Train Object Detection for Android 2024 | Build Realtime Object Detection Apps with Tensorflow Lite

Learn to train custom Object Detection models for Android. Use Tensorflow Lite Object Detection models in Android apps using Java & Kotlin

🚀 Get the full Train Object Detection Models for Android - The 2024 Guide

Welcome to the Android app development course focused on custom object detection models using Kotlin and Java.

In this course, you will learn to:
1: Train custom object detection models for Android using Kotlin and Java.
2: Implement these models in Android apps to process images and live camera footage.
3: Utilize existing object detection models like YOLO, EfficientDet, and MobileNet within Android apps.
4: The Android app development section covers both Kotlin and Java programming languages.

By the end of this course, you will be able to:
1: Collect and annotate datasets for training object detection models.
2: Train models on custom datasets for Android using TensorFlow.
3: Convert models to TensorFlow Lite format for mobile use.
4: Integrate these models into Android apps with image and real-time camera detection.
5: Utilize existing models like YOLO , SSD EfficientDet, and SSD MobileNet in Android apps.

Resources included:
1: Ready-to-use Android (Kotlin/Java) application codes.
2: Customisation guides for integrating your object detection models.
3: Examples of using existing object detection models in Android apps.

Object Detection Applications:
Video surveillance
Crowd counting
Anomaly detection in industries
Self-driving cars

For iOS developers:
While the course also covers training object detection models for iOS, the focus is on Android app development using Kotlin and Java. Integration of these models into iOS apps is not included.

Course highlights:
1: Data collection and annotation: Learn to gather and label datasets for training custom object detection models
2: Model training: Train object detection models with TensorFlow.
3: Model conversion: Convert trained models to TensorFlow Lite.
4: Android app development: Build apps using Kotlin and Java that can process images and live camera feeds.
5: Using existing models: Implement popular object detection models in your Android apps.

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[mygmail]

Your courses are very informative and easy to follow. I have used your Face recognition and detection course and learned quite a lot. keep up the good work !

[danielfabriciofreita]

I need to create an application to know pedestrians, cars, bicycles, traffic lights and crosswalks using tensorflow and then convert the model to tensorflow lite using yolo. Is there a course that can teach me how to do this?

[consolenichecsn]

is there a way to do the annotation offline

[adewolesamuel]

Hello,
I hope this message finds you well. I would greatly appreciate a few minutes of your time for a constructive conversation regarding your Udemy course. If possible, would you be available for a quick call?
Thank you in advance for considering my request.