image_captioning_mapper

Generates image captions using a Hugging Face model and appends them to samples.

This operator generates captions for images in the input samples using a specified Hugging Face model. It can generate multiple captions per image and apply different strategies to retain the generated captions. The operator supports three retention modes: 'random_any', 'similar_one_simhash', and 'all'. In 'random_any' mode, a random caption is retained. In 'similar_one_simhash' mode, the most similar caption to the original text (based on SimHash) is retained. In 'all' mode, all generated captions are concatenated and retained. The operator can also keep or discard the original sample based on the keep_original_sample parameter. If both prompt and prompt_key are set, the prompt_key takes precedence.

使用 Hugging Face 模型生成图像描述并将其附加到样本中。

该算子使用指定的 Hugging Face 模型为输入样本中的图像生成描述。它可以为每张图像生成多个描述，并应用不同的策略来保留生成的描述。该算子支持三种保留模式：'random_any'、'similar_one_simhash' 和 'all'。在 'random_any' 模式下，随机保留一个描述。在 'similar_one_simhash' 模式下，保留与原始文本最相似的描述（基于 SimHash）。在 'all' 模式下，所有生成的描述被连接并保留。该算子还可以根据 keep_original_sample 参数保留或丢弃原始样本。如果同时设置了 prompt 和 prompt_key，则 prompt_key 优先。

Type 算子类型: mapper

Tags 标签: cpu, hf, multimodal

🔧 Parameter Configuration 参数配置

name 参数名

type 类型

default 默认值

desc 说明

hf_img2seq

<class 'str'>

'Salesforce/blip2-opt-2.7b'

model name on huggingface to generate caption

trust_remote_code

<class 'bool'>

False

caption_num

typing.Annotated[int, Gt(gt=0)]

1

how many candidate captions to generate

keep_candidate_mode

<class 'str'>

'random_any'

retain strategy for the generated

keep_original_sample

<class 'bool'>

True

whether to keep the original sample. If

prompt

typing.Optional[str]

None

a string prompt to guide the generation of blip2 model

prompt_key

typing.Optional[str]

None

the key name of fields in samples to store prompts

args

''

extra args

kwargs

''

extra args

📊 Effect demonstration 效果演示

not available 暂无