Exploring Firebase MLKit on Android
summary
Firebase ML Kit packages Cloud Vision, TensorFlow Lite and Neural Networks into one mobile SDK and provides ready APIs for image labeling, face detection, barcode scanning, text and landmark recognition. Setup requires adding the Gradle dependency implementation 'com.google.firebase:firebase-ml-vision:16.0.0', creating detector options, feeding bitmap frames and handling results in callbacks. Offline SDK is available for basic detectors, cloud APIs handle heavier jobs, custom models (trained with TF or TF Lite) can be uploaded to Firebase console under Blaze. Accuracy sits around 80–90 percent in practice.
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chapters (20)
- 0:00Start
- 1:34Skills Required for the Machine Learning
- 3:48Google Vision Api
- 4:56What Is Ml Kit for Firebase
- 5:18Ml Use Cases
- 6:16How To Use Pre-Built Aps for Ml Kit in Your Mobile App
- 10:13Extra Dependencies
- 11:19Landscape Detection and Image Labeling
- 13:16Set Up the Image Detector Options
- 20:21How To Use Cloud Api'S
- 21:04Custom Model
- 25:40Train the Model
- 26:33Upload Your Custom Model
- 27:14Demos
- 33:52Extract Image Frame from the Video
- 34:25Ml Kit
- 43:09Create a Custom Model
- 44:29A Face Detection
- 45:11Can We Find any Ingredients and the Calorie of the Food
- 46:05Implement Ml Kit in Your Android Application
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