Published 10/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 108 lectures (8h 34m) | Size: 6.3 GB
Integrate Object Detection models in Android like YOLO and train custom object detection models for Android and IOS
What you’ll learn
Train object detection models on custom datasets for Android and IOS
Test and optimize trained object detection model
Use object detection models with images in Android
Use object detection models with live camera footage in Android
Collect and annotate datasets for training object detection models
Use YOLO models in Android with images and live camera footage
Use SSD Mobilenet models in Android with images and live camera footage
Use Efficient Det models in Android with images and live camera footage
Convert object detection model into tflite formats
Learn about object detection and it’s applications
Learn about tflite (TensorFlow lite) models integration in Android
Requirements
Having some basic knowledge of Android App development will be a plus
Description
If you want to train custom object detection models for Android and iOS then welcome to this course.
In this course, you will learn to
Train your custom object detection models for Android and IOS
Use those models in Android (Java/Kotlin) with images and live camera footage
Use existing object detection models like YOLO, EfficientDet, and MobileNet models in Android (Java/Kotlin)
The android app development section of this course is for both java and kotlin programming languages.
So after completing this course you will be able to
Collect datasets for training object detection models
Annotate datasets using different tools
Train object detection models on custom datasets for Android and IOS
Convert object detection models into tflite (Tensorflow lite) format
Use those converted models in Android (Java/Kotlin) with images and live camera footage
Use existing object detection models in Android (Java/Kotlin) like YOLO v4, SSD EfficientDet Models, and SSD MobileNet Models
Ready to use Resources
The course comes with ready-to-use codes which means if you have a trained object detection model then
You can take complete android (Java/Kotlin) application codes from course resources
Replace the object detection model with your custom model
And use it for your custom use case
and if you want to use existing object detection models in Android for your custom use cases then
you can take complete android (Java/Kotlin) application codes from course resources
and customize it as per your needs
What is there for IOS developers?
So apart from Android, If you want to train custom object detection models for IOS applications then you can also take this course but the integration of object detection models in IOS applications is not included in this course
Object Detection
Object detection is a computer vision technique that allows us to identify and locate objects in an image or video.
Use Cases & Applications
Video surveillance
Crowd counting
Anomaly detection (i.e. in industries like agriculture, and health care)
Self-driving cars
Course Curriculum
The course is divided into several sections
Data collection and Annotation
In this section, we will cover the basics of dataset collection and annotation and then
We will learn to collect the dataset for training an object detection model
After that, we will learn to annotate that dataset using Roboflow and other such tools
Training Object Detection Model
We will learn to train an object detection model using the dataset we collected and annotated.
Testing and Conversion
After training the model we will test it to check model performance and accuracy
Then we will convert it into tflite (Tensorflow lite) format so that we can use it in mobile applications.
Android App Development
After model training and conversion we will learn to use that model inside Android applications (Java/Kotlin) with both
Images
Live camera footage
Object Detection with Images
So firstly we will build an Android (Java/Kotlin) application where
users can choose images from the gallery or capture images using the camera
and then those images will be passed to our custom object detection model
and then based on the results returned by the model we will draw rectangles around detected objects.
Object Detection with live camera footage
Secondly, we will build an Android (Java/Kotlin) application in which
we will display the live camera footage using camera 2 API
and then we will pass frames of live camera footage to our object detection model
and draw rectangles around the detected objects in real-time
Existing Object Detection Models
We will learn to use existing object detection models inside Android (Java/Kotlin) Applications with both images and live camera footage.
So in that section, we explore three popular families of object detection models and use them inside Android (Java/Kotlin) Applications.
SSD MobileNet Models
Efficient Det Models
YOLO Models
SSD MobileNet Models
In this section, we will learn to use SSD MobileNet Models in Android (Java/Kotlin) with both images and live camera footage.
Firstly we will learn about the structure of MobileNet models and then we will use two popular MobileNet models in Android (Java/Kotlin) which are
SSD MobileNet V1
SSD MobileNet v3
Efficient Det Models
In this section, we will learn to use EfficientDet Models in Android (Java/Kotlin) with both images and live camera footage.
Firstly we will learn about the structure of EfficientDet models and then we will use two popular EfficientDet models in Android (Java/Kotlin) which are
EfficientDet Lite0
EfficientDet Lite1
EfficientDet Lite2
EfficientDet Lite3
YOLO Models
In this section, we will learn to use the latest YOLO V4 model in Android (Java/Kotlin) with both images and live camera footage. We will also cover the YOLO model structure and how input and outputs are handled in YOLO effectively. Apart from that, we will handle the integration of both the regular YOLO V4 model and the tiny YOLO v4 model in Android with both images and live camera footage.
Sign up today, and look forwards to
HD 1080p video content.
Training custom object detection models
Building fully-fledged Android (Java/Kotlin) applications using different object detection models.
All the knowledge you need to start building Object Detection-based Android (Java/Kotlin) application you want
$1000+ Source codes of Android (Java/Kotlin) Applications.
REMEMBER… I’m so confident that you’ll love this course and you will also get 30 days money back guarantee by udemy. So it’s a complete no-brainer, sign up today with ZERO risks and EVERYTHING to gain.
So what are you waiting for? Click the buy now button and join the world’s best Object Detection course.
Who this course is for
Anyone who wants to train object detection models for Android (Java/Kotlin)
Anyone who wants to use object detection models in Android (Java/Kotlin) with images and live camera footage
Beginner Android developer with very little knowledge of mobile app development in Android (Java/Kotlin)
An Intermediate Android developer wanted to build a powerful Machine Learning-based application for Android (Java/Kotlin)
Experienced Android (Java/Kotlin) developers wanted to use Machine Learning models inside their applications.
Machine Learning experts want to use their object detection models in Android (Java/Kotlin)
Who this course is for
Someone want to train custom Object Detection models and build mobile applications
Android Developers want to build smart Machine Learning based Android Applications
IOS Developers want to train custom Object Detection model for IOS applications( model integration for IOS is not included in this course)
Students who have basic knowledge of Android app development and want to build smart machine learning based Android Applications
Students who want to learn use of existing object detection models in Android (YOLO, EfficientDet, mobileNet)
Machine Learning Engineers want to use their existing object detection model in Android
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