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1.8 KiB
Image Captioning with CapDec
author: David Wang
Description
This operator generates the caption with CapDec which describes the content of the given image. ExpansionNet v2 introduces the Block Static Expansion which distributes and processes the input over a heterogeneous and arbitrarily big collection of sequences characterized by a different length compared to the input one. This is an adaptation from DavidHuji/CapDec.
Code Example
Load an image from path './image.jpg' to generate the caption.
Write the pipeline in simplified style:
import towhee
towhee.glob('./image.jpg') \
.image_decode() \
.image_captioning.capdec(model_name='capdec_noise_0') \
.show()

Write a same pipeline with explicit inputs/outputs name specifications:
import towhee
towhee.glob['path']('./image.jpg') \
.image_decode['path', 'img']() \
.image_captioning.capdec['img', 'text'](model_name='capdec_noise_0') \
.select['img', 'text']() \
.show()

Factory Constructor
Create the operator via the following factory method
capdec(model_name)
Parameters:
model_name: str
The model name of CapDec. Supported model names:
- capdec_noise_0
- capdec_noise_01
- capdec_noise_001
- capdec_noise_0001
Interface
An image captioning operator takes a towhee image as input and generate the correspoing caption.
Parameters:
data: towhee.types.Image (a sub-class of numpy.ndarray)
The image to generate caption.
Returns: str
The caption generated by model.
1.8 KiB
Image Captioning with CapDec
author: David Wang
Description
This operator generates the caption with CapDec which describes the content of the given image. ExpansionNet v2 introduces the Block Static Expansion which distributes and processes the input over a heterogeneous and arbitrarily big collection of sequences characterized by a different length compared to the input one. This is an adaptation from DavidHuji/CapDec.
Code Example
Load an image from path './image.jpg' to generate the caption.
Write the pipeline in simplified style:
import towhee
towhee.glob('./image.jpg') \
.image_decode() \
.image_captioning.capdec(model_name='capdec_noise_0') \
.show()

Write a same pipeline with explicit inputs/outputs name specifications:
import towhee
towhee.glob['path']('./image.jpg') \
.image_decode['path', 'img']() \
.image_captioning.capdec['img', 'text'](model_name='capdec_noise_0') \
.select['img', 'text']() \
.show()

Factory Constructor
Create the operator via the following factory method
capdec(model_name)
Parameters:
model_name: str
The model name of CapDec. Supported model names:
- capdec_noise_0
- capdec_noise_01
- capdec_noise_001
- capdec_noise_0001
Interface
An image captioning operator takes a towhee image as input and generate the correspoing caption.
Parameters:
data: towhee.types.Image (a sub-class of numpy.ndarray)
The image to generate caption.
Returns: str
The caption generated by model.