Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Face_recognition | 48,338 | 45 | 5 days ago | 21 | February 20, 2020 | 725 | mit | Python | ||
The world's simplest facial recognition api for Python and the command line | ||||||||||
Insightface | 14,798 | 1 | 4 | 6 days ago | 24 | January 29, 2022 | 1,256 | mit | Python | |
State-of-the-art 2D and 3D Face Analysis Project | ||||||||||
Openface | 14,689 | 4 days ago | 10 | apache-2.0 | Lua | |||||
Face recognition with deep neural networks. | ||||||||||
Face Api.js | 14,578 | 5 months ago | 414 | mit | TypeScript | |||||
JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js | ||||||||||
Deepface | 6,395 | 3 | 3 days ago | 74 | May 10, 2022 | 16 | mit | Python | ||
A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python | ||||||||||
Opencv4nodejs | 4,729 | 62 | 42 | a month ago | 120 | May 13, 2020 | 290 | mit | C++ | |
Nodejs bindings to OpenCV 3 and OpenCV 4 | ||||||||||
Howdy | 4,590 | 2 months ago | 158 | mit | Python | |||||
🛡️ Windows Hello™ style facial authentication for Linux | ||||||||||
Seetafaceengine | 4,035 | 3 years ago | 120 | other | C++ | |||||
Awesome Face_recognition | 3,876 | 4 months ago | 7 | |||||||
papers about Face Detection; Face Alignment; Face Recognition && Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution && Face Deblurring; Face Generation && Face Synthesis; Face Transfer; Face Anti-Spoofing; Face Retrieval; | ||||||||||
Facenet Pytorch | 3,412 | 3 | 8 | 2 months ago | 31 | March 10, 2021 | 68 | mit | Python | |
Pretrained Pytorch face detection (MTCNN) and facial recognition (InceptionResnet) models |
ESP-WHO is an image processing development platform based on Espressif chips. It contains development examples that may be applied in practical applications.
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 provides rich deep learning related interfaces for ESP-WHO, which can be implemented with various peripherals to realize many interesting applications.
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 | ESP32-S2 | ESP32-S3 |
---|---|---|---|
Development Board | ESP-EYE | ESP32-S2-Kaluga-1 | ESP-S3-EYE |
Using a development board not mentioned in the table above, configure pins assigned to peripherals manually, such as camera, LCD, and buttons.
ESP-WHO runs on ESP-IDF. For details on getting ESP-IDF, please refer to ESP-IDF Programming Guide.
Please use the latest ESP-IDF on the release/v4.4 branch.
Run the following commands in your terminal to download ESP-WHO:
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.
All examples of ESP-WHO are stored in examples folder. Structure of this folder is shown below:
├── 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, 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).
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:
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 not using the Espressif development boards mentioned in 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:
Click Camera Configuration to select the pin configuration of the camera according to the development board you use, as shown in the following figure:
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:
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:
Flash the program and launch IDF Monitor:
idf.py flash monitor
The default binaries for each development board are stored in the folder default_bin. You can use Flash Download Tool (https://www.espressif.com/en/support/download/other-tools) to flash binaries.
Please submit an issue if you find any problems using our products, and we will reply as soon as possible.