Train object detection models and learn to perform Object Detection in Android with both Images and Live Camera Footage.
Get the Complete Course "Train Object Detection Models & build Android Applications"
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If you want to train custom object detection models for Android then welcome to this course.
In this course, you will learn to
1: Train your custom object detection models for Android and IOS
2: Use those models in Android (Java/Kotlin) with images and live camera footage
3: 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
1: Collect datasets for training object detection models
2: Annotate datasets using different tools
3: Train object detection models on custom datasets for Android and IOS ( TensorFlow object detection )
4: Convert object detection models into tflite / Tensorflow lite format
5: Use those converted models in Android (Java/Kotlin) with images and live camera footage
6: 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
1: You can take complete android (Java/Kotlin) application codes from course resources
2: Replace the object detection model with your custom model
3: 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
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