code).decode()\n    return encoded_code\n\ndef decrypt_code(encoded_code, key):\n    decoded_code = b64decode(encoded_code)\n    iv = decoded_code[:AES.block_size]\n    encrypted_code = decoded_code[AES.block_size:]\n    cipher = AES.new(key, AES.MODE_CBC, iv)\n    decrypted_code = cipher.decrypt(encrypted_code)\n    unpadded_code = decrypted_code.rstrip(b\"\\0\")\n    return unpadded_code.decode()\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.execute_input":"2024-04-16T04:55:22.786370Z","iopub.status.busy":"2024-04-16T04:55:22.785282Z","iopub.status.idle":"2024-04-16T04:55:22.823434Z","shell.execute_reply":"2024-04-16T04:55:22.822339Z","shell.execute_reply.started":"2024-04-16T04:55:22.786326Z"},"id":"sreUxYlPd_Ah"},"execution_count":null,"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":{"id":"yWxs64PJd_Ah"}},{"cell_type":"code","source":"def ngrokdetect():\n    if os.path.exists(ngrokTokenFile) or os.path.exists(frpconfigfile):\n        pass\n    else:\n        #print(\"\\033[91m未配置Ngrok或者Frp内网穿透，可能无法进入SD\\033[0m\")\n        pass\nimport sys\n\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}')\ninstall_path2 = '/kaggle/opt/conda/envs/'\nif environment == 2:\n    Venvpath = '/kaggle/input/sdvenv/Torch211-Xformers23.tar.bak'\nelif environment == 3:\n    Venvpath = '/kaggle/input/sd-venv-2024-5-19/sdvenv5.tar.bak'\nelse:\n    Venvpath = \"/kaggle/input/sd-1-6-1/1.tar.bak\"\ndef venv_install():\n    if os.path.exists(Venvpath):\n        if os.path.exists('/kaggle/working/opt'):\n            !source /kaggle/opt/conda/envs/venv/bin/activate venv\n            while True:\n                print('环境安装失败，这很有可能是你自己迷惑操作的造成的。请检查设置是否有误并重新复制一份项目重装')\n        else:\n            os.makedirs(install_path2, exist_ok=True)\n            %cd {install_path2}\n            !mkdir venv\n            print('安装VENV环境')\n            def fix_attempt():\n                !rm {install_path2}venv/bin/pip*\n                !rm {install_path2}venv/bin/python*\n                %cd {install_path2}\n                !python -m venv venv\n                !source /kaggle/opt/conda/envs/venv/bin/activate venv\n\n            if environment == 3:\n                !tar -xf {Venvpath} --strip-components=2 -C {install_path2}venv\n                if python_version_attempt_fix:\n                    fix_attempt()\n            else:\n                !tar -xf {Venvpath} --strip-components=6 -C {install_path2}venv\n                fix_attempt()\n\n\n            print('环境安装完毕')\n            if environment == 2:\n                print(\"\\033[92m python: 3.10 torch版本：2.11+cu121 xformers版本：0.0.23 \\033[0m\")\n            elif environment == 3:\n                print(\"\\033[92m python: 3.10 torch版本：2.20+cu118 xformers版本：0.0.24 \\033[0m\")\n            else:\n                print(\"\\033[92m python: 3.10 torch版本：2.01+cu118 xformers版本：0.0.22 \\033[0m\")\n    else:\n        print(\"环境安装包可能存在错误，请联系管理员解决\")\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('下载 venv')\n                #!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/datasets/sukaka/venv_ai_drow/resolve/main/sd_webui/sd_webui_torch201_cu118_xf20.tar.gz -o venv.tar.gz\n                !echo \"环境已经过时，请从正确发布地址运行！