Human Tracking & Counting using TensorFlow & Deep Learning
Uncover the art of Human Tracking & Counting with TensorFlow & Deep Learning! Explore how AI technologies are revolutionizing people tracking and crowd analysis. #HumanTracking #DeepLearning #TensorFlow #AIInstitute ▼
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Course Feature
Cost:
Paid
Provider:
Udemy
Certificate:
Paid Certification
Language:
English
Start Date:
2023-04-01
Course Overview
❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [August 31st, 2023]
What does this course tell?
(Please note that the following overview content is from Alison)
This python project is a Human Detection and Counting System through Webcam. It is an intermediate-level deep learning project on computer vision and TensorFlow which can help you master the concepts of AI and become an expert in Data Science. The course is divided into 14 sections, covering topics such as Artificial Intelligence, Neural Networks, Object Detection Models, Computer Vision Library, TensorFlow TF API, IDE and required settings, Jupyter notebook, dependencies, paths, labels, real-time demonstrations, source code, OpenCV, Annotations, Human Detection Model, pre-trained models, TensorFlow Model API, Protocol Buffers, Model Garden, WGET Module, Protoc, training, evaluation, checkpoints, pipeline configurations, label maps, model records, TensorFlow Lite, freezing graphs, and archiving models. Technical support is available from Monday to Saturday, and the course comes with a 30-day Money Back Guarantee.
We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
What skills and knowledge will you acquire during this course?
In this course, students will acquire skills and knowledge in human tracking and counting using TensorFlow and deep learning. They will learn about artificial intelligence, neural networks, object detection models, computer vision library, TensorFlow TF API and its detailed specifications and applications, human detection model, software and tools installation, setting up python environments, jupyter notebook, importing dependencies, defining and setting paths, computer vision library, capturing images using OpenCV, annotations and their types, customizing models, pre-trained models, script records, label maps, TensorFlow Model API and Protocol Buffers, Model Garden, WGET Module, Protoc, downloading pre-trained models from TensorFlow Zoo, creating label maps, writing files, model records, training and test records, copying model config into the training folder, pipeline configurations, checkpoints, configuring, copying and writing pipeline config, training and evaluating Human Detection Model, model evaluation, mean average precisions, recalls, confusion matrix, loading pipeline configs, restoring checkpoints, building a detection model, testing Human Detection Model from an image file, real-time detections from a webcam, freezing graphs, TensorFlow lite, and archiving models.
lHow does this course contribute to professional growth?
This course contributes to professional growth by providing a comprehensive understanding of Artificial Intelligence, Neural Networks, Object Detection Models, Computer Vision Library, TensorFlow, TF API, and its applications. It also covers the installation of software and tools such as Anaconda, Visual Studio, and Jupyter, as well as setting up Python environments. Additionally, the course covers Human Detection Model, Annotations, TensorFlow Model API and Protocol Buffers, Model Garden, WGET Module, Protoc, and the verification of the source code. Furthermore, it covers Training Script commands, Model Evaluation, Loading Pipeline Configs, Restoring Checkpoints, Building a Detection Model, Testing Human Detection Model from an Image File, Real-Time Detection from a Webcam, Freezing Graphs, TensorFlow Lite, and Archiving Models. This course provides a comprehensive understanding of the concepts of AI and can make one an expert in the field of Data Science.
Is this course suitable for preparing further education?
This course is suitable for preparing further education as it covers a wide range of topics related to Artificial Intelligence, Neural Networks, Object Detection Models, Computer Vision Library, TensorFlow, TF API, Human Detection Model, Anaconda, Visual Studio, Jupyter, IDE, Python environments, OpenCV, Annotations, Customizing Models, Pre-trained Models, Script Records, Label Maps, Model Garden, WGET Module, Protoc, Model Records, Pipeline Configurations, Checkpoints, Training Scripts, Model Evaluation, Loading Pipeline Configs, Restoring Checkpoints, Building Detection Model, Testing from Image File, Real-Time Detection from Webcam, Freezing Graphs, TensorFlow Lite, and Archiving Models. The course also comes with dedicated technical support and a 30-day money-back guarantee, making it a safe and reliable option for further education.
Course Syllabus
INTRODUCTION
GETTING STARTED WITH HUMAN DETECTION MODEL
STARTING WITH JUPYTER NOTEBOOK
SETTING DIRECTORIES & LABEL PATH
CAPTURING IMAGES USING OPEN-CV AND MAKING ANNOTATIONS
HUMAN DETECTION MODEL & WORKSPACE
TENSORFLOW MODEL API AND PROTOCOL BUFFERS
WORKING WITH MODELS
CONFIGURING PIPELINE CONFIGURATION
TRAINING & EVALUATION OF HUMAN DETECTION MODEL
TRAINED MODEL AND CHECK-POINT
TESTING HUMAN DETECTION MODEL
REAL-TIME DETECTION FROM WEB-CAMS
SAVING HUMAN DETECTION MODEL
Course Provider
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