500 AI Machine learning Deep learning Computer vision NLP Projects with code

Image Processing and Deep Learning algorithm to detect leopards from a live camera feed.

🤖 Explore 500 AI, machine learning, deep learning, computer vision, and NLP projects with complete code to enhance your skills and projects.

Screen Recorder Project with OpenCV and C++ on Ubuntu

🧠 Explore deep learning through hands-on projects, implementing neural networks like CNNs, RNNs, and Transformers using Python and TensorFlow.

Apple Tree Diseases Predication using Image Classification

基于计算机视觉（姿态估计）的运动动作识别、规范性评估与实时反馈系统 核心对比：MediaPipe+1D-CNN+GRU vs 传统DTW模板匹配 / 规则驱动方法 应用场景：大众健身、居家体能训练、青少年体测辅导 (桌面端/移动端)

Using YOLOv8s and YOLOv5s network. Model optimization: based on YOLOv8s, the original detection Head is replaced by Dynamic Head, and the FasterNet lightweight module is introduced. Finished ablation experiments.

ADAS system for Indian road scenarios using YOLOv8-Seg for road segmentation, object detection, and instance segmentation, trained on diverse real-world datasets with superpixel refinement and real-time inference capabilities.

skin disease classification using YOLOv8

VisionCraft is an intelligent photo editing application built with Python, OpenCV, and Streamlit. It provides real-time image enhancement, artistic filters, computer vision effects, and interactive editing tools through a user-friendly web interface.

Multi-architecture neural network comparison (FFNN, LSTM-RNN, CNN) for surface fracture detection on ~228k grayscale images

Real-time autonomous driving perception system: detection, tracking, segmentation, and TensorRT C++ deployment

Android lane detection application using OpenCV and computer vision techniques.

An AI-powered face recognition attendance system using Python, OpenCV, and Tkinter — automate student attendance with real-time facial detection, image training, and CSV tracking.

CNN-based vehicle number plate detection and recognition system using TensorFlow, OpenCV, and Flask API for real-time image inference and automated license plate identification

🌿 Projet de Computer Vision basé sur un dataset de feuilles malades : analyse exploratoire, data augmentation, transformations d’images et classification CNN. Pipeline complet en Python, tests, visualisations, reproductibilité et modèle >90% accuracy.

AI-powered Diabetic Retinopathy detection using ResNet-50, FastAPI, React, Docker and PyTorch. Full stack clinical screening system with Bayesian decision theory and TTA ensemble.

OMR Sheet Evaluation system using Python and OpenCV. Automatically detects answer bubbles, evaluates marked responses, calculates scores, and visualizes grading results. Built with Computer Vision techniques including contour detection, thresholding, morphology, and pixel-density analysis for automated exam assessment.