### Project Overview A comprehensive web application designed to showcase and manage ATV tour experiences on Mount Bistra in Galičnik. The platform provides visitors with an intuitive interface to explore available tours while offering administrators robust management capabilities. ### Key Features #### Client-Facing Functionality - **Tour Catalog**: Browse comprehensive tour listings with detailed information - **Advanced Sorting**: Filter tours by price and duration for easy comparison - **Rich Media Gallery**: View high-quality images and visual content for each tour - **Detailed Tour Information**: Access comprehensive descriptions and specifications #### Administrative Dashboard - **Reservation Management**: Handle tour bookings through an integrated admin panel - **Calendar Integration**: Full Calendar implementation for tracking and managing reserved tours - **Tour Management**: Complete CRUD operations for tour listings - **Media Management**: Upload and manage thumbnail images and photo galleries for each tour ### Technical Specifications #### Backend Technologies - **.NET 6**: Modern web application framework - **PostgreSQL**: Robust relational database management #### Frontend Technologies - **JavaScript & jQuery**: Dynamic user interactions - **HTML5**: Modern semantic markup - **CSS3**: Advanced styling and responsive design - **Bootstrap**: Mobile-first responsive framework #### Infrastructure - **Hosting**: Windows Server environment - **Web Server**: Internet Information Services (IIS) ### Project Status Initial version with core functionality implemented, featuring admin-side reservation capabilities and comprehensive tour management system. **Website:** [rupicapra.mk](http://rupicapra.mk)

### Project Overview A comprehensive corporate web platform for Avto Guma AD, a leading rubber manufacturing company established in 1947. The application serves as both a product showcase and business management system for premium rubber solutions, featuring multi-language support, advanced content management, and sophisticated product categorization for industrial rubber products. ### Key Features #### Product Management System - **Multi-Category Architecture**: Comprehensive product categorization including: - Rubber Hoses and Profiles - Rubber-Metal Products - Compounds and Materials - Industrial Rubber Solutions - **Advanced Product Catalog**: Detailed product specifications with custom parameters - **Technical Documentation**: Rich content management with HTML editing capabilities - **Visual Product Gallery**: High-quality product imagery and technical drawings #### Multi-Language & Localization - **Comprehensive Localization**: Full internationalization support with resource files - **Language Management**: Administrative interface for translation management - **Cultural Adaptation**: Region-specific content and formatting - **Dynamic Language Switching**: Seamless language selection for users #### Content Management System - **Rich Text Editing**: TinyMCE integration for advanced content creation - **Category Sections**: Modular content sections for detailed product information - **Custom Parameters**: Industry-specific product characteristics including: - Chemical resistance - Temperature resistance - Elasticity and hardness metrics - Oil and grease resistance - Wear and tear specifications #### Administrative Dashboard - **User Management**: Role-based access control and user administration - **Product Administration**: Complete CRUD operations for products and categories - **Content Management**: Section-based content editing and management - **Localization Admin**: Translation and resource management interface #### Communication & Contact - **Contact Forms**: Integrated inquiry and communication system - **Email Integration**: Automated email notifications and responses - **Business Information**: Company history, manufacturing processes, and services ### Technical Architecture #### Backend Technologies - **.NET Core MVC**: Modern web application framework - **Entity Framework Core**: Advanced ORM with comprehensive migration system - **Multi-Language Support**: Resource-based localization system - **Email Services**: SMTP integration for business communications #### Frontend Technologies - **Bootstrap**: Responsive CSS framework for professional design - **Font Awesome & Iconoir**: Comprehensive icon libraries - **jQuery**: Enhanced user interactions and AJAX functionality - **AOS (Animate On Scroll)**: Smooth scrolling animations - **Select2**: Advanced dropdown and selection components - **TinyMCE**: Professional rich text editor #### Infrastructure & Hosting - **Windows Server**: Enterprise hosting environment - **IIS (Internet Information Services)**: Professional web server hosting - **File Management**: