# tagger script by @bdsqlsz # Train data path $train_data_dir = "./input" # input images path | 图片输入路径 $repo_id = "SmilingWolf/wd-v1-4-swinv2-tagger-v2" # model repo id from huggingface |huggingface模型repoID $model_dir = "" # model dir path | 本地模型文件夹路径 $batch_size = 4 # batch size in inference 批处理大小,越大越快 $max_data_loader_n_workers = 0 # enable image reading by DataLoader with this number of workers (faster) | 0最快 $thresh = 0.35 # concept thresh | 最小识别阈值 $general_threshold = 0.35 # general threshold | 总体识别阈值 $character_threshold = 0.1 # character threshold | 人物姓名识别阈值 $remove_underscore = 0 # remove_underscore | 下划线转空格,1为开,0为关 $undesired_tags = "" # no need tags | 排除标签 $recursive = 0 # search for images in subfolders recursively | 递归搜索下层文件夹,1为开,0为关 $frequency_tags = 0 # order by frequency tags | 从大到小按识别率排序标签,1为开,0为关 # Activate python venv .\venv\Scripts\activate $Env:HF_HOME = "huggingface" $Env:XFORMERS_FORCE_DISABLE_TRITON = "1" $ext_args = [System.Collections.ArrayList]::new() if ($repo_id) { [void]$ext_args.Add("--repo_id=" + $repo_id) } if ($model_dir) { [void]$ext_args.Add("--model_dir=" + $model_dir) } if ($batch_size) { [void]$ext_args.Add("--batch_size=" + $batch_size) } if ($max_data_loader_n_workers) { [void]$ext_args.Add("--max_data_loader_n_workers=" + $max_data_loader_n_workers) } if ($general_threshold) { [void]$ext_args.Add("--general_threshold=" + $general_threshold) } if ($character_threshold) { [void]$ext_args.Add("--character_threshold=" + $character_threshold) } if ($remove_underscore) { [void]$ext_args.Add("--remove_underscore") } if ($undesired_tags) { [void]$ext_args.Add("--undesired_tags=" + $undesired_tags) } if ($recursive) { [void]$ext_args.Add("--recursive") } if ($frequency_tags) { [void]$ext_args.Add("--frequency_tags") } # run tagger accelerate launch --num_cpu_threads_per_process=8 "./scripts/finetune/tag_images_by_wd14_tagger.py" ` $train_data_dir ` --thresh=$thresh ` --caption_extension .txt ` $ext_args Write-Output "Tagger finished" Read-Host | Out-Null ;