Image Tutorials

These tutorials will help you learn how to create and use models that work with images and other computer vision tasks. Most of these tutorials use the MXNet GluonCV toolkit.

Basic Image Tutorials

MNISTmnist.html

How to create a convolutional neural network for handwritten digit recognition.

Image Recognition with Pretrained Modelspre-trained_models.html

How to use pretrained models to recognize what is in an image.

Advanced Image Tutorials

Image similarity search with InfoGANhttps://mxnet.apache.org/versions/master/tutorials/gluon/info_gan.html

Implementing an InfoGAN based on the MXNet Gluon.

GluonCV Toolkit Tutorials

These tutorials link to the MXNet GluonCV Toolkit website.

Prepare Datasetshttps://gluon-cv.mxnet.io/build/examples_datasets/index.html

How to use built-in MXNet GluonCV features for loading and preparing both common & custom datasets.

Image Classificationhttps://gluon-cv.mxnet.io/build/examples_classification/index.html

Pretrained models for inference, fine-tune models, train your own model on ImageNet, and more.

Object Detectionhttps://gluon-cv.mxnet.io/build/examples_detection/index.html

Learn how to use Single shot detector (SSD), RCNN, and YOLO models.

Semantic Segmentationhttps://gluon-cv.mxnet.io/build/examples_segmentation/index.html

Learn how to use and train models that can identify and segment objects in an image.

Instance Segmentationhttps://gluon-cv.mxnet.io/build/examples_instance/index.html

Learn how to use and train models the perform a variation of semantic segmentation that also classifies similar objects into discrete entities.

Pose Estimationhttps://gluon-cv.mxnet.io/build/examples_pose/index.html

Learn how to use a simple Pose network that predicts the heatmap for each joint then map it to the coordinates on the original image.