OVERVIEW

This chapter introduces you to the framework of MMDetection, and provides links to detailed tutorials about MMDetection.

What is MMDetection

MMDetection is an object detection toolbox that contains a rich set of object detection, instance segmentation, and panoptic segmentation methods as well as related components and modules, and below is its whole framework:

MMDetection consists of 7 main parts, apis, structures, datasets, models, engine, evaluation and visualization.

• apis provides high-level APIs for model inference.

• structures provides data structures like bbox, mask, and DetDataSample.

• datasets supports various dataset for object detection, instance segmentation, and panoptic segmentation.

  • transforms contains a lot of useful data augmentation transforms .

  • samplers defines different data loader sampling strategy.

• models is the most vital part for detectors and contains different components of a detector.

  • detectors defines all of the detection model classes.

  • data_preprocessors is for preprocessing the input data of the model.

  • backbones contains various backbone networks

  • necks contains various neck components

  • dense_heads contains various detection heads that perform dense predictions.

  • roi_heads contains various detection heads that predict from RoIs.

  • seg_heads contains various segmentation heads

  • losses contains various loss functions

  • task_modules provides modules for detection tasks. E.g. assigners, samplers, box coders, and prior generators.

  • layers provides some basic neural network layers

• engine is a part for runtime components.

  • runner provides extensions for MMEngine’s runner.

  • schedulers provides schedulers for adjusting optimization hyperparameters.

  • optimizers provides optimizers and optimizer wrappers.

  • hooks provides various hooks of the runner.

• evaluation provides different metrics for evaluating model performance.

• visualization is for visualizing detection results.

How to Use this Guide

Here is a detailed step-by-step guide to learn more about MMDetection:

1. For installation instructions, please see get_started.

2. Refer to the below tutorials for the basic usage of MMDetection.

   • Train and Test

   • Useful Tools

3. Refer to the below tutorials to dive deeper:

   • Basic Concepts

   • Component Customization