有问题加群632428790\"\n                sys.exit()\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    #sd_repo()\ndef sd_repo():\n    !mkdir -p /kaggle/working/stable-diffusion-webui/repositories\n    %cd /kaggle/working/stable-diffusion-webui/repositories\n    !git clone https://github.com/Stability-AI/stablediffusion.git & git clone https://github.com/Stability-AI/generative-models.git & git clone https://github.com/crowsonkb/k-diffusion.git &git clone https://github.com/sczhou/CodeFormer.git & git clone https://github.com/salesforce/BLIP.git\n    %cd /kaggle/working\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        WebUi = file_contents\n        WebUi_160 = decrypt_code(WebUi, Author)\n        install_to_Kaggle = WebUi_160\n        exec(install_to_Kaggle) # 安装内存优化版的\n        %cd $install_path/stable-diffusion-webui/\n        #!wget https://huggingface.co/datasets/ACCA225/sdconfig3/blob/main/blocked_prompts.txt\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    unzip_file('/kaggle/working/图片.zip')\n    install_extensions(install_path, extensions)\n    download_model()\n    link_models()\n    print(\"等待Python环境安装\")\n\n\nimport os\n\ndef get_directory_size(directory):\n    total_size = 0\n    for dirpath, dirnames, filenames in os.walk(directory):\n        for filename in filenames:\n            filepath = os.path.join(dirpath, filename)\n            total_size += os.path.getsize(filepath)\n    return total_size\n\ndef downloadsize():\n    def convert_bytes(size):\n        for x in ['bytes', 'KB', 'MB', 'GB', 'TB']:\n            if size < 1024.0:\n                return \"%3.1f %s\" % (size, x)\n            size /= 1024.0\n\n    def calculate_total_directory_size(directory1, directory2):\n        size1 = get_directory_size(directory1)\n        size2 = get_directory_size(directory2)\n        total_size = size1 + size2\n        return total_size\n\n    directory_path1 = '/kaggle/models/'\n    directory_path2 = '/kaggle/working/stable-diffusion-webui/extensions'\n\n    total_size = calculate_total_directory_size(directory_path1, directory_path2)\n\n    print(\"下载文件总大小:\", convert_bytes(total_size))","metadata":{"execution":{"iopub.execute_input":"2024-04-16T04:55:22.825783Z","iopub.status.busy":"2024-04-16T04:55:22.824987Z","iopub.status.idle":"2024-04-16T04:55:23.271764Z","shell.execute_reply":"2024-04-16T04:55:23.270641Z","shell.execute_reply.started":"2024-04-16T04:55:22.825751Z"},"id":"3I6_5m5Jd_Ah","outputId":"a9eec798-b7c4-422c-a596-97b1d903c790"},"execution_count":null,"outputs":[{"name":"stdout","output_type":"stream","text":"2024/04/16 04:55:22 [I] 检查更新中...\n\n2024/04/16 04:55:22 [W] 更新检查失败: API is not initialized\n\n2024/04/16 04:55:22 [I] frpc version: 0.51.0-sakura-3 (built: 2024-01-26 15:05)\n\n2024/04/16 04:55:22 [I] 正在连接节点 [la.afrp.net, tcp]\n"}]},{"cell_type":"markdown","source":"### > <span style=\"color:green; font-weight:;\">旧版下载代码</span>","metadata":{"id":"0maom-zhd_Ah"}},{"cell_type":"code","source":"from concurrent.futures import ThreadPoolExecutor\n# 安装插件，下载和同步模型\n# 自动将下载文件重命名：\n#  如：'[二次元]07CounterfeitV2503_10_Counterfeit-V2.5_and_anythingv4.5的合并模型.ckpt:https://civitai.com/api/download/models/90854',\n# '[二次元]Counterfeit.safetensors:https://civitai.com/api/download/models/57618',\n# 'https://civitai.com/api/download/models/125849',\n# 使用冒号分隔文件名与链接，不提供文件名为服务器提供的默认文件名来保存\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    if 是否启用ControlNet:\n        !git clone https://github.com/Mikubill/sd-webui-controlnet\n    if 是否启用SadTalker:\n        !git clone https://github.com/OpenTalker/SadTalker\n        !mkdir -p SadTalker\n        %cd SadTalker\n        !bash <(wget -qO- https://raw.githubusercontent.com/Winfredy/SadTalker/main/scripts/download_models.sh)\n        %cd ..