Organized asset storage for products and categories - **SSL Security**: Secure HTTPS communication ### Specialized Features #### Industrial Focus - **Technical Specifications**: Detailed product parameters for industrial applications - **Manufacturing Process**: Visual representation of rubber production workflow - **Quality Standards**: Emphasis on premium quality and customer satisfaction - **Laboratory Services**: Research and development capabilities showcase #### Modern Web Standards - **Responsive Design**: Optimized for all device types and screen sizes - **Performance Optimization**: Fast loading times and efficient resource management - **SEO Optimization**: Search engine friendly structure and content - **Accessibility**: User-friendly interface design and navigation **Website:** [avtoguma.com.mk](https://www.avtoguma.com.mk/) **Framework:** .NET Core MVC | **Hosting:** Windows Server (IIS)

**Framework:** Python with YOLOv4 | **Dataset:** MS COCO + Custom Mask Detection ### Project Overview A comprehensive object detection software built with deep learning techniques, utilizing the YOLOv4 (You Only Look Once - version 4) algorithm for real-time object recognition. The system features dual detection capabilities: general object detection for 80 different object classes and a specialized custom detector for mask-wearing classification. ### Key Features #### Multi-Object Detection - **80 Object Classes**: Complete MS COCO dataset object recognition - **Custom Mask Detection**: Specialized person mask-wearing classification - **Real-Time Processing**: Fast inference suitable for live applications - **High Accuracy**: YOLOv4's state-of-the-art detection performance #### Versatile Input Sources - **Image Processing**: Single image analysis and batch processing - **Video Analysis**: Frame-by-frame object detection in video files - **Webcam Integration**: Real-time detection from live camera feed - **Flexible Output**: Annotated results with bounding boxes and confidence scores #### Specialized Applications - **General Object Detection**: Comprehensive everyday object recognition - **Mask Compliance Monitoring**: COVID-19 safety protocol enforcement - **Multi-Purpose Usage**: Adaptable for various computer vision applications ### Technical Specifications #### Core Algorithm - **YOLOv4 Architecture**: Advanced single-shot detection network - **MS COCO Dataset**: Pre-trained on 80 object categories including: - Vehicles (car, truck, bus, motorcycle, bicycle) - Animals (dog, cat, horse, bird, etc.) - Household items (chair, table, TV, laptop, etc.) - Sports equipment (ball, racket, skis, etc.) #### Custom Detection Model - **Mask Detection**: Binary classification for face mask compliance - **Person Detection**: Human subject identification and tracking - **Safety Applications**: Public health monitoring capabilities #### Implementation Details - **Programming Language**: Python - **Deep Learning Framework**: Darknet/PyTorch implementation - **Computer Vision**: OpenCV for image processing - **Performance Optimization**: GPU acceleration support #### Cross-Platform Conversion Pipeline ##### TensorFlow Lite Optimization - **Model Quantization**: Reduced precision for mobile deployment - **Size Optimization**: Compressed models for resource-constrained devices - **Android Integration**: Native Android app compatibility - **Hardware Acceleration**: GPU and NPU support ##### Core ML Integration - **iOS Optimization**: Apple Neural Engine acceleration - **Swift Compatibility**: Native iOS development support - **On-Device Processing**: Privacy-focused local inference - **Performance Tuning**: iOS-specific optimizations ### System Capabilities #### Input Processing - **Image Formats**: JPEG, PNG, BMP, and other standard formats - **Video Formats**: MP4, AVI, MOV, and common video containers - **Live Stream**: Real-time webcam processing - **Batch Processing**: Multiple file handling capabilities #### Detection Performance - **Object Recognition**: 80 different object classes from MS COCO - **Mask Classification**: Binary detection (mask/no mask) - **Confidence Scoring**: Probability metrics for each detection - **Bounding Box Annotation**: Precise object localization

**Framework:** .NET 8 MVC | **Database:** PostgreSQL | **Hosting:** IIS ### Project Overview A sophisticated, enterprise-level e-commerce platform featuring comprehensive business management capabilities, advanced analytics, multi-language support, and real-time notifications. The application demonstrates modern software architecture with extensive logging, audit trails, and administrative controls. ### Core Features #### Advanced Product Management - **Hierarchical Categories**: Multi-level category and subcategory system - **Brand Management**: Comprehensive brand catalog