Digimon Dataset for MultiModal Machine Learning
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Updated
Jun 2, 2023 - Python
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Digimon Dataset for MultiModal Machine Learning
This repository guides to develop a Multimodal FastAPI application that leverages the CLIP model for analyzing images or text. The app performs semantic search to identify and retrieve nutritional information by querying a vector database, making it a powerful tool for multimodal data processing.
Authors official PyTorch implementation of the "ContraCLIP: Interpretable GAN generation driven by pairs of contrasting sentences".
Scene Sense is an AI-powered image search engine which lets you search images using natural language queries.
A benchmark and analysis of QFormer, Cross Attention, and Concat models for binary Visual Question Answering (VQA) using CLIP and BERT+ViT-CLIP encoders.
Classic original Inception style DeepDream, but with CLIP ResNet. And CLIP ViT for comparison.
Clip highlights from your YouTube live stream instantly with just one Nightbot command.
A short audio-visual clip that runs in the browser made by rendering SVGs and animating them with CSS.
CommE5052: Deep Learning for Computer Vision (Prof. Frank Wang)
A great library that will allow you to use the Twitch API service. All you need to do is use your Token and Client Id information.
Image captioning using pytorch by finetuning GPT2 and CLIP
Generative models nano version for fun. No STOA here, nano first.
This project enhances text encoders' global descriptors by implementing advanced aggregation techniques from computer vision literature, to improve sentence-level representations. We utilize models such as BERT, RoBERTa, and CLIP, and benchmark performance using datasets like MTEB, SemEval24 and Quora Question Pairs.
CLIP Embeddings for images and text. A clojure wrapper for clip.cpp.
A multimodal RAG system powered by Gemini and ChromaDB that lets you explore cat breeds via text and image queries.
Build & Host multi-modal cloud search
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