TO8_Captionr.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "view-in-github"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/theovercomer8/captionr/blob/main/TO8_Captionr.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "OGgQmF2rO1DY"
      },
      "source": [
        "# Captionr by theovercomer8\n",
        "You can find the latest update to the notebook [here](https://github.com/theovercomer8/captionr).\n",
        "\n",
        "v. 0.3.0\n",
        "\n",
        "Changelog:\n",
        "\n",
        "* 2/27/23: Added fuzz_ratio for similarity matching\n",
        "* 2/15/23: Added Caption Editor widget\n",
        "* 2/12/23: Added BLIP2 questions\n",
        "* 2/11/23: Added BLIP2 support\n",
        "* 2/11/23: Added GDrive cell\n",
        "* 2/11/23: Refactored to support new captionr.py module\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "_IOte4F_aNLI"
      },
      "outputs": [],
      "source": [
        "#@title GDrive\n",
        "mount_drive = True #@param {type: 'boolean'}\n",
        "if mount_drive:\n",
        "  from google.colab import drive\n",
        "  drive.mount('/content/gdrive')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "ie6oPstv4Xx5"
      },
      "outputs": [],
      "source": [
        "#@title Install Dependencies\n",
        "#@markdown Installs requirements and imports CLIP data\n",
        "import os\n",
        "\n",
        "if not os.path.exists('/content/dataset'):\n",
        "  !mkdir /content/dataset\n",
        "%cd /content\n",
        "!git clone https://github.com/theovercomer8/captionr\n",
        "%cd /content/captionr\n",
        "!pip install -r requirements.txt\n",
        "!apt-get install aria2\n",
        "!pip install prettytable\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "P8Zrmzbu5gEP"
      },
      "outputs": [],
      "source": [
        "#@title Login to Huggingface hub\n",
        "from huggingface_hub import login\n",
        "%store -r\n",
        "\n",
        "#@markdown Login to Huggingface hub\n",
        "#@markdown 1. You need a Huggingface account.\n",
        "#@markdown 2. To create a huggingface token, go to https://huggingface.co/settings/tokens, then create a new token or copy an available token with the `Write` role.\n",
        "write_token = \"\" #@param {type:\"string\"}\n",
        "login(write_token, add_to_git_credential=True)\n",
        "\n",
        "%store write_token\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "Do6uhfD85t91"
      },
      "outputs": [],
      "source": [
        "#@title Download and Extract Zip (.zip)\n",
        "import os\n",
        "import shutil\n",
        "from pathlib import Path\n",
        "%store -r\n",
        "\n",
        "root_dir = '/content'\n",
        "#@markdown ### Define Zipfile URL or Zipfile Path\n",
        "zipfile_url_or_path = \"\" #@param {'type': 'string'}\n",
        "zipfile_dst = str(root_dir)+\"/zip_file.zip\"\n",
        "extract_to = \"/content/dataset\" #@param {'type': 'string'}\n",
        "\n",
        "if extract_to != \"\":\n",
        "  os.makedirs(extract_to, exist_ok=True)\n",
        "else:\n",
        "  extract_to = \"/content/dataset\"\n",
        "\n",
        "#@markdown This will ignore `extract_to` path and automatically extracting to `train_data_dir`\n",
        "is_dataset = False \n",
        "\n",
        "#@markdown Tick this if you want to extract all files directly to `extract_to` folder, and automatically delete the zip to save disk space\n",
        "auto_unzip_and_delete = False #@param{'type':'boolean'}\n",
        "\n",
        "dirname = os.path.dirname(zipfile_dst)\n",
        "basename = os.path.basename(zipfile_dst)\n",
        "\n",
        "try:\n",
        "  if zipfile_url_or_path.startswith(\"/content\"):\n",
        "    zipfile_dst = zipfile_url_or_path\n",
        "    if auto_unzip_and_delete == False:\n",
        "      if is_dataset:\n",
        "        extract_to = \"/content/dataset\"\n",
        "      !unzip -j {zipfile_dst} -d \"{extract_to}\"\n",
        "  elif zipfile_url_or_path.startswith(\"https://drive.google.com\"):\n",
        "    !gdown --fuzzy  {zipfile_url_or_path}\n",
        "  elif zipfile_url_or_path.startswith(\"magnet:?\"):\n",
        "    !aria2c --summary-interval=10 -c -x 10 -k 1M -s 10 {zipfile_url_or_path}\n",
