Train & Deploy TFLite Object Detection for Android (2025)

Train & Deploy TFLite Object Detection for Android (2025) free download

Train custom object detection models and deploy them in Android apps using TensorFlow Lite, Kotlin & Java - Realtime OD

Mobile AI is shifting from cloud to on-device. With TensorFlow Lite (TFLite) you can run real-time object detection directly on Android phones—no server, zero latency. This course gives you an end-to-end workflow to train, convert, and deploy custom models using Kotlin and Java.

What You’ll Master

• Data Collection & Annotation
  Capture images and label them with LabelImg, CVAT, or Roboflow to create high-quality datasets.

• Model Training in TensorFlow / YOLO / EfficientDet / SSD-MobileNet
  Hands-on Colab notebooks show you how to train from scratch or fine-tune pre-trained weights.

• TFLite Conversion & Optimization
  Quantize, prune, and add metadata for maximum FPS and minimum battery drain.

• Android Integration (CameraX + ML Model Binding)
  Build apps in Kotlin or Java that detect objects in both images and live camera streams.

• Using Pre-Trained Models
  Plug in ready-made YOLOv8-Nano, EfficientDet-Lite, or SSD-MobileNet with just a few lines of code.

  
  

Included Resources

• Production-ready Android templates (Kotlin & Java) worth $1,000+

• Re-usable model-conversion scripts and Colab notebooks

• Pre-annotated sample dataset to get you started fast

• Cheatsheets for common TFLite errors and performance tuning

Real-World Use-Cases You’ll Build

• Smart CCTV with intrusion alerts

• Industrial defect detection on assembly lines

• Crowd counting & retail analytics dashboards

• Prototype modules for self-driving or AR apps

Who Should Enroll?

• Android developers eager to add on-device AI (beginner to pro)

• ML engineers targeting mobile deployment and edge-AI optimization

• Makers, startup founders, or hobbyists who want to build vision-powered apps without a backend

What You Need

• Basic Android Studio familiarity (layouts, activities, Gradle)

• Light Python knowledge (all heavy lifting handled in the provided notebooks)

• A computer with 8 GB RAM—heavy training runs on free Google Colab GPUs

Course Format

• 1080p HD video lectures (updated for Android Studio 2025 & TensorFlow Lite 3.x)

• Mini-projects after each section to cement skills

• Lifetime access, Q&A support, and Udemy’s 30-day money-back guarantee

Ready to build fast, reliable object-detection apps that run entirely on Android devices?
Click Buy Now and start training & deploying your own TFLite models today!