Autonomous driving - car detection using the very powerful YOLO model
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Updated
Jul 18, 2018 - Python
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Autonomous driving - car detection using the very powerful YOLO model
Detecting Cars in real time and identifying the speed of cars and tracking
Car's plate detection and car's colour detection with YOLO5 and LPRnet
"Car Detection" is trained in Keras using Tensorflow as back-end. It's taking an image as input & gives a binary decision whether a car is present in the image or not.
This is a Multi object tracker. Mainly it was build for tracking car movement in a junction.
This model is very useful to detecting cars, buses, and trucks in a video.
Simple car and pedestrian detection in video using "openCV" library 🚗 🚶
Car-Model-Detection is a Python project that uses transfer learning with the ResNet50 model to detect the brand of cars.
Mini Projects like lane detection, face detection, car detection, pedestrian detection and segmentation using only OpenCV tools.
Detecting Cars in a video using OpenCV and the pretrained haarcascade data set for car detection!
Web-service for car washes
"Car Detection" is trained in Keras using Tensorflow as back-end. It's taking an image as input & gives a binary decision whether a car is present in the image or not.
Cars and Pedestrains Detection
Detection of cars from video or live webcam using opencv python
Car Detection for Autonomous driving using YOLO algorithm.
Using OpenCV to detect cars! This is how self driving cars works. Using pretrained data of haarcascade for detecting cars!
Detection of cars from video or live webcam using opencv python
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