        "  elif zipfile_url_or_path.startswith(\"https://huggingface.co/\"):\n",
        "    if '/blob/' in zipfile_url_or_path:\n",
        "      zipfile_url_or_path = zipfile_url_or_path.replace('/blob/', '/resolve/')\n",
        "\n",
        "    hf_token = write_token\n",
        "    user_header = f\"\\\"Authorization: Bearer {hf_token}\\\"\"\n",
        "    !aria2c --console-log-level=error --summary-interval=10 --header={user_header} -c -x 16 -k 1M -s 16 -d {dirname} -o {basename} {zipfile_url_or_path}\n",
        "  else:\n",
        "    !aria2c --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 -d {dirname} -o {basename} {zipfile_url_or_path}\n",
        "\n",
        "except Exception as e:\n",
        "  print(\"An error occurred while downloading the file:\", e)\n",
        "\n",
        "if is_dataset:\n",
        "  extract_to = '/content/dataset'\n",
        "\n",
        "if auto_unzip_and_delete:\n",
        "  !unzip -j {zipfile_dst} -d \"{extract_to}\"\n",
        "\n",
        "  path_obj = Path(zipfile_dst)\n",
        "  zipfile_name = path_obj.parts[-1]\n",
        "  \n",
        "  if os.path.isdir(zipfile_dst):\n",
        "    print(\"\\nThis zipfile doesn't exist or has been deleted \\n\")\n",
        "  else:\n",
        "    os.remove(zipfile_dst)\n",
        "    print(f\"\\n{zipfile_name} has been deleted\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "jt6lNJRa5aK6"
      },
      "outputs": [],
      "source": [
        "#@title Caption Wizard\n",
        "%cd /content/captionr\n",
        "\n",
        "from captionr.captionr_class import Captionr, CaptionrConfig\n",
        "from captionr.blip_cap import BLIP\n",
        "from captionr.blip2_cap import BLIP2\n",
        "from captionr.clip_interrogator import Interrogator, Config\n",
        "from captionr.coca_cap import Coca\n",
        "from captionr.git_cap import Git\n",
        "import os\n",
        "from PIL import Image\n",
        "import pathlib\n",
        "from tqdm import tqdm\n",
        "from prettytable import PrettyTable\n",
        "from IPython.core.display import display, HTML\n",
        "import gc\n",
        "import torch\n",
        "\n",
        "#@markdown Folder to scan for images\n",
        "folder_path = '/content/dataset' #@param {type:\"string\"}\n",
        "#@markdown Folder to output captions. Captions will be named the same as the input image with the chosen extension. Leave `output_path` blank to output captions side-by-side\n",
        "output_path = '' #@param {type:\"string\"}\n",
        "folder = [pathlib.Path(folder_path)]\n",
        "if output_path == '':\n",
        "  output = folder[0]\n",
        "else:\n",
        "  output = pathlib.Path(output_path)\n",
        "\n",
        "extension = 'txt' #@param ['txt','caption']\n",
        "#@markdown Action to take for existing caption files\n",
        "existing = 'ignore' #@param [ 'skip', 'ignore', 'copy', 'prepend', 'append']\n",
        "\n",
        "#@markdown Read caption from filename if caption file does not exist\n",
        "use_filename = False #@param {type:\"boolean\"}\n",
        "#@markdown ---\n",
        "\n",
        "#@markdown Max caption length\n",
        "cap_length = 150 #@param {type: \"slider\", min: 0, max: 400}\n",
        "\n",
        "#@markdown ---\n",
        "\n",
        "git = False #@param {type:\"boolean\"}\n",
        "coca = False #@param {type:\"boolean\"}\n",
        "blip = False #@param {type:\"boolean\"}\n",
        "#@markdown Will perform captioning in the priority set by `model_order` for any enabled models\n",
        "model_order = 'coca,git,blip' #@param ['coca,git,blip','coca,blip,git','git,coca,blip','git,blip,coca','blip,coca,git','blip,git,coca']\n",
        "#@markdown Phrases that will fail a caption pass and move to the fallback model. \n",
        "fail_phrases = 'a sign that says,writing that says,that says,with the word' #@param\n",
        "#@markdown ---\n",
        "#@markdown BLIP options (if BLIP enabled)\n",
        "use_blip2 = False #@param {type:\"boolean\"}\n",
        "#@markdown BLIP2 requires the Pro tier High-RAM shape to run. Any of the xl or larger models require a premium GPU.\n",