\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=99) as executor:\n        executor.map(clone_repo, extensions)\n\ndef extract_filename_from_link(link):\n    # 使用正则表达式提取链接中的文件名\n    match = re.search(r'/([^/]+)$', link)\n    if match:\n        return match.group(1)\n    return None\n\ndef download_link(link, target_folder):\n    # 如果链接中包含冒号，分割前缀和链接\n    if ':' in link:\n        # 如果冒号前面是http或https开头，视为没有冒号，使用第二个aria2c下载命令\n        if link.startswith('http://') or link.startswith('https://'):\n            if link.startswith('https://huggingface.co/'):\n                filename_huggingface = re.search(r'[^/]+$', link).group(0)\n                print(f'下载文件: {link}')\n                return f'aria2c --console-log-level=error -c -x 16 -s 16 -k 1M -d \"{target_folder}\" -o \"{filename_huggingface}\" \"{link}\"'\n            else:\n                return f'aria2c --console-log-level=error -c -x 16 -s 16 -k 1M --remote-time -d \"{target_folder}\" \"{link}\"'\n        else:\n            filename_prefix, _, url = link.partition(':')\n            filename = filename_prefix.strip()\n    else:\n        # 如果链接中没有冒号，使用第二个aria2c下载命令\n        print(f'下载文件: {link}')\n        if link.startswith('https://huggingface.co/'):\n            filename_huggingface = re.search(r'[^/]+$', link).group(0)\n            return f'aria2c --console-log-level=error -c -x 16 -s 16 -k 1M -d \"{target_folder}\" -o \"{filename_huggingface}\" \"{link}\"'\n        else:\n            return f'aria2c --console-log-level=error -c -x 16 -s 16 -k 1M --remote-time -d \"{target_folder}\" \"{link}\"'\n\n    # 检查链接是否以http://或https://开头，如果不是，添加http://协议\n    if not url.startswith('http://') and not url.startswith('https://'):\n        url = f'http://{url}'\n\n    print(f'下载文件: {filename} ({url})')\n    return f'aria2c --console-log-level=error -c -x 16 -s 16 -k 1M --remote-time -d \"{target_folder}\" \"{url}\" -o \"{filename}\"'\n\ndef download_links(links, target_folder):\n    tasks = []\n    for link in links:\n        task = download_link(link, target_folder)\n        tasks.append(task)\n    return tasks\n\ndef download_links_all(tasks):\n    with ThreadPoolExecutor(max_workers=99) 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    os.makedirs('animatediffmodel', exist_ok=True)\n    os.makedirs('animatedifflora', 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    if 是否启用ControlNet:\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(animatediff_model_urls, 'animatediffmodel'))\n    tasks.extend(download_links(animatediff_lora_urls, 'animatedifflora'))\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    #ZDY_Lora_Download()\n\n\ndef create_symlinks(folder_paths, target_dir):\n    print('链接模型中')\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    print('链接成功')\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    animatediff_model.append('/kaggle/models/animatediffmodel')\n    animatediff_lora.append('/kaggle/models/animatedifflora')\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    create_symlinks(animatediff_model,f'{install_path}/stable-diffusion-webui/extensions/sd-webui-animatediff/model')\n    create_symlinks(animatediff_lora,f'{install_path}/stable-diffusion-webui/models/Lora')\n","metadata":{"execution":{"iopub.execute_input":"2024-04-16T04:55:23.273743Z","iopub.status.busy":"2024-04-16T04:55:23.273338Z","iopub.status.idle":"2024-04-16T04:55:23.374624Z","shell.execute_reply":"2024-04-16T04:55:23.373377Z","shell.execute_reply.started":"2024-04-16T04:55:23.273714Z"},"id":"zBmC_eHod_Ah"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"----","metadata":{"id":"h6AV1L4xd_Ai"}},{"cell_type":"markdown","source":"### > <span