The dataset viewer is not available because its heuristics could not detect any supported data files. You can try uploading some data files, or configuring the data files location manually.

Game Playthrough

最终解析出的语料在 honkai_impact_3rd_chinese_dialogue_corpus

See honkai_impact_3rd_chinese_dialogue_corpus for final parsed result!

Description (English)

This is a collection of playthrough videos of Honkai Impact 3rd from Hoyoverse, along with efforts to build a Chinese text corpus (with OCR and MLLM-based parsing).

The language setting is Chinese.

All credits to the source author from BiliBili

The dataset contains the following contents:

  • Videos: The video-only files, corresponding to all videos in the source. Mostly in 1280x720 aspect ratio, HEVC encoding.
  • Audios: The audio-only files, coresponding to all the videos. Mostly in M4A format with various kbps.
  • OCR-Results (Raw): The OCR results for all the frames every 1 second. This process is done by using Paddle-OCR.
  • VLM-Parsed corpus: Given the OCR-results and image frames, hopefully we will parse the raw info into structured story narrations and dialogues (with associated speaker & content). This process will be done by using strong vision language models.

Up-to-date: 2024.08.08

Latest video: [P186]主线第二部03间章:一个梦游者的苦痛-02[720P 高清]

Description (Chinese)

本 Repo 收集了崩坏3的CG + 剧情对话视频,同时基于 OCR 和多模态大语言模型构造相应的中文崩坏3剧情语料。

感谢 B站视频Up主

数据集包括以下部分:

  • 视频:纯视频文件 source. 大部分都在 1280x720 分辨率, HEVC 编码。
  • 音频:纯音频文件. 均为 M4A 格式,不同的 kbps。
  • OCR 结果 (无任何后处理):对所有视频每隔1秒取一帧,使用 Paddle-OCR 对每一帧执行 OCR,获取画面上的任何可识别文字。
  • 多模态大模型解析结果:对所有 OCR 结果 + 图像信息,调用多模态大模型将其解析成结构化剧情数据,包含旁白、说话人、说话内容等信息。

时间截止:2024.08.08

最新视频:[P186]主线第二部03间章:一个梦游者的苦痛-02[720P 高清]

Illustration for text corpus construction pipeline

Here we show how text information is parsed from raw videos.

  1. Extracting Video Frames

Save each frame as a image.

frame_130.jpg

  1. OCR on video frame

Apply an OCR model to recognize texts that appear in a frame.

[{"box": [[1161.0, 17.0], [1250.0, 20.0], [1249.0, 49.0], [1160.0, 46.0]], "text": "跳过I", "score": 0.8165686130523682}, {"box": [[539.0, 154.0], [724.0, 136.0], [726.0, 158.0], [542.0, 177.0]], "text": "SOURCEUNKNOWN", "score": 0.9888437986373901}, {"box": [[541.0, 475.0], [645.0, 475.0], [645.0, 499.0], [541.0, 499.0]], "text": "不明通讯", "score": 0.9979484677314758}, {"box": [[807.0, 476.0], [976.0, 481.0], [976.0, 508.0], [806.0, 504.0]], "text": "无量塔姬子", "score": 0.9982650876045227}, {"box": [[544.0, 509.0], [1107.0, 534.0], [1106.0, 567.0], [542.0, 542.0]], "text": "防御系统已经解除,我们暂时安全了。但还是", "score": 0.9949256777763367}, {"box": [[548.0, 545.0], [786.0, 558.0], [784.0, 585.0], [546.0, 573.0]], "text": "不知道琪亚娜在哪里。", "score": 0.9898449182510376}]
  1. Vision-Language Understanding

Prompt a performant VLM to understand the frame image as well as OCR result (prevent hallucinations), and output structured information as follows:

{
    "role": "无量塔姬子",
    "content": "防御系统已经解除,我们暂时安全了。但还是不知道琪亚娜在哪里。"
}
Downloads last month
102