Image Captioning Alternatives

Image Captioning is the process of generating textual description of an image.It uses both Natural language Processing and Computer Vision to generate the captions.
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Alternatives To Thejesh-M/Image-Captioning
Project Name Stars Downloads Repos Using This Packages Using This Most Recent Commit Total Releases Latest Release Open Issues License Language
d2l-ai/d2l-zh 53,401 1 1 about 2 years ago 51 August 18, 2023 65 apache-2.0 Python
《动手学深度学习》:面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
microsoft/AI-For-Beginners 26,668 0 0 about 2 years ago 0 64 mit Jupyter Notebook
12 Weeks, 24 Lessons, AI for All!
eugeneyan/applied-ml 24,828 0 0 over 2 years ago 0 3 mit
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
d2l-ai/d2l-en 20,613 0 0 about 2 years ago 2 November 13, 2022 115 other Python
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
huggingface/datasets 17,925 9 760 about 2 years ago 76 November 16, 2023 665 apache-2.0 Python
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
bharathgs/Awesome-pytorch-list 14,715 0 0 about 2 years ago 0 4
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code 14,248 0 0 over 2 years ago 0 22
500 AI Machine learning Deep learning Computer vision NLP Projects with code
ShusenTang/Dive-into-DL-PyTorch 13,747 0 0 over 4 years ago 0 76 apache-2.0 Jupyter Notebook
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
virgili0/Virgilio 13,515 0 0 over 3 years ago 0 20 other Jupyter Notebook
Your new Mentor for Data Science E-Learning.
NVIDIA/DeepLearningExamples 12,073 0 0 about 2 years ago 0 295 Jupyter Notebook
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
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