        "blip2_model = 'blip2_opt/pretrain_opt2.7b' #@param ['blip2_t5/pretrain_flant5xxl','blip2_opt/pretrain_opt2.7b', 'blip2_opt/pretrain_opt6.7b', 'blip2_opt/caption_coco_opt2.7b', 'blip2_opt/caption_coco_opt6.7b', 'blip2_t5/pretrain_flant5xl', 'blip2_t5/caption_coco_flant5xl']\n",
        "#@markdown Pipe `|` delimeted list of questions to ask BLIP2 and add answers as tags\n",
        "blip2_questions = '' #@param {type: \"string\"}\n",
        "#@markdown ---\n",
        "blip_beams = 8 #@param {type: \"slider\", min: 1, max: 100}\n",
        "blip_min = 30 #@param {type: \"slider\", min: 5, max: 75}\n",
        "blip_max = 56 #@param {type: \"slider\", min: 5, max: 75}\n",
        "\n",
        "#@markdown ---\n",
        "\n",
        "clip_model_name = 'ViT-H-14/laion2b_s32b_b79k' #@param ['ViT-L-14/openai',\"ViT-H-14/laion2b_s32b_b79k\"]\n",
        "\n",
        "#@markdown Use ViT-H for SD 2.x, ViT-L for SD 1.5\n",
        "#@markdown\n",
        "#@markdown Only used if one of the following flavor/artist/medium/movement/trending checkboxes are checked\n",
        "\n",
        "clip_use_flavor = True #@param {type:\"boolean\"}\n",
        "clip_max_flavors = 16 #@param {type: \"slider\", min: 1, max: 100}\n",
        "clip_use_artist = False #@param {type:\"boolean\"}\n",
        "clip_use_medium = False #@param {type:\"boolean\"}\n",
        "clip_use_movement = False #@param {type:\"boolean\"}\n",
        "clip_use_trending = False  #@param {type:\"boolean\"}\n",
        "#@markdown Clip method to use\n",
        "clip_method = 'interrogate_fast' #@param ['interrogate','interrogate_fast','interrogate_classic']\n",
        "#@markdown ---\n",
        "#@markdown Comma separated list of tags to ignore\n",
        "ignore_tags = '' #@param {type:\"string\"}\n",
        "#@markdown Find/replace in caption and tags. \n",
        "find = '' #@param {type:\"string\"}\n",
        "replace = '' #@param {type:\"string\"}\n",
        "#@markdown ---\n",
        "#@markdown Tag the caption with the containing folder. Useful when using nested folder structure. Can tag up to `folder_tag_levels` deep\n",
        "folder_tag = False #@param {type:\"boolean\"}\n",
        "folder_tag_levels = 1 #@param {type: \"slider\", min: 1, max: 10}\n",
        "#@markdown Do not tag folders any deeper than this path. Overrides `folder_tag_levels` if `folder_tag_stop` is shallower\n",
        "folder_tag_stop = '' #@param {type:\"string\"}\n",
        "#@markdown ---\n",
        "#@markdown Ensure tag uniqueness if checked\n",
        "uniquify_tags = True #@param {type:\"boolean\"}\n",
        "#@markdown Similarity % allowed. Tags exceeding this percentage will be filtered.\n",
        "fuzz_ratio = 60 #@param {type:\"slider\", min: 0, max: 100}\n",
        "#@markdown Text to prepend or append to the generated caption. Useful for adding a subject or style\n",
        "prepend_text = '' #@param {type:\"string\"}\n",
        "append_text = '' #@param {type:\"string\"}\n",
        "#@markdown Check `preview` to just perform a preview run without writing a caption file\n",
        "preview = False #@param {type:\"boolean\"}\n",
        "print_params = False #@param {type:\"boolean\"}\n",
        "#@markdown ---\n",
        "\n",
        "\n",
        "try:\n",
        "  config\n",
        "except NameError:\n",
        "  config = CaptionrConfig()\n",
        "\n",
        "try:\n",
        "  last_blip2_model\n",
        "except NameError:\n",
        "  last_blip2_model = ''\n",
        "\n",
        "config.folder = folder\n",
        "config.output = output\n",
        "config.existing = existing\n",
        "config.cap_length = cap_length\n",
        "config.git_pass = git\n",
        "config.coca_pass = coca\n",
        "config.blip_pass = blip\n",
        "config.model_order = model_order\n",
        "config.use_blip2 = use_blip2\n",
        "config.blip2_model = blip2_model\n",
        "config.blip2_questions = blip2_questions.split('|')\n",
        "config.blip_beams = blip_beams\n",
        "config.blip_min = blip_min\n",
        "config.blip_max = blip_max\n",
        "config.clip_model_name = clip_model_name\n",
        "config.clip_flavor = clip_use_flavor\n",
        "config.clip_artist = clip_use_artist\n",
        "config.clip_medium = clip_use_medium\n",
        "config.clip_movement = clip_use_movement\n",
