Building a real-time automatic number plate recognition system using YOLO and OpenCV library in Python, order your copy now!Download EBook
Using image processing, machine learning and deep learning methods to build computer vision applications using popular frameworks such as OpenCV and TensorFlow in Python.
Learn how to build a deep learning malaria detection model to classify cell images to either infected or not infected with Malaria Tensorflow 2 and Keras API in Python.
Blurring and anonymizing faces in images and videos after performing face detection using OpenCV library in Python.
Using the state-of-the-art YOLOv8 object detection for real-time object detection, recognition and localization in Python using OpenCV, Ultralytics and PyTorch.
Using K-Means Clustering unsupervised machine learning algorithm to segment different parts of an image using OpenCV in Python.
Learning how to detect contours in images for image segmentation, shape analysis and object detection and recognition using OpenCV in Python.
Detecting shapes, lines and circles in images using Hough Transform technique with OpenCV in Python. Hough transform is a popular feature extraction technique to detect any shape within an image.
Learning how to apply edge detection in computer vision applications using canny edge detector algorithm with OpenCV in Python.
Learn what is transfer learning and how to use pre trained MobileNet model for better performance to classify flowers using TensorFlow in Python.