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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# This notebook will guide you to make correct format of Huggingface dataset, in proper parquet format and visualizable in Huggingface dataset hub.\n",
"# We will take the example of the dataset \"Otter-AI/MMVet\" and convert it to the proper format."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/tiger/miniconda3/envs/llava/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from .autonotebook import tqdm as notebook_tqdm\n",
"100%|██████████| 499/499 [00:18<00:00, 26.87it/s]\n"
]
}
],
"source": [
"from datasets import Dataset, Features, Value, Image\n",
"import pandas as pd\n",
"from tqdm import tqdm\n",
"import os\n",
"\n",
"# Define the features for the dataset\n",
"features = Features(\n",
" {\n",
" \"video_name\": Value(dtype=\"string\"),\n",
" \"question\": Value(dtype=\"string\"),\n",
" \"answer\": Value(dtype=\"string\"),\n",
" }\n",
")\n",
"\n",
"df_items = {\n",
" \"video_name\": [],\n",
" \"question\": [],\n",
" \"answer\": [],\n",
"}\n",
"\n",
"description_root = \"/mnt/bn/vl-research/workspace/yhzhang/data/llava_video/video_detail_description/Test_Human_Annotated_Captions\"\n",
"videos = os.listdir(description_root)\n",
"for cur_video_name in tqdm(videos):\n",
" sample_set = {}\n",
" video_name = cur_video_name.split(\".\")[0]\n",
" with open(f\"{description_root}/{cur_video_name}\", encoding=\"utf-8-sig\") as f:\n",
" description = f.readlines()[0]\n",
" question = \"Please provide a detailed description of the video, focusing on the main subjects, their actions, and the background scenes\"\n",
" df_items[\"video_name\"].append(video_name)\n",
" df_items[\"question\"].append(question)\n",
" df_items[\"answer\"].append(description)\n",
" # Add other fields as necessary\n",
"\n",
"df_items = pd.DataFrame(df_items)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>video_name</th>\n",
" <th>question</th>\n",
" <th>answer</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>v_-6dz6tBH77I</td>\n",
" <td>Please provide a detailed description of the v...</td>\n",
" <td>The video is of a man in athletic clothes stan...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>v_-D1gdv_gQyw</td>\n",
" <td>Please provide a detailed description of the v...</td>\n",
" <td>The video begins with a man holding a knife in...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>v_-HpCLXdtcas</td>\n",
" <td>Please provide a detailed description of the v...</td>\n",
" <td>A man is standing behind a barbell placed on t...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>v_-IMXSEIabMM</td>\n",
" <td>Please provide a detailed description of the v...</td>\n",
" <td>The video starts with two people standing behi...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>v_-MbZ-W0AbN0</td>\n",
" <td>Please provide a detailed description of the v...</td>\n",
" <td>The video starts with an advertisement for fur...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" video_name question \\\n",
"0 v_-6dz6tBH77I Please provide a detailed description of the v... \n",
"1 v_-D1gdv_gQyw Please provide a detailed description of the v... \n",
"2 v_-HpCLXdtcas Please provide a detailed description of the v... \n",
"3 v_-IMXSEIabMM Please provide a detailed description of the v... \n",
"4 v_-MbZ-W0AbN0 Please provide a detailed description of the v... \n",
"\n",
" answer \n",
"0 The video is of a man in athletic clothes stan... \n",
"1 The video begins with a man holding a knife in... \n",
"2 A man is standing behind a barbell placed on t... \n",
"3 The video starts with two people standing behi... \n",
"4 The video starts with an advertisement for fur... "
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_items.head()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"dataset = Dataset.from_pandas(df_items, features=features)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Creating parquet from Arrow format: 100%|██████████| 1/1 [00:00<00:00, 340.67ba/s]\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Uploading the dataset shards: 100%|██████████| 1/1 [00:00<00:00, 2.46it/s]\n"
]
},
{
"data": {
"text/plain": [
"CommitInfo(commit_url='https://huggingface.co/datasets/lmms-lab/VideoDetailDescription/commit/ad8e58fa42ad8daf56808724a4bcf4724688194e', commit_message='Upload dataset', commit_description='', oid='ad8e58fa42ad8daf56808724a4bcf4724688194e', pr_url=None, pr_revision=None, pr_num=None)"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"hub_dataset_path = \"lmms-lab/VideoDetailDescription\"\n",
"dataset.push_to_hub(repo_id=hub_dataset_path, split=\"test\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "lmms-eval",
"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": "3.10.14"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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