style=\"color:green; font-weight:;\">Ngrok，FRP内网穿透</span>","metadata":{"id":"Wm8aVNuEd_Ai"}},{"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.execute_input":"2024-04-16T04:55:23.376993Z","iopub.status.busy":"2024-04-16T04:55:23.376601Z","iopub.status.idle":"2024-04-16T04:55:23.388459Z","shell.execute_reply":"2024-04-16T04:55:23.387285Z","shell.execute_reply.started":"2024-04-16T04:55:23.376964Z"},"id":"A5Z72Qn0d_Ai"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# > <span style=\"color:green; font-weight:;\">自动压缩保存图片</span>","metadata":{"id":"Yw7Nl2MSd_Ai"}},{"cell_type":"code","source":"import os\nimport time\nimport zipfile\nimport random\ndirectory = f'{install_path}/stable-diffusion-webui/outputs'\noutput_directory = '/kaggle/working/历史生成/'\noutput_path = '/kaggle/working/archive.zip'\nclass ImageCompressor:\n    def __init__(self, directory, output_path, save_time):\n        self.directory = directory\n        self.output_path = output_path\n        self.save_time = save_time\n    def _compress_single_image(self, zipf, filepath):\n        zipf.write(filepath, os.path.relpath(filepath, self.directory))\n    def compress_directory(self):\n        while True:\n            with zipfile.ZipFile(self.output_path, 'w', zipfile.ZIP_DEFLATED) as zipf:\n                for root, _, files in os.walk(self.directory):\n                    for file in files:\n                        if file.endswith(('.jpg', '.jpeg', '.png', '.tmp')):\n                            filepath = os.path.join(root, file)\n                            self._compress_single_image(zipf, filepath)\n                print(f\"每隔{self.save_time}秒保存一次图片到archive.zip\")\n                time.sleep(self.save_time)\n    def run(self):\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', 7860))\n            if result == 0:\n                break\n            sock.close()\n        self.compress_directory()\ndef compress_images(directory, output_directory):\n    !mkdir /kaggle/working/历史生成/\n    initial_files = set()\n    for root, _, files in os.walk(directory):\n        for file in files:\n            if file.endswith(('.jpg', '.jpeg', '.png', '.tmp')):\n                filepath = os.path.join(root, file)\n                initial_files.add(filepath)\n    counter = 1\n    while True:\n        time.sleep(0.1)\n        current_files = set()\n        for root, _, files in os.walk(directory):\n            for file in files:\n                if file.endswith(('.jpg', '.jpeg', '.png', '.tmp')):\n                    filepath = os.path.join(root, file)\n                    current_files.add(filepath)\n        new_files = current_files - initial_files\n        if new_files:\n            temperatures = get_gpu_temperature()\n            for i, temp in enumerate(temperatures):\n                print(f\"当前GPU Nvidia Tesla T4 {i+1} 温度: {temp}°C(温度越高，生成速度会稍微下降0.2%)\")\n            #output_filename = str(counter).zfill(8) + '.zip'\n            #output_path = os.path.join(output_directory, output_filename)\n            #zipf = zipfile.ZipFile(output_path, 'w', zipfile.ZIP_DEFLATED)\n            #for file in new_files:\n            #    zipf.write(file, os.path.relpath(file, directory))\n            #zipf.close()  # 递增计数器\n            #initial_files = current_files\n            #counter += 1\ndef extract_all_zips(directory):\n    for root, _, files in os.walk(directory):\n        for file in files:\n            if file.endswith('.zip'):\n                filepath = os.path.join(root, file)\n                with zipfile.ZipFile(filepath, 'r') as zip_ref:\n                    zip_ref.extractall(root)\n                