
BLIP
Overview
The BLIP model was proposed in BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation by Junnan Li, Dongxu Li, Caiming Xiong, Steven Hoi.
BLIP is a model that is able to perform various multi-modal tasks including:
- Visual Question Answering 
- Image-Text retrieval (Image-text matching)
- Image Captioning
The abstract from the paper is the following:
Vision-Language Pre-training (VLP) has advanced the performance for many vision-language tasks. 
However, most existing pre-trained models only excel in either understanding-based tasks or generation-based tasks. Furthermore, performance improvement has been largely achieved by scaling up the dataset with noisy image-text pairs collected from the web, which is a suboptimal source of supervision. In this paper, we propose BLIP, a new VLP framework which transfers flexibly to both vision-language understanding and generation tasks. BLIP effectively utilizes the noisy web data by bootstrapping the captions, where a captioner generates synthetic captions and a filter removes the noisy ones. We achieve state-of-the-art results on a wide range of vision-language tasks, such as image-text retrieval (+2.7% in average recall@1), image captioning (+2.8% in CIDEr), and VQA (+1.6% in VQA score). BLIP also demonstrates strong generalization ability when directly transferred to videolanguage tasks in a zero-shot manner. Code, models, and datasets are released.

This model was contributed by ybelkada.
The original code can be found here.
Resources

Jupyter notebook on how to fine-tune BLIP for image captioning on a custom dataset

BlipConfig
[[autodoc]] BlipConfig
    - from_text_vision_configs
BlipTextConfig
[[autodoc]] BlipTextConfig
BlipVisionConfig
[[autodoc]] BlipVisionConfig
BlipProcessor
[[autodoc]] BlipProcessor
BlipImageProcessor
[[autodoc]] BlipImageProcessor
    - preprocess

BlipModel
[[autodoc]] BlipModel
    - forward
    - get_text_features
    - get_image_features
BlipTextModel
[[autodoc]] BlipTextModel
    - forward
BlipVisionModel
[[autodoc]] BlipVisionModel
    - forward
BlipForConditionalGeneration
[[autodoc]] BlipForConditionalGeneration
    - forward
BlipForImageTextRetrieval
[[autodoc]] BlipForImageTextRetrieval
    - forward
BlipForQuestionAnswering
[[autodoc]] BlipForQuestionAnswering
    - forward

TFBlipModel
[[autodoc]] TFBlipModel
    - call
    - get_text_features
    - get_image_features
TFBlipTextModel
[[autodoc]] TFBlipTextModel
    - call
TFBlipVisionModel
[[autodoc]] TFBlipVisionModel
    - call
TFBlipForConditionalGeneration
[[autodoc]] TFBlipForConditionalGeneration
    - call
TFBlipForImageTextRetrieval
[[autodoc]] TFBlipForImageTextRetrieval
    - call
TFBlipForQuestionAnswering
[[autodoc]] TFBlipForQuestionAnswering
    - call

