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Image Captioning with BLIP
author: David Wang
Description
This operator generates the caption with BLIP which describes the content of the given image. This is an adaptation from salesforce/BLIP.
Code Example
Load an image from path './animals.jpg' to generate the caption.
Write the pipeline in simplified style:
import towhee
towhee.glob('./animals.jpg') \
.image_decode() \
.image_captioning.blip(model_name='blip_base') \
.show()
Write a same pipeline with explicit inputs/outputs name specifications:
import towhee
towhee.glob['path']('./animals.jpg') \
.image_decode['path', 'img']() \
.image_captioning.blip['img', 'text'](model_name='blip_base') \
.select['img', 'text']() \
.show()
Factory Constructor
Create the operator via the following factory method
blip(model_name)
Parameters:
model_name: str
The model name of BLIP. Supported model names:
- blip_base
Interface
An image captioning operator takes a towhee image as input and generate the correspoing caption.
Parameters:
img: towhee.types.Image (a sub-class of numpy.ndarray)
The image to generate caption.
Returns: str
The caption generated by model.
1.5 KiB
Image Captioning with BLIP
author: David Wang
Description
This operator generates the caption with BLIP which describes the content of the given image. This is an adaptation from salesforce/BLIP.
Code Example
Load an image from path './animals.jpg' to generate the caption.
Write the pipeline in simplified style:
import towhee
towhee.glob('./animals.jpg') \
.image_decode() \
.image_captioning.blip(model_name='blip_base') \
.show()
Write a same pipeline with explicit inputs/outputs name specifications:
import towhee
towhee.glob['path']('./animals.jpg') \
.image_decode['path', 'img']() \
.image_captioning.blip['img', 'text'](model_name='blip_base') \
.select['img', 'text']() \
.show()
Factory Constructor
Create the operator via the following factory method
blip(model_name)
Parameters:
model_name: str
The model name of BLIP. Supported model names:
- blip_base
Interface
An image captioning operator takes a towhee image as input and generate the correspoing caption.
Parameters:
img: towhee.types.Image (a sub-class of numpy.ndarray)
The image to generate caption.
Returns: str
The caption generated by model.