        "config.clip_trending = clip_use_trending\n",
        "config.clip_method = clip_method\n",
        "config.fuzz_ratio = fuzz_ratio\n",
        "config.fail_phrases = fail_phrases\n",
        "config.ignore_tags = ignore_tags\n",
        "config.find = find\n",
        "config.replace = replace\n",
        "config.folder_tag = folder_tag\n",
        "config.folder_tag_levels = folder_tag_levels\n",
        "config.preview = preview\n",
        "config.use_filename = use_filename\n",
        "config.append_text = append_text\n",
        "config.prepend_text = prepend_text\n",
        "config.uniquify_tags = uniquify_tags\n",
        "config.device = 'cuda'\n",
        "config.extension = extension\n",
        "config.quiet = True\n",
        "config.base_path = '/content/captionr'\n",
        "\n",
        "\n",
        "\n",
        "debug_params = [\"folder\", \\\n",
        "                \"output\", \\\n",
        "                \"existing\", \\\n",
        "                \"cap_length\", \\\n",
        "                \"git_pass\", \\\n",
        "                \"coca_pass\", \\\n",
        "                \"blip_pass\", \\\n",
        "                \"model_order\", \\\n",
        "                \"use_blip2\", \\\n",
        "                \"blip2_model\", \\\n",
        "                \"blip2_questions\", \\\n",
        "                \"blip_beams\", \\\n",
        "                \"blip_min\", \\\n",
        "                \"blip_max\", \\\n",
        "                \"clip_model_name\", \\\n",
        "                \"clip_flavor\", \\\n",
        "                \"clip_artist\", \\\n",
        "                \"clip_medium\", \\\n",
        "                \"clip_medium\", \\\n",
        "                \"clip_movement\", \\\n",
        "                \"clip_trending\", \\\n",
        "                \"clip_method\", \\\n",
        "                \"fuzz_ratio\", \\\n",
        "                \"fail_phrases\", \\\n",
        "                \"ignore_tags\", \\\n",
        "                \"find\", \\\n",
        "                \"replace\", \\\n",
        "                \"folder_tag\", \\\n",
        "                \"folder_tag_levels\", \\\n",
        "                \"preview\", \\\n",
        "                \"use_filename\", \\\n",
        "                \"append_text\", \\\n",
        "                \"prepend_text\", \\\n",
        "                \"uniquify_tags\", \\\n",
        "                \"device\", \\\n",
        "                \"extension\", \\\n",
        "                \"quiet\", \\\n",
        "                \"debug\", \\\n",
        "                \"_git\", \\\n",
        "                \"_coca\", \\\n",
        "                \"_blip\", \\\n",
        "                \"_clip\", \\\n",
        "                \"base_path\"]\n",
        "if print_params:\n",
        "  table = PrettyTable()\n",
        "  table.field_names = [\"Hyperparameter\", \"Value\"]\n",
        "  for params in debug_params:\n",
        "      if params != \"\":\n",
        "          if getattr(config,params) == \"\":\n",
        "              value = \"False\"\n",
        "          else:\n",
        "              value = getattr(config,params)\n",
        "          table.add_row([params, value])\n",
        "  table.align = \"l\"\n",
        "  print(table)\n",
        "\n",
        "if folder_path == '':\n",
        "  print ('Folder is required')\n",
        "  exit()\n",
        "  \n",
        "\n",
        "if not config.git_pass \\\n",
        "      and not config.blip_pass \\\n",
        "      and not config.coca_pass \\\n",
        "      and not config.clip_flavor \\\n",
        "      and not config.clip_artist \\\n",
        "      and not config.clip_medium \\\n",
        "      and not config.clip_movement \\\n",
        "      and not config.clip_trending:\n",
        "  if config.existing == 'skip' \\\n",
        "      and  ( \\\n",
        "          ( \\\n",
        "              config.find is not None and config.find != '' \\\n",
        "              and config.replace is not None and config.replace != '' \\\n",
        "          ) \\\n",
        "          or config.folder_tag \\\n",
        "          or ( \\\n",