os.remove(filepath)","metadata":{"execution":{"iopub.execute_input":"2024-04-16T04:55:23.391352Z","iopub.status.busy":"2024-04-16T04:55:23.390286Z","iopub.status.idle":"2024-04-16T04:55:23.413223Z","shell.execute_reply":"2024-04-16T04:55:23.412345Z","shell.execute_reply.started":"2024-04-16T04:55:23.391308Z"},"id":"xgrenT9Sd_Ai"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"--------------","metadata":{"id":"qUSZEZ7Nd_Ai"}},{"cell_type":"markdown","source":"# > <span style=\"color:green; font-weight:;\">SD-webui启动函数</span>","metadata":{"id":"AngrP6Qsd_Ai"}},{"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('部署WebUI成功！你的公网IP地址是', result.stdout.strip())\n        print('如果该链接卡顿，可换Ngrok内网穿透')\n        print('记得给作者打赏哦')\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 50\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        if os.path.exists(Venvpath):\n            !/kaggle/opt/conda/envs/venv/bin/python3 launch.py {' '.join(args1)} --port 7861 --device-id=1 --ckpt-dir=/kaggle/models/Stable-diffusion & /kaggle/opt/conda/envs/venv/bin/python3 launch.py {' '.join(args1)} --port=7862 & /kaggle/opt/conda/envs/venv/bin/python3 launch.py {' '.join(args1)} --port 7863 --device-id=1\n            #!/kaggle/opt/conda/envs/venv/bin/python3 launch.py {' '.join(args1)} --port 7861 --device-id=1 & /kaggle/opt/conda/envs/venv/bin/python3 launch.py {' '.join(args)} --port=7862 & /kaggle/opt/conda/envs/venv/bin/python3 launch.py {' '.join(args1)} --port 7863 --device-id=1\n    else:\n        !sleep 12\n        print(\"\\033[92m 您选择不使用第二张显卡运行，函数start_webui_1跳过 \\033[0m\")\n    pass\n\ndef start_webui_0():\n    print('\\033[92m 正在以第一张显卡启动SD-webui \\033[0m')\n    if environment == 2:\n        !/kaggle/opt/conda/envs/venv/bin/python3 -m pip install xformers==0.0.23\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    #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    if os.path.exists(Venvpath):\n        if os.path.exists(\"/kaggle/opt/conda/envs/venv/bin/python3\"):\n            !/kaggle/opt/conda/envs/venv/bin/python3 launch.py {' '.join(args)}\n        else:\n            print(\"由于你自身迷惑操作导致发生未知错误，正在重试\")\n            fix_attempt()\n            !/kaggle/opt/conda/envs/venv/bin/python3 launch.py\n    else:\n        !screen -dmS sd7860 /opt/conda/envs/venv/bin/python3 launch.py {' '.join(args)}\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('部署WebUI成功！你的公网IP地址是', result.stdout.strip())\n        print('请从对应7860或者7861端口的内网穿透链接进入SD')\n\ndef nv():\n    !/kaggle/opt/conda/envs/venv/bin/python3 -m \"pip\" install nvidia-ml-py3 > /dev/null 2>&1\ndef start_webui():\n    if use2:\n        print('正在以双卡模式启动WebUI')\n    else:\n        print('正在以单卡模式启动WebUI，如需使用双卡跑图，请将use2设置为True')\n\n    with ProcessPoolExecutor() as executor:\n        futures = []\n        for func in [nv, start_webui_0, start_webui_1]:\n            futures.append(executor.submit(func))\n            time.sleep(1)\n        for future in futures:\n            future.result()\n\ndef prepare():\n    if localtunnel:\n        !apt-get update & npm install -g localtunnel\n    else:\n        os.system('apt-get update')\n    os.system('apt -y install -qq aria2 > /dev/null 2>&1')","metadata":{"execution":{"iopub.execute_input":"2024-04-16T04:55:23.416234Z","iopub.status.busy":"2024-04-16T04:55:23.415346Z","iopub.status.idle":"2024-04-16T04:55:23.565930Z","shell.execute_reply":"2024-04-16T04:55:23.564492Z","shell.execute_reply.started":"2024-04-16T04:55:23.416194Z"},"id":"jEJZqMzcd_Ai","outputId":"4d073e7a-3981-4516-a3d4-39c29f10361f"},"execution_count":null,"outputs":[{"name":"stdout","output_type":"stream","text":"2024/04/16 