MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + srt | Duration: 61 lectures (3h 59m) | Size: 958.6 MB Learn Face Recognition for Face Mask Detection using Python, TensorFlow 2, OpenCV, PyQT, Qt
What you'll learn: Face Recognition for Mask detection with Deep Learning Develop Convolutional Network Network for Face Mask from Scratch using TensorFlow Preprocess the big data of image OpenCV for Face Detection Requirements Basic Python Knowledge Familiar with Tensor Flow and Deep Learning Familiar with Numpy and Pandas Description Project that you will be Developing: Prerequisite of Project: OpenCV Image Processing with OpenCV Section -0 : Setting Up Project Install Python Install Dependencies Section -1 : Data Preprocessing Gather Images Extract Faces only from Images Labeling (Target output) Images Data Preprocessing RGB mean subtraction image Section - 2: Develop Deep Learning Model Training Face Recognition with OWN Deep Learning Model. Convolutional Neural Network Model Evaluation Section - 3: Prediction with CNN Model 1. Putting All together Section - 4: Flask API Setting Up Visual Studio Code Install all Dependencies of VS Code Setting Virtual Environment Freeze Requirements Build Flask API Overview: I will start the course by installing Python and installing the necessary libraries in Python for developing the end-to-end project. Then I will teach you one of the prerequisites of the course that is image processing techniques in OpenCV and the mathematical concepts behind the images. We will also do the necessary image analysis and required preprocessing steps for the images. Then we will do a mini project on Face Detection using OpenCV and Deep Neural Networks. With the concepts of image basics, we will then start our project phase-1, face identity recognition. I will start this phase with preprocessing images, we will extract features from the images using deep neural networks. Then with the features of faces, we will train the different Deep learning models like Convolutional Neural Network. I will teach you the model selection and hyperparameter tuning for face recognition models Once our Deep learning model is ready, will we move to Section-3, and write the code for preforming predictions with CNN model. Finally, we will develop Flask API and make prediction to live video streaming. What are you waiting for? Start the course develop your own Computer Vision Flask Web Project using Machine Learning, Python and Deploy it in Cloud with your own hands. Who this course is for Anyone who want to develop face recognition application Homepage