video_captioning_from_video_mapper¶
Generates video captions using a Hugging Face video-to-text model and sampled video frames.
This operator processes video samples to generate captions based on the provided video frames. It uses a Hugging Face video-to-text model, such as ‘kpyu/video-blip-opt-2.7b-ego4d’, to generate multiple caption candidates for each video. The number of generated captions and the strategy to keep or filter these candidates can be configured. The operator supports different frame sampling methods, including extracting all keyframes or uniformly sampling a specified number of frames. Additionally, it allows for horizontal and vertical flipping of the frames. The final output can include both the original sample and the generated captions, depending on the configuration.
使用 Hugging Face 视频转文本模型和采样的视频帧生成视频字幕。
该算子处理视频样本，基于提供的视频帧生成字幕。它使用 Hugging Face 视频转文本模型（如 ‘kpyu/video-blip-opt-2.7b-ego4d’）为每个视频生成多个字幕候选。可以配置生成的字幕数量和保留或筛选这些候选字幕的策略。该算子支持不同的帧采样方法，包括提取所有关键帧或均匀采样指定数量的帧。此外，还允许对帧进行水平和垂直翻转。最终输出可以包括原始样本和生成的字幕，具体取决于配置。
Type 算子类型: mapper
Tags 标签: gpu, hf, multimodal
🔧 Parameter Configuration 参数配置¶
name 参数名 |
type 类型 |
default 默认值 |
desc 说明 |
|---|---|---|---|
|
<class ‘str’> |
|
video-blip model name on huggingface to generate caption |
|
<class ‘bool’> |
|
whether to trust the remote code of HF models. |
|
typing.Annotated[int, Gt(gt=0)] |
|
how many candidate captions to generate for each video |
|
<class ‘str’> |
|
retain strategy for the generated $caption_num$ candidates. ‘random_any’: Retain the random one from generated captions ‘similar_one_simhash’: Retain the generated one that is most similar to the original caption ‘all’: Retain all generated captions by concatenation Note: This is a batched_OP, whose input and output type are both list. Suppose there are $N$ list of input samples, whose batch size is $b$, and denote caption_num as $M$. The number of total samples after generation is $2Nb$ when keep_original_sample is True and $Nb$ when keep_original_sample is False. For ‘random_any’ and ‘similar_one_simhash’ mode, it’s $(1+M)Nb$ for ‘all’ mode when keep_original_sample is True and $MNb$ when keep_original_sample is False. |
|
<class ‘bool’> |
|
whether to keep the original sample. If it’s set to False, there will be only generated captions in the final datasets and the original captions will be removed. It’s True in default. |
|
typing.Optional[str] |
|
a string prompt to guide the generation of video-blip model for all samples globally. It’s None in default, which means no prompt provided. |
|
typing.Optional[str] |
|
the key name of fields in samples to store prompts for each sample. It’s used for set different prompts for different samples. If it’s none, use prompt in parameter “prompt”. It’s None in default. |
|
<class ‘str’> |
|
sampling method of extracting frame videos from the videos. Should be one of [“all_keyframes”, “uniform”]. The former one extracts all key frames (the number of which depends on the duration of the video) and the latter one extract specified number of frames uniformly from the video. Default: “all_keyframes”. |
|
typing.Annotated[int, Gt(gt=0)] |
|
the number of frames to be extracted uniformly from the video. Only works when frame_sampling_method is “uniform”. If it’s 1, only the middle frame will be extracted. If it’s 2, only the first and the last frames will be extracted. If it’s larger than 2, in addition to the first and the last frames, other frames will be extracted uniformly within the video duration. |
|
<class ‘bool’> |
|
flip frame video horizontally (left to right). |
|
<class ‘bool’> |
|
flip frame video vertically (top to bottom). |
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extra args |
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extra args |
📊 Effect demonstration 效果演示¶
not available 暂无