vcc_gnd
/
esp-who
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity
官方ESP-WHO资料，这里可以找到板子的测试DEMO,推荐乌班图下编译生成固件
118 Commits
6 Branches
10 Tags
30 MiB
C 72.5%
HTML 21.9%
C++ 4.5%
Shell 0.8%
CMake 0.2%
 
 
 
 
 
Go to file
XiaochaoGONG 1911942083 sync esp-face 
- add implementation tutorial
- Fix transform_output
 		2020-02-17 13:33:28 +08:00
components sync esp-face 2020-02-17 13:33:28 +08:00
docs Bugfix/change alloc interface 2019-10-22 19:09:35 +08:00
esp-idf@143d26aa49 update idf v3.3.1 2020-01-06 20:03:15 +08:00
examples/single_chip add new face recognition models 2020-01-07 17:35:03 +08:00
img update docu 2019-06-04 15:34:25 +08:00
tools/ci Misc/gitlab ci 2019-10-17 21:42:33 +08:00
.gitignore Feature/http recog 2018-12-29 18:02:22 +08:00
.gitlab-ci.yml Misc/gitlab ci 2019-10-17 21:42:33 +08:00
.gitmodules Init commit 2018-11-23 16:05:18 +08:00
CHANGELOG.md WIP 2019-01-24 11:10:30 +08:00
LICENSE Init commit 2018-11-23 16:05:18 +08:00
README.md update readme idfv3.3.1 2020-01-07 17:42:19 +08:00

README.md

ESP-WHO

ESP-WHO is a face detection and recognition platform that is currently based on Espressif Systems' ESP32 chip.

Overview

ESP-WHO supports development of face detection and recognition applications based around Espressif Systems' ESP32 chip in the most convenient way. With ESP-WHO, you can easily build up face detection- and recognition-featured applications, for instance:

  • A coffee machine that brews coffee according to your taste preference;
  • Home applicance that will shut off the electricity automatically when unsupervised children are operating them;
  • And other more applications that suit your needs.

In general, the ESP-WHO features will be supported as shown below:

overview

In ESP-WHO, Detection, Recognition and Image Utility are at the core of the platform.

  • Image Utility offers fundamental image processing APIs.

  • Detection takes images as input and give the position of face if there is a face. It is implemented with MTMN model, which refers to MTCNN and MobileNets.

  • Recognition is to identify the particular person, and it needs the results of detection. It is implemented with MobileFace model.

  • Optimization is mainly to increase the precision of the inference, and to accelerate the whole process. But also it might change the structure of the network, update the coefficients, refactor the code, etc.

Both input and output are flexible.

  • Image sources could be input via camera. However, we don't provide many drivers right now, those for other camera modules will be released in the future.

  • Results could be output and displayed through Command line, LCD or even website via Wi-Fi http service.

Quick Start with ESP-WHO

Hardware Preparation

To run ESP-WHO, you need to have a development board which integrates a ESP32 module that has sufficient GPIO pins and more than 4 MB external SPI RAM. Either ESP-WROVER-KIT or ESP-EYE can be a good choice as the test board.

On how to configure ESP32 module for your applications, please refer to the README.md of each example.

Software Preparation

Image

The recommended resolution of input image is QVGA (320x240).

As for choosing camera as an image offer, make sure that the ESP32 module you choose offers specific pins that your camera needs.

By now, we have provided the driver of OV2640 and OV3660, which are highly recommended to get started with.

ESP-WHO

Make sure you clone the project recursive:

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

If you clone project without --recursive flag, please go to the esp-who directory and run command git submodule update --init before doing anything.

ESP-IDF

See setup guides for detailed instructions to set up the ESP-IDF:

In this case, we take ESP-IDF v3.3.1 as the test version.

If you have already configured ESP-IDF before and don't want to change the existing one, you can just point IDF_PATH to the ESP-IDF that is in ESP-WHO.

Components

Components is the main framework of the SDK, with some drivers and algorithm inside.

Camera

The camera component contains drivers for camera devices of ESP32.

esp-face

The esp-face component contains the APIs of ESP-WHO neural networks, including face detection and recognition framework.

Examples

The folder of examples contains sample applications demonstrating the API features of ESP-WHO.

Take one Face Detection as an example.

  1. Get into one example folder esp-who/examples/single_chip/detection_with_command_line.
cd esp-who/examples/single_chip/detection_with_command_line
  1. Compile and flash the project.
idf.py build
idf.py flash -p [PORT]
  1. Advanced users can modify some options by using the command idf.py menuconfig.

Check README.md of each example for more details.

Resources