Computer Vision Tutorials

Learn how to fine tune the Vision Transformer (ViT) model for the image classification task using the Huggingface Transformers, evaluate, and datasets libraries in Python.

Learn how to use image segmentation transformer model to segment any image using huggingface transformers and PyTorch libraries in Python.

Learn how to use pre-trained image captioning transformer models and what are the metrics used to compare models, you'll also learn how to train your own image captioning model with Pytorch and transformers in Python.

Learn how to build a complete GUI QR code generator and reader program in Python using Tkinter, qrcode and OpenCV libraries.

Learn how to fine-tune the current state-of-the-art EffecientNet V2 model to perform image classification on satellite data (EuroSAT) using TensorFlow in Python.

Learn how to perform age and gender detection using OpenCV library in Python with camera or image input.

Learn how to perform gender detection on detected faces in images using OpenCV library in Python.

Learn how to predict someone's age from his front face picture using OpenCV library in Python

Learn how to compute and detect SIFT features for feature matching and more using OpenCV library in Python.

Learn how to use scikit-image library to extract Histogram of Oriented Gradient (HOG) features from images in Python.

Learn how to perform perspective image transformation techniques such as image translation, reflection, rotation, scaling, shearing and cropping using OpenCV library in Python.

Learn how to make a barcode scanner that decodes barcodes and draw them in the image using pyzbar and OpenCV libraries 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.

Learn how to use transfer learning to build a model that is able to classify benign and malignant (melanoma) skin diseases in Python using TensorFlow 2.