        "              config.prepend_text is not None \\\n",
        "              and config.prepend_text != '' \\\n",
        "          ) \\\n",
        "          or ( \\\n",
        "              config.append_text is not None \\\n",
        "              and config.append_text != '' \\\n",
        "          ) \\\n",
        "      ):\n",
        "\n",
        "      print ('existing=skip cannot be used for find/replace, folder tagging, text prepending/appending unless a caption model is selected. To run a caption pass without a model selected, please choose a different option for existing caption.')\n",
        "      exit()\n",
        "  else:\n",
        "      if config.existing == 'skip' \\\n",
        "          and not ( \\\n",
        "              (config.find is not None and config.find != '' \\\n",
        "              and config.replace is not None and config.replace != '') \\\n",
        "              or config.folder_tag \\\n",
        "              or (config.prepend_text is not None \\\n",
        "                  and config.prepend_text != '') \\\n",
        "              or (config.append_text is not None \\\n",
        "                  and config.append_text != '') \\\n",
        "          ):\n",
        "\n",
        "          print ('No captioning flags specified. Select a model or use CLIP tagging or use find/replace or use folder tagging or use append/prepend text to initiate captioning ')\n",
        "          exit()\n",
        "\n",
        "if config.coca_pass and config._coca is None:\n",
        "    print(\"Loading Coca Model...\")\n",
        "    config._coca = Coca(config.device,max_length=config.cap_length)\n",
        "\n",
        "if config.git_pass and config._git is None:\n",
        "    print(\"Loading Git Model...\")\n",
        "    config._git = Git(config.device,max_length=config.cap_length)\n",
        "\n",
        "if config.blip_pass and (config._blip is None or (config.blip2_model != last_blip2_model and config.use_blip2)):\n",
        "    if config.use_blip2:\n",
        "      if config.blip2_model != last_blip2_model:\n",
        "        config._blip = None\n",
        "        gc.collect()\n",
        "\n",
        "        with torch.no_grad():\n",
        "          torch.cuda.empty_cache()\n",
        "      print(\"Loading BLIP2 Model...\")\n",
        "      config._blip = BLIP2(config.device,model_name=config.blip2_model,max_length=config.cap_length)\n",
        "    else:\n",
        "      print(\"Loading BLIP Model...\")\n",
        "      config._blip = BLIP(config.device,beams=config.blip_beams,blip_max=config.blip_max, blip_min=config.blip_min)\n",
        "\n",
        "if config._clip == None and (config.clip_artist or config.clip_flavor or config.clip_medium or config.clip_movement or config.clip_trending):\n",
        "    print(\"Loading Clip Model...\")\n",
        "    config._clip = Interrogator(Config(clip_model_name=config.clip_model_name,\n",
        "                                        captionr_config=config,\n",
        "                                        quiet=config.quiet,\n",
        "                                        data_path=os.path.join(config.base_path,'data'),\n",
        "                                        cache_path=os.path.join(config.base_path,'data')))\n",
        "last_blip2_model = config.blip2_model\n",
        "\n",
        "paths = []\n",
        "cptr = Captionr(config=config)\n",
        "for folder in config.folder:\n",
        "    for root, dirs, files in os.walk(folder.absolute(), topdown=False):\n",
        "        for name in files:\n",
        "            if os.path.splitext(os.path.split(name)[1])[1].upper() not in ['.JPEG','.JPG','.JPE', '.PNG']:\n",
        "                continue\n",
        "            if config.extension not in os.path.splitext(os.path.split(name)[1])[1]:\n",
        "                cap_file = os.path.join(folder.absolute(),os.path.splitext(os.path.split(name)[1])[0] + f'.{config.extension}')\n",
        "            if not config.existing == 'skip' or not os.path.exists(cap_file):\n",
        "                paths.append(os.path.join(root, name))\n",
        "            else:\n",
        "                print(f'Caption file {cap_file} exists. Skipping.')\n",
