Description
Face Mask Recognition: Deep Learning based Desktop App, the course of creating a deep learning based face mask recognition desktop app, has been published by Udemy Academy. The instructor starts this course by installing Python and the necessary libraries for the development of the end-to-end project. Then, one of the prerequisites of this course, which is image processing techniques in OpenCV and the mathematical concepts behind the images, will teach you. He will also perform the necessary image analysis and pre-processing steps required for the images. Then you will do a small project on face recognition using OpenC and Deep NeuralV.
Using basic image concepts, the instructor begins his project step by step, phase one: face recognition. He will start this step with pre-processed images, you extract the features of the images using deep neural networks. Then, with the features of faces, you train different deep learning models such as convolutional neural network. You will also learn model selection and hyperparameter setting for facial recognition models. When the deep learning model is ready, you go to part 3 and write the code related to the predictions with the CNN model. Finally, you will develop a desktop application and enable live video streaming.
What you will learn
- Face recognition for mask recognition with deep learning
- Development of convolutional network for face mask from scratch using TensorFlow
- Big image data preprocessing
- OpenCV for face recognition
- Computer vision desktop application with PyQt
- Essential concepts of PyQt
Who is this course suitable for?
- People who want to develop facial recognition application
Specifications of Face Mask Recognition course: Deep Learning based Desktop App
Head of the course chapters on 2022-6
Course prerequisites
- Basic Python Knowledge
- Familiar with Tensor Flow and Deep Learning
- Familiar with Numpy and Pandas
Pictures
Sample video
Installation guide
After Extract, view with your favorite Player.
English subtitle
Quality: 720p
download link
File(s) password: www.downloadly.ir
Size
1.22 GB
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