Pytorch Implementation of Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic

Last update: Jan 03, 2023

Related tags

Deep Learning zero-shot-image-to-text

Overview

Pytorch Implementation of Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic

[Paper] [Colab is coming soon]

Approach

Example

Usage

To run captioning on a single image:

$ python run.py 
--reset_context_delta
--caption_img_path "example_images/captions/COCO_val2014_000000097017.jpg"

To run model on visual arithmetic:

$ python run.py 
--reset_context_delta
--end_factor 1.06
--fusion_factor 0.95
--grad_norm_factor 0.95
--run_type arithmetics
--arithmetics_imgs "example_images/arithmetics/woman2.jpg" "example_images/arithmetics/king2.jpg" "example_images/arithmetics/man2.jpg"
--arithmetics_weights 1 1 -1

To run model on real world knowledge:

$ python run.py
--reset_context_delta --cond_text "Image of" 
--end_factor 1.04 
--caption_img_path "example_images/real_world/simpsons.jpg"

To run model on OCR:

$ python run.py
--reset_context_delta --cond_text "Image of text that says" 
--end_factor 1.04 
--caption_img_path "example_images/OCR/welcome_sign.jpg"

Owner

GitHub Repository

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Pytorch Implementation of Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic

Related tags

Overview

Pytorch Implementation of Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic

Approach

Example

Usage

To run captioning on a single image:

To run model on visual arithmetic:

To run model on real world knowledge:

To run model on OCR:

Owner

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Semantic segmentation task for ADE20k & cityscapse dataset, based on several models.

The repo contains the code of the ACL2020 paper `Dice Loss for Data-imbalanced NLP Tasks`

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