        "for path in tqdm(paths):\n",
        "    display(HTML(f'<div>-----</div><h1>{path}</h1>'))\n",
        "    with Image.open(path).convert('RGB') as img:\n",
        "      display(img.resize((200,200)))\n",
        "    caption = cptr.process_img(path)\n",
        "    display(HTML(f'<h2>Final Caption</h2><div>{caption}</div>'))\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "HAaAtVBe_UJh"
      },
      "outputs": [],
      "source": [
        "import ipywidgets as widgets\n",
        "from io import BytesIO\n",
        "#@markdown #Edit Captions\n",
        "\n",
        "#@markdown - Open a tool to view/edit captions.\n",
        "\n",
        "paths=\"\"\n",
        "out=\"\"\n",
        "widgets_l=\"\"\n",
        "def Caption(path):\n",
        "    name = os.path.splitext(os.path.basename(path))[0]\n",
        "    ext=os.path.splitext(os.path.basename(path))[-1][1:]\n",
        "    if ext==\"jpg\" or \"JPG\":\n",
        "      ext=\"JPEG\"      \n",
        "\n",
        "    if os.path.exists(folder_path+\"/\"+name + '.' + extension):\n",
        "      with open(folder_path+\"/\"+name + '.' + extension, 'r') as f:\n",
        "          text = f.read()\n",
        "    else:\n",
        "      with open(folder_path+\"/\"+name + '.' + extension, 'w') as f:\n",
        "          f.write(\"\")\n",
        "          with open(folder_path+\"/\"+name + '.' + extension, 'r') as f:\n",
        "              text = f.read()   \n",
        "\n",
        "    img=Image.open(os.path.join(folder_path,path))\n",
        "    img=img.resize((420, 420))\n",
        "    image_bytes = BytesIO()\n",
        "    img.save(image_bytes, format=ext, qualiy=10)\n",
        "    image_bytes.seek(0)\n",
        "    image_data = image_bytes.read()\n",
        "    img= image_data  \n",
        "    image = widgets.Image(\n",
        "        value=img,\n",
        "        width=420,\n",
        "        height=420\n",
        "    )\n",
        "    text_area = widgets.Textarea(value=text, description='', disabled=False, layout={'width': '300px', 'height': '120px'})\n",
        "    \n",
        "\n",
        "    def update_text(text):\n",
        "        with open(folder_path+\"/\"+name + '.' + extension, 'w') as f:\n",
        "            f.write(text)\n",
        "\n",
        "    button = widgets.Button(description='Save', button_style='success')\n",
        "    button.on_click(lambda b: update_text(text_area.value))\n",
        "\n",
        "    return widgets.VBox([widgets.HBox([image, text_area, button])])\n",
        "\n",
        "\n",
        "paths = os.listdir(folder_path)\n",
        "paths = list(filter(lambda fn: not fn.endswith(extension), paths))\n",
        "\n",
        "widgets_l = widgets.Select(options=[\"Select an image to caption\"]+paths, rows=25)\n",
        "\n",
        "\n",
        "out = widgets.Output()\n",
        "\n",
        "def click(change):\n",
        "    with out:\n",
        "        out.clear_output()\n",
        "        display(Caption(change.new))\n",
        "\n",
        "widgets_l.observe(click, names='value')\n",
        "display(widgets.HBox([widgets_l, out]))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "F06v8KVh7m7j",
        "outputId": "79627b4e-fac1-4343-8d36-a85781784878"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Dataset repo: theovercomer8/to8highkey exists, skipping create repo\n",
            "\n"
          ]
        }
      ],
      "source": [
        "#@title Define your Huggingface Repo\n",
        "\n",
        "from huggingface_hub import HfApi\n",
        "from huggingface_hub.utils import validate_repo_id, HfHubHTTPError\n",
        "%store -r\n",
        "\n",
        "api = HfApi()\n",
        "user = api.whoami(write_token)\n",
        "\n",
        "#@markdown #### If your model/dataset repo doesn't exist, it will automatically create your repo.\n",
        "dataset_name = \"\" #@param{type:\"string\"}\n",
        "make_this_dataset_private = True #@param{type:\"boolean\"}\n",
        "\n",
        "datasets_repo = user['name']+\"/\"+dataset_name.strip()\n",
        "\n",
        "if dataset_name != \"\":\n",
        "  try:\n",
        "      validate_repo_id(datasets_repo)\n",
        "      api.create_repo(repo_id=datasets_repo,\n",