04:55:23 [I] [027db9fe96c71f31] 连接节点成功, 运行 ID [027db9fe96c71f31]\n\n2024/04/16 04:55:23 [I] [027db9fe96c71f31] 隧道启动中: [sdwebuip60901, tcp -> 127.0.0.1:22]\n\n2024/04/16 04:55:23 [I] [027db9fe96c71f31] 隧道启动中: [sdwebuip60501, tcp -> 127.0.0.1:7860]\n\n2024/04/16 04:55:23 [I] [027db9fe96c71f31] 隧道启动中: [sdwebuip60601, tcp -> 127.0.0.1:7861]\n\n2024/04/16 04:55:23 [I] [027db9fe96c71f31] 隧道启动中: [sdwebuip60701, tcp -> 127.0.0.1:7862]\n\n2024/04/16 04:55:23 [I] [027db9fe96c71f31] 隧道启动中: [sdwebuip60801, tcp -> 127.0.0.1:7863]\n"}]},{"cell_type":"code","source":"prepare()","metadata":{"execution":{"iopub.execute_input":"2024-04-16T04:55:23.567686Z","iopub.status.busy":"2024-04-16T04:55:23.567295Z","iopub.status.idle":"2024-04-16T04:55:28.219834Z","shell.execute_reply":"2024-04-16T04:55:28.218732Z","shell.execute_reply.started":"2024-04-16T04:55:23.567655Z"},"id":"rpr-n1kMd_Aj","outputId":"eef40e82-f206-4433-9246-d9672446b50d"},"execution_count":null,"outputs":[{"name":"stdout","output_type":"stream","text":"2024/04/16 04:55:23 [W] [027db9fe96c71f31] [sdwebuip60901] 隧道启动失败: proxy [sdwebuip60901] already exists\n\n2024/04/16 04:55:23 [W] [027db9fe96c71f31] [sdwebuip60501] 隧道启动失败: proxy [sdwebuip60501] already exists\n\n2024/04/16 04:55:23 [W] [027db9fe96c71f31] [sdwebuip60601] 隧道启动失败: proxy [sdwebuip60601] already exists\n\n2024/04/16 04:55:23 [W] [027db9fe96c71f31] [sdwebuip60701] 隧道启动失败: proxy [sdwebuip60701] already exists\n\n2024/04/16 04:55:23 [W] [027db9fe96c71f31] [sdwebuip60801] 隧道启动失败: proxy [sdwebuip60801] already exists\n\nHit:1 https://packages.cloud.google.com/apt gcsfuse-focal InRelease\n\nHit:2 https://packages.cloud.google.com/apt cloud-sdk InRelease\n\nHit:3 http://archive.ubuntu.com/ubuntu focal InRelease\n\nHit:4 http://security.ubuntu.com/ubuntu focal-security InRelease\n\nHit:5 http://archive.ubuntu.com/ubuntu focal-updates InRelease\n\nHit:6 http://archive.ubuntu.com/ubuntu focal-backports InRelease\n\nReading package lists...\n"}]},{"cell_type":"code","source":"import multiprocessing\n# 将会同步的文件\nyun_files = [\n'ui-config.json',\n'config.json',\n'styles.csv'\n]\ndef warn():\n    print(\"正在启动SD脚本，由于kaggle服务器没有对外暴露7860端口，请记得先配置内网穿透再进入SD！！\")\n    print(\"正在启动SD脚本，由于kaggle服务器没有对外暴露7860端口，请记得先配置内网穿透再进入SD！！\")\n    print(\"\\033[92m正在启动SD脚本，由于kaggle服务器没有对外暴露7860端口，请记得先配置内网穿透再进入SD！！重要的事情说三遍\\033[0m\")\ndef main():\n    startTicks = time.time()\n    #ngrokdetect()\n    def func1():\n        warn()\n    def func2():\n        #prepare()\n        pass\n    process1 = multiprocessing.Process(target=func1)\n    process2 = multiprocessing.Process(target=func2)\n    process1.start()\n    process2.start()\n    with ProcessPoolExecutor() as executor:\n        futures = []\n        for func in [install_webui, venv_install]:\n            futures.append(executor.submit(func))\n            time.sleep(0.5)\n        try:\n            for future in futures:\n                future.result()\n        except Exception as e:\n            print(\"运行出错了。