https://github.com/first-coding/multimodal-assistant
https://github.com/first-coding/multimodal-assistant
ai deep-learning faiss multimodal-deep-learning python torch
Last synced: 5 months ago
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- Host: GitHub
- URL: https://github.com/first-coding/multimodal-assistant
- Owner: first-coding
- Created: 2025-02-14T13:17:36.000Z (about 1 year ago)
- Default Branch: master
- Last Pushed: 2025-02-16T04:12:56.000Z (about 1 year ago)
- Last Synced: 2025-05-20T09:09:06.206Z (10 months ago)
- Topics: ai, deep-learning, faiss, multimodal-deep-learning, python, torch
- Language: Python
- Homepage:
- Size: 1.29 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
### Multimodal Assistant
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### Project Overview
Multimodal Assistant is an intelligent assistant based on multimodal (text and image) capabilities, integrating features such as image-text retrieval, image captioning, question answering, and sentiment analysis. This project leverages state-of-the-art pre-trained models like CLIP and BLIP to facilitate efficient interaction and understanding between images and text.
### Features
- Image-Text Matching: Given a textual description, find the most relevant image (based on the CLIP model).
- Image Captioning: Generate natural language descriptions from images using the BLIP model.
- Sentiment Analysis: Perform sentiment analysis on input text (positive, negative, neutral) using the DistilBERT model.
- Image Question Answering: Given an image and a user's question, the system generates answers related to the image.
### Key Technologies
- CLIP (Contrastive Language-Image Pretraining): Used for matching similarity between images and text.
- BLIP (Bootstrapping Image-Language Pretraining): Used for generating natural language descriptions from images and answering image-related questions.
- DistilBERT: Utilized for sentiment analysis tasks to determine the sentiment of a given text.
- FAISS (Facebook AI Similarity Search): Used for efficient image vector indexing and retrieval. FAISS enables fast similarity search, allowing the project to perform image retrieval on large-scale image datasets.
### Suggestions and Issues
I hope this project is helpful to everyone，If you have any suggestions or issues, feel free to discuss them with me through the issues section. Thank you!