and filtering - **Product Variants**: Multiple measurement types and specifications - **Inventory Tracking**: Real-time stock management - **Excel Integration**: Bulk product import/export capabilities #### Customer Experience - **Wishlist System**: Save and manage favorite products - **Shopping Cart**: Advanced cart management with session persistence - **Product Reviews**: Customer feedback and rating system - **Quick View**: Product preview without page navigation - **Related Products**: Intelligent product recommendations #### Order Management & Processing - **Multi-Status Workflow**: Comprehensive order status tracking - **Payment Integration**: Multiple payment type support - **Transport Options**: Various shipping and delivery methods - **Order Analytics**: Detailed order reporting and insights - **Customer Order History**: Complete purchase tracking #### Discount & Promotion System - **Flexible Discounts**: Multiple discount types and configurations - **Promotional Campaigns**: Time-based and usage-limited promotions - **Coupon Management**: Advanced coupon creation and tracking - **Discount Analytics**: Performance monitoring and reporting #### Real-Time Communication - **SignalR Integration**: Live notifications and updates - **Notification System**: Multi-type notification management - **User Alerts**: Real-time status updates and messaging - **Admin Notifications**: System alerts and monitoring #### Internationalization & Localization - **Multi-Language Support**: Complete localization system - **Cultural Adaptation**: Region-specific formatting and content - **Translation Management**: Admin interface for content translation - **Language Switching**: Dynamic language selection #### Advanced Analytics & Logging - **Activity Logging**: Comprehensive user action tracking - **Audit Trail**: Complete system change history - **Application Logs**: Technical monitoring and debugging - **Performance Metrics**: System performance tracking - **Business Intelligence**: Sales and customer analytics ### Technical Architecture #### Backend Technologies - **.NET 8 MVC**: Latest .NET framework with modern C# features - **PostgreSQL**: Enterprise-grade relational database - **Entity Framework Core**: Advanced ORM with migration support - **SignalR**: Real-time web functionality - **Repository Pattern**: Clean data access architecture #### Frontend Technologies - **Bootstrap**: Responsive CSS framework - **Font Awesome**: Comprehensive icon library - **Material Design Icons**: Modern icon system - **jQuery**: Client-side scripting and AJAX - **JavaScript**: Modern ES6+ features #### Infrastructure & Deployment - **IIS Hosting**: Windows Server deployment - **PostgreSQL Database**: High-performance data storage - **File Management**: Organized media and asset storage - **Security**: Authentication and authorization systems

The **IFC Viewer** is a comprehensive web-based Building Information Modeling (BIM) application designed for viewing, analyzing, and managing IFC (Industry Foundation Classes) files. It's built using **Python Flask** for the backend and **JavaScript with Three.js** for the 3D visualization frontend, utilizing **Bootstrap 5.3** for the UI framework. ### Core Architecture #### Backend (Python Flask) - Core modules for database management, IFC parsing, geometry processing, and analysis - RESTful API endpoints for model management and data processing - Background task management system for long-running operations - SQLite database for persistent storage #### Frontend (JavaScript/Three.js) - Interactive 3D viewer with Three.js for model visualization - Bootstrap 5.3 responsive UI components - jQuery for DOM manipulation and AJAX requests - Real-time property inspection and element filtering ### Key Functionalities #### 3D Model Visualization ##### Interactive 3D Viewer - Full 3D navigation with OrbitControls - Multiple View Modes: Front, Top, Right, Isometric views - Progressive Loading: Optimized loading for large models with batch processing - Element Interaction: Click-to-select elements with property inspection ##### Visual Controls - Wireframe toggle - Section view with cutting planes - Element highlighting and selection - Screenshot capture functionality #### File Management ##### Upload System - IFC File Upload: Drag-and-drop or browse file upload - File Browser: Navigate and select files from server storage - Background Processing: Asynchronous file processing with progress tracking ##### Model Library - View and manage all uploaded IFC models - Model information display with project details - Quick access to 3D viewer for each model #### Element Analysis & Filtering ##### Advanced Filtering System - Filter by element type, properties, and custom conditions - Multiple filter criteria with AND/OR logic - Real-time