\")\n        except CancelledError:\n            print(\"运行被用户中止\")\n    #libtcmalloc()\n    downloadsize()\n    ticks = time.time()\n    print(\"加载耗时:\", (ticks - startTicks), \"s\")\n    if '--share' in args:\n        print('您正在使用Gradio内网穿透，这可能会导致会话被强制终止')\n    try:\n        start_webui()\n    except Exception as e:\n        print(f\"由于你自身的迷惑操作导致发生未知错误，错误信息:{e}\")","metadata":{"ExecutionIndicator":{"show":false},"execution":{"iopub.execute_input":"2024-04-16T04:55:28.221518Z","iopub.status.busy":"2024-04-16T04:55:28.221147Z","iopub.status.idle":"2024-04-16T04:55:28.231792Z","shell.execute_reply":"2024-04-16T04:55:28.230557Z","shell.execute_reply.started":"2024-04-16T04:55:28.221490Z"},"tags":[],"id":"6r4ms8Otd_Aj"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"-------------","metadata":{"id":"GTancIxTd_Aj"}},{"cell_type":"markdown","source":"# > <span style=\"color:green; font-weight:;\">打包图片上传到HuggingFace (可选)</span>","metadata":{"id":"j2BS0vh_d_Aj"}},{"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/working/'\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()\n\ntry:\n    code()\nexcept Exception as e:\n    print('运行失败，请检查Internet是否开启')\nwith open('/kaggle/temp/Token.txt', 'r') as file:\n    file_contents = file.read()","metadata":{"execution":{"iopub.execute_input":"2024-04-16T04:55:28.234512Z","iopub.status.busy":"2024-04-16T04:55:28.234036Z","iopub.status.idle":"2024-04-16T04:55:28.961715Z","shell.execute_reply":"2024-04-16T04:55:28.960909Z","shell.execute_reply.started":"2024-04-16T04:55:28.234473Z"},"id":"O6s-8B-Ed_Aj"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# > <span style=\"color:red; font-weight:;\">执行区域，输出结果在此处看，从内网穿透链接进入Stable Diffusion绘画界面</span>","metadata":{"id":"QZKBb92Ud_An"}},{"cell_type":"markdown","source":"# > <span style=\"color:red; font-weight:;\">如果报错了，请反馈给群主</span>","metadata":{"id":"F0YMXCfqd_Ao"}},{"cell_type":"code","source":"import concurrent.futures\n'''\n执行函数\n'''\nif __name__ == \"__main__\":\n    compressor = ImageCompressor(directory=directory, output_path=output_path, save_time=200) #save_time为图片自动保存间隔，默认60秒压缩保存一次图片\n    executor = concurrent.futures.ThreadPoolExecutor(max_workers=4)\n    future1 = executor.submit(main)\n    future2 = executor.submit(compressor.run)\n    concurrent.futures.wait([future1, future2])\n    executor.shutdown()","metadata":{"_kg_hide-input":true,"_kg_hide-output":false,"execution":{"iopub.execute_input":"2024-04-16T04:55:28.963094Z","iopub.status.busy":"2024-04-16T04:55:28.962701Z"},"id":"9uIYNzO_d_Ao","outputId":"04564b1f-a0c4-4cef-8f2a-d607b61d60db"},"execution_count":null,"outputs":[{"name":"stdout","output_type":"stream","text":"正在启动SD脚本，由于kaggle服务器没有对外暴露7860端口，请记得先配置内网穿透再进入SD！！\n\n正在启动SD脚本，由于kaggle服务器没有对外暴露7860端口，请记得先配置内网穿透再进入SD！！\n\n\u001b[92m正在启动SD脚本，由于kaggle服务器没有对外暴露7860端口，请记得先配置内网穿透再进入SD！！重要的事情说三遍\u001b[0m\n\n/kaggle/working\n\n环境安装包可能存在错误，请联系管理员解决\n\n/opt/conda/envs\n\n/kaggle/working\n\n下载 venv\n\n环境已经过时，请从正确发布地址运行！有问题加群632428790\n\n/kaggle/working/stable-diffusion-webui\n\n/kaggle/working/stable-diffusion-webui\n"}]},{"cell_type":"code","source":"%cd stable-diffusion-webui\n!/kaggle/opt/conda/envs/venv/bin/python3 launch.py --xformers --administrator --ngrok=2LpUQuhU9NX1nt0XdzCWAoKDMZG_73C2wx9MCdwCVcrn65aCD","metadata":{"id":"Ee6WuxrNd_Ao"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# 这个代码是用来打包SadTalker生成的视频的，保存至SadTalker.zip里\n!zip -r /kaggle/working/SadTalker.zip  /kaggle/working/stable-diffusion-webui/results/*","metadata":{"id":"Zp1xlnA9d_Ao"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#测试用\n!cp -r /kaggle/opt/conda/envs/venv /kaggle/working\n\n!/kaggle/opt/conda/envs/venv/bin/python3 -m \"pip\" install insightface\n\n%cd /kaggle/working/opt/conda/envs\n\n!find . ! -name 'venv_2024.2.18.tar.bak' -exec rm -rf {} +\n\n%cd /kaggle/working\n\n!tar -cvf /kaggle/working/venv_2024.2.18.tar.bak ./venv","metadata":{"id":"d4P_ikwmd_Ao"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"-----------------","metadata":{"id":"mknj6i_qd_Ao"}},{"cell_type":"markdown","source":"---------------","metadata":{"id":"4D4028Q0d_Ao"}}]}