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Introduction to Graphic Illustration
Computational Social Science Methods
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Learn to create a fall detection app using YOLOv7 pose estimation, covering UI design, push-up counting logic, and implementation on both CPU and GPU. Explore real-world applications of computer vision in healthcare.
Step-by-step guide to train and deploy YOLOv7 object detection on custom datasets using Google Colab's free GPU. Covers model evaluation and inference on images, videos, and webcam.
Comprehensive Python-based OpenCV tutorial covering fundamentals to advanced applications, including face detection, object tracking, and image classification. Ideal for aspiring computer vision professionals.
Learn to build a real-time weed detection model using YOLOR and OpenCV in Python. Extract weed coordinates and implement computer vision techniques for agricultural applications.
Learn to create a Bernie Sanders detector using YOLOv4/v5, OpenCV, and Roboflow. Build datasets, train models, and implement real-time detection on various platforms.
Build a Raspberry Pi pan-tilt tracking camera using OpenCV AI Kit. Learn hardware setup, coding, and dataset creation with Roboflow for real-time object detection and camera movement at 30 FPS.
Step-by-step guide to installing Detectron2 for computer vision projects using OpenCV and Python, covering essential requirements, software setup, and testing procedures.
Comprehensive introduction to machine learning theory, covering algorithms, neural networks, and computer vision topics through engaging whiteboard animations designed for beginners.
Build a real-time mask detection access control system using Raspberry Pi, OpenCV AI Kit, and a stepper motor. Learn hardware setup, coding, and dataset annotation with Roboflow for this practical AI application.
Learn to detect chess pieces using YOLOv5 and OpenCV in Python. Explore object detection techniques, train a custom model, and implement computer vision for chess analysis.
Build a real-time social distancing detection system using Raspberry Pi and OpenCV AI Kit. Learn to implement computer vision for monitoring and alerting, with depth capability and high performance on an embedded platform.
Build a real-time AI surveillance camera using Raspberry Pi and OpenCV AI Kit. Detect objects, people, and packages with MobileNet SSD at 30 FPS. Includes hardware setup, coding, and Roboflow integration for custom object detection.
Master React.js front-end development by building an image upload interface for crop disease identification, integrating object detection and GPT-powered chatbot functionality.
Master Flask API development by integrating LLMs, handling image processing, and implementing chatbot functionality through practical backend routes and data management techniques.
Master building a weather dashboard by integrating React with Google Maps API, implementing interactive markers, real-time weather updates, and Material-UI components for a polished user interface.
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