filter application with visual feedback - Property-based filtering with autocomplete ##### Element Organization - Element Tree View: Hierarchical display by type and storey - Batch Element Editor: Bulk operations on filtered elements - Property Search: Search and filter elements by property values #### Rule Builder System ##### Visual Rule Builder - Create complex business rules without coding - Property-Based Conditions: Build rules using IFC properties and values - Rule Validation: Test rules against model data ##### Rule Management - Attribute Assignment: Bulk assign attributes based on rule conditions - Rule Import/Export: Save and share rule configurations - Template System: Pre-built rule templates #### Quantity Takeoff ##### Automated Calculations - Calculate areas, volumes, lengths, and counts - Material Quantification: Extract material quantities from IFC properties - Custom Quantity Rules: Define custom calculation methods ##### Export & Reporting - Export quantity data to various formats - Cost Estimation: Basic cost calculation features - Detailed quantity reports with breakdowns #### Analysis Tools ##### Building Analysis - Energy Analysis: Building performance analysis capabilities - Clash Detection: Identify geometric conflicts between elements - Area Calculations: Automated space and surface area calculations ##### Reporting - Report Generation: Comprehensive analysis reports with charts and graphs - Statistics Dashboard: Model statistics and element counts - Visual analytics with Chart.js integration #### Advanced Features ##### Measurement Tools - Interactive 3D measuring functionality - Distance, area, and volume measurements - Measurement point visualization - Real-time measurement display ##### Schema Integration - IFC Schema Integration: Full IFC schema support with property definitions - Element property exploration - Hierarchical property set navigation ##### User Experience - Element Tooltips: Hover tooltips showing element information - Dark/Light Theme: User preference theme switching - Responsive Design: Mobile and tablet compatible interface #### Data Management ##### Property Inspection - Detailed view of element properties and property sets - Element Hierarchy: Navigate IFC building hierarchy - Property search with autocomplete suggestions ##### Export Capabilities - Search Functionality: Global search across elements and properties - Data Export: Export filtered elements and analysis results - JSON/CSV export formats #### Background Processing ##### Task Management - Task Queue System: Handle long-running operations asynchronously - Progress Tracking: Real-time progress updates for file processing - Error Handling: Comprehensive error reporting and recovery ##### Performance - Memory management with proper disposal of 3D objects - Efficient database queries with indexing - Caching mechanisms for improved performance #### API Integration ##### RESTful API - Complete API for programmatic access - Model upload and processing endpoints - Element filtering and property access ##### Real-time Features - Real-time Updates: WebSocket-like updates for long-running operations - Extensible Architecture: Plugin-ready architecture for custom modules ### Technical Highlights #### Performance Optimizations - Progressive model loading for large files - Efficient 3D geometry processing with DRACO compression support - Memory management with proper disposal of 3D objects - Optimized database queries with indexing #### Code Quality - Modular architecture with clear separation of concerns - Comprehensive error handling and logging - Clean, maintainable code structure - Responsive and accessible UI design #### Scalability - Background task processing for heavy operations - Efficient memory usage for large IFC models - Database optimization for fast queries - Caching mechanisms for improved performance ### Application Use Cases #### For Architects - Visual model review and validation - Design analysis and measurements - Element property inspection - Quality control and clash detection #### For Engineers - Structural analysis and calculations - Quantity takeoffs for cost estimation - Technical property verification - Performance analysis #### For Construction Professionals - Material quantity extraction - Cost estimation and budgeting - Progress tracking and validation - Quality assurance workflows ### Conclusion This application represents a professional-grade BIM tool suitable for architects, engineers, and construction professionals who need to analyze and visualize IFC building models with advanced filtering, measurement, and analysis capabilities. The combination of Three.js visualization, comprehensive IFC support, and advanced analysis tools makes it a powerful platform for building information management.

