video_captioning_from_frames_mapper¶
Generates video captions from sampled frames using an image-to-text model. Captions from different frames are concatenated into a single string.
Uses a Hugging Face image-to-text model to generate captions for sampled video frames.
Supports different frame sampling methods: ‘all_keyframes’ or ‘uniform’.
Can apply horizontal and vertical flips to the frames before captioning.
Offers multiple strategies for retaining generated captions: ‘random_any’, ‘similar_one_simhash’, or ‘all’.
Optionally keeps the original sample in the final dataset.
Allows setting a global prompt or per-sample prompts to guide caption generation.
Generates a specified number of candidate captions per video, which can be reduced based on the selected retention strategy.
The number of output samples depends on the retention strategy and whether original samples are kept.
使用图像到文本模型从采样的帧中生成视频字幕。来自不同帧的字幕被连接成一个字符串。
使用Hugging Face图像到文本模型为采样的视频帧生成字幕。
支持不同的帧采样方法：’all_keyframes’或’uniform’。
可以在字幕前对帧进行水平和垂直翻转。
提供多种保留生成字幕的策略：’random_any’、’similar_one_simhash’或’all’。
可选地在最终数据集中保留原始样本。
允许设置全局提示或每个样本的提示来指导字幕生成。
为每个视频生成指定数量的候选字幕，可以根据选定的保留策略进行减少。
输出样本的数量取决于保留策略以及是否保留原始样本。
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’> |
|
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 image-to-text 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