        "                      repo_type=\"dataset\",\n",
        "                      private=make_this_dataset_private)\n",
        "      print(\"Dataset Repo didn't exists, creating repo\")\n",
        "      print(\"Dataset Repo\",datasets_repo,\"created!\\n\")\n",
        "\n",
        "  except HfHubHTTPError as e:\n",
        "      print(f\"Dataset repo: {datasets_repo} exists, skipping create repo\\n\")\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "dUKhs0SB60VE"
      },
      "outputs": [],
      "source": [
        "#@title Upload Dataset\n",
        "from huggingface_hub import HfApi\n",
        "from pathlib import Path\n",
        "import shutil\n",
        "import zipfile\n",
        "import os\n",
        "\n",
        "api = HfApi()\n",
        "\n",
        "#@markdown #### This will be compressed to zip and  uploaded to datasets repo, leave it empty if not necessary\n",
        "dataset_path = \"/content/dataset\" #@param {type :\"string\"}\n",
        "dataset_name = \"dataset\" #@param {type :\"string\"}\n",
        "#@markdown #### Delete zip after upload\n",
        "delete_zip = True #@param {type :\"boolean\"}\n",
        "\n",
        "tmp_dataset = \"/content/dataset\"\n",
        "\n",
        "dataset_zip = f\"/content/{dataset_name}.zip\"\n",
        "\n",
        "\n",
        "#@markdown #### Other Information\n",
        "commit_message = \"\" #@param {type :\"string\"}\n",
        "\n",
        "if not commit_message:\n",
        "  commit_message = \"feat: upload captioned dataset\"\n",
        "\n",
        "def upload_dataset(dataset_paths, is_zip : bool):\n",
        "  path_obj = Path(dataset_paths)\n",
        "  dataset_name = path_obj.parts[-1]\n",
        "\n",
        "  if is_zip:\n",
        "    print(f\"Uploading dataset to https://huggingface.co/datasets/\"+datasets_repo)\n",
        "    print(f\"Please wait...\")\n",
        "\n",
        "    api.upload_file(\n",
        "        path_or_fileobj=dataset_paths,\n",
        "        path_in_repo=dataset_name,\n",
        "        repo_id=datasets_repo,\n",
        "        repo_type=\"dataset\",\n",
        "        commit_message=commit_message,\n",
        "    )\n",
        "    print(f\"Upload success, located at https://huggingface.co/datasets/\"+datasets_repo+\"/blob/main/\"+dataset_name+\"\\n\")\n",
        "  else:\n",
        "    print(f\"Uploading {dataset_name} to https://huggingface.co/datasets/\"+datasets_repo)\n",
        "    print(f\"Please wait...\")\n",
        "\n",
        "    api.upload_folder(\n",
        "        folder_path=dataset_paths,\n",
        "        path_in_repo=dataset_name,\n",
        "        repo_id=datasets_repo,\n",
        "        repo_type=\"dataset\",\n",
        "        commit_message=commit_message,\n",
        "        ignore_patterns=\".ipynb_checkpoints\",\n",
        "    )\n",
        "    print(f\"Upload success, located at https://huggingface.co/datasets/\"+datasets_repo+\"/tree/main/\"+dataset_name+\"\\n\")\n",
        "  \n",
        "def zip_file(tmp,zip):\n",
        "    zipfiles = zip \n",
        "    with zipfile.ZipFile(zipfiles, 'w') as zip:\n",
        "      for tmp, dirs, files in os.walk(tmp):\n",
        "          for file in files:\n",
        "              zip.write(os.path.join(tmp, file))\n",
        "\n",
        "def upload():\n",
        "  zip_file(tmp_dataset,dataset_zip)\n",
        "  upload_dataset(dataset_zip, True)\n",
        "  if delete_zip:\n",
        "    os.remove(dataset_zip)\n",
        "\n",
        "upload()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-hJm9VY0E_9_"
      },
      "source": [
        "\n",
        "\n",
        "\n",
        "<a href=\"https://ko-fi.com/theovercomer8\" target=\"_blank\">![blunt2.png](data:image/png;base64,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)</a>"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "include_colab_link": true,
      "machine_shape": "hm",
      "provenance": []
    },
    "gpuClass": "standard",
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "name": "python",
      "version": "3.10.9"
    },
    "vscode": {
      "interpreter": {
        "hash": "aee8b7b246df8f9039afb4144a1f6fd8d2ca17a180786b69acc140d282b71a49"
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}