Hello and thank you for this awesome article. I'm kind of new to Github (learnt it all this summer) and I'm slowly digging in into the community. So far I'm trying to migrate all my local projects to git, and I was really wondering how I will ever attract other people.
This article will be my checklist from now on! Thank you again. Here's one of my "hard-worked" repos:
Age and Gender classification in real-time, using Convolutional Neural Networks (with MobileNet v1 network using a converted .tflite model), on Raspberry Pi 4. The app is wrapped in PyQt5 interface.
Real-Time Age and Gender Classification on RaspberryPi4 using TFLite and PyQt5 Interface
Automatic age and gender classification in real-time, using Convolutional Neural Networks (based on MobileNet v1 network), fitted on Raspberry Pi 4 model using a converted .tflite model. The application is wrapped in a simple and modern UI using PyQt5.
Automatic age and gender classification can be used in a large number of applications, especially in intelligent human-computer interfaces, as well as in biometrics, visual surveillance, limited access to multimedia content, and for commercial applications such as self-checkouts.
Hello and thank you for this awesome article. I'm kind of new to Github (learnt it all this summer) and I'm slowly digging in into the community. So far I'm trying to migrate all my local projects to git, and I was really wondering how I will ever attract other people.
This article will be my checklist from now on! Thank you again. Here's one of my "hard-worked" repos:
Age and Gender classification in real-time, using Convolutional Neural Networks (with MobileNet v1 network using a converted .tflite model), on Raspberry Pi 4. The app is wrapped in PyQt5 interface.
Real-Time Age and Gender Classification on RaspberryPi4 using TFLite and PyQt5 Interface
Automatic age and gender classification in real-time, using Convolutional Neural Networks (based on MobileNet v1 network), fitted on Raspberry Pi 4 model using a converted .tflite model. The application is wrapped in a simple and modern UI using PyQt5.
Contents:
Demo
Screenshots
About this App
Automatic age and gender classification can be used in a large number of applications, especially in intelligent human-computer interfaces, as well as in biometrics, visual surveillance, limited access to multimedia content, and for commercial applications such as self-checkouts.
This app is proposed to be an optimal…