**Framework:** .NET Core 3.1 | **Database:** MS SQL Server | **Hosting:** Windows Server (IIS) ### Project Overview A specialized e-commerce web application designed for selling premium meat products online. The platform prioritizes user convenience with guest checkout capabilities while providing comprehensive administrative tools for order management and inventory control. Built with modern web technologies to deliver a seamless shopping experience for high-quality meat products. ### Key Features #### Customer Experience - **Guest Checkout**: Streamlined ordering process without required registration - **Product Catalog**: Comprehensive premium meat product listings - **Package Options**: Multiple product packaging and sizing choices - **Intuitive Shopping**: User-friendly interface optimized for meat product selection - **Order Placement**: Simple and efficient checkout process #### Administrative Management - **Secure Admin Access**: Authentication-protected administrative dashboard - **Order Management**: Complete order tracking and processing capabilities - **Product Administration**: Full CRUD operations for meat products - **Package Management**: Control over product packaging options and configurations - **Inventory Control**: Real-time stock management and updates #### Product Management - **Premium Meat Catalog**: Specialized product categories for various meat types - **Package Configurations**: Flexible packaging options (weight, size, quantity) - **Product Information**: Detailed descriptions, pricing, and specifications - **Image Management**: High-quality product photography and galleries ### Technical Architecture #### Backend Technologies - **.NET Core 3.1**: Modern cross-platform web application framework - **MS SQL Server**: Enterprise-grade relational database management - **MVC Pattern**: Model-View-Controller architectural design - **Entity Framework**: Object-relational mapping for data access #### Frontend Technologies - **HTML5**: Modern semantic markup and structure - **CSS3**: Advanced styling and responsive layouts - **JavaScript**: Dynamic user interactions and client-side functionality - **jQuery**: Enhanced DOM manipulation and AJAX requests - **Bootstrap**: Responsive CSS framework for mobile-first design #### Infrastructure & Deployment - **Windows Server**: Enterprise hosting environment - **Internet Information Services (IIS)**: Web server and application hosting - **Database Integration**: MS SQL Server connectivity and optimization - **Security**: Admin authentication and authorization systems ### Business Logic #### Order Workflow 1. **Product Selection**: Browse and select premium meat products 2. **Package Choice**: Select preferred packaging options 3. **Order Details**: Provide delivery and contact information 4. **Order Confirmation**: Complete purchase without registration 5. **Admin Processing**: Administrative review and fulfillment #### Security Features - **Admin Authentication**: Secure administrative access control - **Data Protection**: Customer information security - **Input Validation**: Comprehensive form validation and sanitization - **SQL Injection Prevention**: Parameterized queries and security measures

**Backend:** Java Spring Boot | **ML API:** Python REST API | **Models:** CNN + Vision Transformer ### Project Overview An intelligent web application that leverages advanced computer vision and machine learning to identify dog breeds from uploaded images. The system features two distinct TensorFlow implementations: a traditional Convolutional Neural Network with dense layers and an advanced Vision Transformer architecture, with cross-platform deployment capabilities for edge devices. ### Key Features #### Advanced Model Architecture - **CNN Implementation**: Traditional convolutional neural network with dense classification layers - **Vision Transformer**: Modern attention-based architecture for improved accuracy - **Dual Model Support**: Choice between traditional and state-of-the-art approaches - **Performance Comparison**: Benchmarking between different architectures #### Cross-Platform Deployment - **TensorFlow Lite**: Optimized models for Android devices - **Core ML**: Native iOS integration for on-device inference - **Edge Computing**: Local processing capabilities for mobile applications - **Multi-Platform Support**: Seamless deployment across different platforms #### User Experience - **Multi-Source Upload**: Support for images from computer and mobile devices - **Intelligent Preprocessing**: Automatic image resizing and optimization - **Instant Results**: Quick breed prediction display - **Clear Output Format**: "The breed of the previous uploaded dog it's most likely to be: {breed}" ### Technical Architecture #### Backend Services - **Java Spring Boot**: Main web application framework - RESTful web services - File upload handling - Request/response management - Model selection logic - **Python REST API**: Machine learning service - TensorFlow model integration - Image preprocessing pipeline - Breed prediction algorithms - JSON response formatting #### Machine Learning Models ##### CNN Implementation (Version 1) - **Architecture**: Convolutional Neural Network with dense layers - **Feature Extraction**: Multi-layer convolution and pooling - **Classification**: Dense neural network for breed prediction - **Training**: Traditional supervised learning approach ##### Vision Transformer (Version 2) - **Architecture**: Transformer-based computer vision model - **Attention Mechanism**: Self-attention for image patch analysis - **Modern Approach**: State-of-the-art vision processing - **Enhanced Accuracy**: Improved breed classification performance ### Technical Specifications #### Core Technologies - **Backend Framework**: Java Spring Boot - **ML Framework**: TensorFlow 2.x with Python - **Computer Vision**: TensorFlow Image APIs and OpenCV - **API Architecture**: REST-based microservices #### Frontend Technologies - **HTML5**: Modern semantic markup and structure - **CSS3**: Advanced styling and responsive layouts - **JavaScript**: Dynamic user interactions and API communication - **Responsive Design**: Cross-device compatibility