Computer Vision & Object Detection

Upload images for real-time object detection and scene analysis using YOLOv8 and advanced CNN models.

📷

Drag & drop an image or click to upload

0.5

Natural Language Processing & Text Analysis

Comprehensive text analysis using BERT, sentiment analysis, and advanced NLP techniques.

AI Content Generation

Generate creative content using advanced language models and generative AI techniques.

Conservative 7 Creative

Multi-Modal AI Analysis

Combined image and text analysis for comprehensive understanding and cross-modal insights.

Image Input

📷

Upload image

Text Input

Project Information & Technical Specifications

Comprehensive overview of the AI models, architectures, and performance metrics used in this deep learning project.

Model Architectures

Computer Vision

  • YOLOv8: Real-time object detection
  • ResNet-50: Image classification
  • Faster R-CNN: Precise object localization
  • SSD MobileNet: Lightweight detection

Natural Language Processing

  • BERT: Bidirectional text understanding
  • GPT-3.5: Text generation and completion
  • RoBERTa: Sentiment analysis
  • T5: Text summarization

Performance Metrics

Task Accuracy Speed Model Size
Object Detection 92.3% 45 FPS 350MB
Sentiment Analysis 88.7% 1000 tok/s 120MB
Text Generation 85.4% 50 tok/s 380MB

Technical Stack

Frameworks

PyTorch TensorFlow Transformers

Libraries

OpenCV NLTK NumPy Pandas

Deployment

Docker AWS Streamlit Cloud

Future Enhancements

🚀 Model Improvements

Integration of latest transformer architectures and fine-tuning on domain-specific datasets

đŸŽ¯ Real-time Processing

GPU acceleration and model optimization for real-time inference capabilities

🔗 API Integration

RESTful API endpoints for seamless integration with other applications

📊 Advanced Analytics

Comprehensive dashboard with detailed analytics and model performance tracking