metadata
license: mit
language:
- en
tags:
- deep-learning
- computer-vision
- vision-language
- segmentation
- multimodal
- pytorch
library_name: pytorch
DEEP – Vision-Language Intelligence Framework
🔥 Overview
DEEP is a multimodal AI framework that integrates computer vision and language understanding to perform intelligent visual reasoning tasks.
The system is designed for:
- 🧠 Vision-Language Understanding
- 🖼 Image Segmentation
- 📝 Visual Question Answering
- 🔍 Prompt-driven Object Localization
- 🤖 AI Agent-based Visual Reasoning
This repository contains model weights, training scripts, and inference pipeline.
🏗 Architecture
The architecture integrates:
- Vision Encoder (CNN / ViT)
- Text Encoder (Transformer-based)
- Cross-Modal Attention Fusion
- Task-specific Heads (Segmentation / QA / Classification)
Pipeline Flow:
Image → Vision Encoder
Text Prompt → Text Encoder
Fusion → Cross Attention
Output → Task Head
📊 Training Details
- Framework: PyTorch
- Optimizer: AdamW
- Loss: Cross-Entropy / Contrastive Loss
- Training Strategy: Supervised Learning
- Hardware: GPU-based Training
🚀 Usage
Install Dependencies
pip install torch torchvision transformers