Train Custom Object Detection Models for Android & IOS
Integrate Object Detection models in Android like YOLO and train custom object detection models for Android and IOS
IOS Development,Development,Android
Lectures -109
Resources -1
Duration -7.5 hours
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Course 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 ( TensorFlow object detection )
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 YOLOv4, 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(Object Detection IOS)
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 / Tensorflow Object Detection
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 (Object Detection Android)
After model training and conversion we will learn to use that model inside Android applications (Java/Kotlin) with both
Images
Live camera footage / Real-Time Object Detection
Object Detection with Images (Object Detection Android)
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 (Object Detection Android)
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 (Object Detection Android)
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 / YOLO object detection
In this section
we will learn to use the latest YOLOV4 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
We will handle the integration of both the regular YOLOV4 model and the tiny YOLOv4 model in Android with both images and live camera footage.
So a complete YOLO object detection package for android.
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.
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)
Goals
- 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
Prerequisites
- Having some basic knowledge of Android App development will be a plus
![Train Custom Object Detection Models for Android & IOS Train Custom Object Detection Models for Android & IOS](https://d3mxt5v3yxgcsr.cloudfront.net/courses/12596/course_12596_image.jpg)
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction
5 Lectures
-
Course Introduction 04:01 04:01
-
What is Object Detection 04:28 04:28
-
How an Object Detection Model is Trained 03:38 03:38
-
What is there for IOS developers 01:07 01:07
-
What is there for Machine Learning Engineers 02:08 02:08
Dataset Collection and Annotation
7 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Training Custom Object Detection models
3 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Java: Image Picker Section
5 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Kotlin: Image Picker Section
5 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Java: Object Detection with Images
10 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Kotlin: Object Detection with Images
10 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Java: Object Detection with Live Camera Footage / Real Time Object Detection
6 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Kotlin: Object Detection with Live Camera Footage / Real Time Object Detection
6 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Pretrained Object Detection Models
1 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Java: Using EfficientDet Models Family in Android
7 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Kotlin: Using EfficientDet Models Family in Android
7 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Java: Using SSD MobileNet Models in Android
10 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Kotlin: Using SSD MobileNet Models in Android
10 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
YOLO (You Only Look Once)
10 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Instructor Details
![Hamza Asif](https://www.tutorialspoint.com/assets/profiles/536013/profile/200_381301-1692691672.jpg)
Hamza Asif
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