Image-Text Retrieval Embdding with BLIP

author: David Wang

Description

This operator extracts features for image or text with BLIP which can generate embeddings for text and image by jointly training an image encoder and text encoder to maximize the cosine similarity. This is a adaptation from salesforce/BLIP.

Code Example

Load an image from path './teddy.jpg' to generate an image embedding.

Read the text 'A teddybear on a skateboard in Times Square.' to generate an text embedding.

Write a pipeline with explicit inputs/outputs name specifications:

from towhee.dc2 import pipe, ops, DataCollection

img_pipe = (
    pipe.input('url')
    .map('url', 'img', ops.image_decode.cv2_rgb())
    .map('img', 'vec', ops.image_text_embedding.blip(model_name='blip_itm_base_coco', modality='image'))
    .output('img', 'vec')
)

text_pipe = (
    pipe.input('text')
    .map('text', 'vec', ops.image_text_embedding.blip(model_name='blip_itm_base_coco', modality='text'))
    .output('text', 'vec')
)

DataCollection(img_pipe('./teddy.jpg')).show()
DataCollection(text_pipe('A teddybear on a skateboard in Times Square.')).show()

Factory Constructor

Create the operator via the following factory method

blip(model_name, modality)

Parameters:

​ model_name: str

​ The model name of BLIP. Supported model names:

• blip_itm_base_coco
• blip_itm_large_coco
• blip_itm_base_flickr
• blip_itm_large_flickr

​ modality: str

​ Which modality(image or text) is used to generate the embedding.

Interface

An image-text embedding operator takes a towhee image or string as input and generate an embedding in ndarray.

save_model(format='pytorch', path='default')

Save model to local with specified format.

Parameters:

format: str

​ The format of saved model, defaults to 'pytorch'.

path: str

​ The path where model is saved to. By default, it will save model to the operator directory.

from towhee import ops

op = ops.image_text_embedding.blip(model_name='blip_itm_base_coco', modality='image').get_op()
op.save_model('onnx', 'test.onnx')

Parameters:

​ data: towhee.types.Image (a sub-class of numpy.ndarray) or str

​ The data (image or text based on specified modality) to generate embedding.

Parameters:

​ data: towhee.types.Image (a sub-class of numpy.ndarray) or str

​ The data (image or text based on specified modality) to generate embedding.

Returns: numpy.ndarray

​ The data embedding extracted by model.