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# Overview

This chapter introduces you to the overall framework of MMYOLO and provides links to detailed tutorials.

## What is  MMYOLO

![pic](https://user-images.githubusercontent.com/12907710/137271636-56ba1cd2-b110-4812-8221-b4c120320aa9.png)

MMYOLO is a YOLO series algorithm toolbox, which currently implements only the target detection task and will subsequently support various tasks such as instance segmentation, panoramic segmentation and key point detection. It includes a rich set of target detection algorithms and related components and modules, and the following is its overall framework.

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MMYOLO file structure is identical to the MMDetection. To allow full reuse of the MMDetection code, MMYOLO includes only custom content, which consists of 3 main parts: `datasets`, `models`, `engine`.
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- **datasets** supports a variety of data sets for target detection
  - **transforms** includes various data enhancement transforms
- **models** is the most important part of the detector, which include different component of it.
  - **detectors** define all detection model classes
  - **data_preprocessors** is used to preprocess the dataset of the model
  - **backbones** include various backbone networks
  - **necks** include various neck components
  - **dense_heads** include various dense head of different tasks
  - **losses** include various loss functions
  - **task_modules** provide component for testing tasks,such as assigners、samplers、box coders and prior generators。
  - **layers** provide some basic network layers
- **engine** is a component of running
  - **optimizers** provide optimizers and packages for optimizers
  - **hooks** provide hooks for runner

## How to use this tutorial

The detailed instruction of MMYOLO is as following

1. Look up install instruction through [start your first step](get_started.md)

2. Basic method of how to use MMYOLO can be found here:

   - [Training and testing](https://mmyolo.readthedocs.io/en/latest/user_guides/index.html#train-test)
   - [From getting started to deployment tutorial](https://mmyolo.readthedocs.io/en/latest/user_guides/index.html#from-getting-started-to-deployment-tutorial)
   - [Useful Tools](https://mmyolo.readthedocs.io/en/latest/user_guides/index.html#useful-tools)

3. YOLO series of tutorials on algorithm implementation and full analysis:

   - [Essential Basics](https://mmyolo.readthedocs.io/en/latest/algorithm_descriptions/index.html#essential-basics)
   - [Full explanation of the model and implementation](https://mmyolo.readthedocs.io/en/latest/algorithm_descriptions/index.html#algorithm-principles-and-implementation)

4. Refer to the following tutorials for an in-depth look:

   - [How to](https://mmyolo.readthedocs.io/en/latest/advanced_guides/index.html#how-to)