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https://github.com/espressif/esp-who

Face detection and recognition framework
https://github.com/espressif/esp-who

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Face detection and recognition framework

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README 

        
# ESP-WHO [[中文]](./README_CN.md)



ESP-WHO is an image processing development platform based on Espressif chips. It contains development examples that may be applied in practical applications.



## Overview



ESP-WHO provides examples such as Human Face Detection, Human Face Recognition, Cat Face Detection, Gesture Recognition, etc. You can develop a variety of practical applications based on these examples. ESP-WHO runs on ESP-IDF. [ESP-DL](https://github.com/espressif/esp-dl) provides rich deep learning related interfaces for ESP-WHO, which can be implemented with various peripherals to realize many interesting applications.





     




## What You Need



### Hardware



We recommend novice developers to use the development boards designed by Espressif. The examples provided by ESP-WHO are developed based on the following Espressif development board, and the corresponding relationships between the development boards and SoC are shown in the table below.

    

|    SoC    | [ESP32](https://www.espressif.com/en/products/socs/esp32) | [ESP32-S2](https://www.espressif.com/en/products/socs/esp32-s2) | [ESP32-S3](https://www.espressif.com/en/products/socs/esp32-s3) |

| :------- | :----------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: |

| Development Board | [ESP-EYE](https://www.espressif.com/en/products/devkits/esp-eye/overview) | [ESP32-S2-Kaluga-1](https://docs.espressif.com/projects/esp-idf/en/latest/esp32s2/hw-reference/esp32s2/user-guide-esp32-s2-kaluga-1-kit.html) | [ESP-S3-EYE](https://www.espressif.com/en/products/devkits/esp-s3-eye/overview) |



> Using a development board not mentioned in the table above, configure pins assigned to peripherals manually, such as camera, LCD, and buttons.



### Software



#### Get ESP-IDF



ESP-WHO runs on [ESP-IDF release/v5.0](https://github.com/espressif/esp-idf/tree/release/v5.0) branch . For details on getting ESP-IDF, please refer to [ESP-IDF Programming Guide](https://idf.espressif.com/).  

If you use [ESP-IDF release/v4.4](https://github.com/espressif/esp-idf/tree/release/v4.4), please checkout the ESP-WHO branch to the idfv4.4.



#### Get ESP-WHO



Run the following commands in your terminal to download ESP-WHO:



```bash

git clone --recursive https://github.com/espressif/esp-who.git

```



> Remember to use ``git submodule update --recursive --init`` to pull and update submodules of ESP-WHO.



## Run Examples



All examples of ESP-WHO are stored in [examples](./examples) folder. Structure of this folder is shown below:



```bash

├── examples

│   ├── cat_face_detection          // Cat Face Detection examples

│   │   ├── lcd                     // Output displayed on LCD screen

│   │   ├── web                     // Output displayed on web

│   │   └── terminal                // Output displayed on terminal

│   ├── code_recognition            // Barcode and QR Code Recognition examples

│   ├── human_face_detection        // Human Face Detection examples

│   │   ├── lcd

│   │   ├── web

│   │   └── terminal

│   ├── human_face_recognition      // Human Face Recognition examples

│   │   ├── lcd

│   │   ├── terminal

│   │   └── README.md               // Detailed description of examples

│   └── motion_detection            // Motion Detection examples

│       ├── lcd 

│       ├── web

│       ├── terminal

│       └── README.rst              

```



For the development boards mentioned in [Hardware](#Hardware), all examples are available out of the box. To run the examples, you only need to perform [Step 1: Set the target chip] (#Step-1 Set the target chip) and [Step 4: Launch and monitor] (#Step-4 Launch and monitor).



### Step 1: Set the target chip



Open the terminal and go to any folder that stores examples (e.g. examples/human_face_detection/lcd). Run the following command to set the target chip: 



```bash

idf.py set-target [SoC]

```



Replace [SoC] with your target chip, e.g. esp32, esp32s2, esp32s3.



**NOTE:** we implement examples of target chip `esp32s3` with ESP32-S3-EYE by defaults. So that `flash` and `monitor` are through USB. If you are using other board, please confirm which method you will use first,



- If by USB, just keep it in defaults,

- If by UART, set it in menuconfig.



### (Optional) Step 2: Configure the camera



If not using the Espressif development boards mentioned in [Hardware](#Hardware), configure the camera pins manually. Enter `idf.py menuconfig` in the terminal and click (Top) -> Component config -> ESP-WHO Configuration to enter the ESP-WHO configuration interface, as shown below:



![](./img/esp-who_config.png)



Click Camera Configuration to select the pin configuration of the camera according to the development board you use, as shown in the following figure:



![](./img/esp-who_config_camera_config_select_pinout.png)



If the board you are using is not shown in the figure above, please select ``Custom Camera Pinout`` and configure the corresponding pins correctly, as shown in the following figure: 



![](./img/esp-who_config_camera_config_custom.png)



### (Optional) Step 3: Configure the Wi-Fi



If the output of example is displayed on web server, click Wi-Fi Configuration to configure Wi-Fi password and other parameters, as shown in the following figure: 



![](./img/esp-who_config_wifi_config.png)



### Step 4: Launch and monitor



Flash the program and launch IDF Monitor:



```bash

idf.py flash monitor

```



## Default Binaries of Development Boards



The default binaries for each development board are stored in the folder [default_bin](./default_bin). You can use Flash Download Tool (https://www.espressif.com/en/support/download/other-tools) to flash binaries.



## Feedback



Please submit an [issue](https://github.com/espressif/esp-who/issues) if you find any problems using our products, and we will reply as soon as possible.