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This project was developed for the 2022 Teknofest Artificial Intelligence in Transportation Competition. It focuses on detecting vehicles and pedestrians from bird's-eye view images using deep learning. The dataset includes images from stock videos and photos, labeled in YOLO format for use in object detection models.
Turkish Teknofest SIHA Combat UAV Competition - Eflatun Team code repository for autonomous flight and mission logic.
Source code components for the Eflatun UAV team projects, focusing on mission logic.
YOLOv8 deep learning model, integrated into a Django + Django REST Framework application.
A local-first EPUB reader with high-fidelity neural text-to-speech, word-level synchronization, and Next.js/FastAPI/ONNX stack.
Comprehensive guide and documentation for Getting Started with ROS2 in Turkish.
Unified multi-provider ChatModel manager for LangChain. Supports routing, rate limits, fallbacks, and structured output across multiple LLMs.
AI Agent configuration and policy template for VS Code Copilot and Codex to standardize behavior, enforce safety, and reduce hallucinations.
Svelte-based dashboard to visualize and share your GitHub profile statistics and projects.
Video Frame Extractor is a Python script that extracts frames from videos and saves them as images with unique filenames using OpenCV. It allows you to specify the frequency of extraction and directories for videos and images. Useful for creating datasets for ML or CV projects
Open Source Impact
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