Run Model on Stream Frame:

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Object Detection App With Flutter and TensorFlow Lite

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  Let’s learn how to build a flutter app that detects objects on a live camera. In this blog, we shall learn how to build an app that can detect Objects, and using AI and Deep Learning it can determine what the object is.  Tflite  provides us access to  TensorFlow Lite  . TensorFlow Lite  is an open-source deep learning framework for on-device inference. To integrate  tflite  into our flutter app, we need to install  tflite  package and we need two files  model.tflite  and  labels.txt  .  model.tflite   is the trained model and  labels.txt  the file is a text file containing all the labels. Many websites provide us facility to train our model with our dataset and deploy them on  TensorFlow Lite  and we can directly get these two files from there. You can read my blog on  Object  Detection App with Flutter and TensorFlow Lite  to trains your model with your own dataset.
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Android Configuration

  Android Configuration: Change the minimum Android SDK version to 21 (or higher) in your  android/app/build.gradle  file. minSdkVersion 21 In  android/app/build.gradle , add the following setting in  android  block. aaptOptions { noCompress 'tflite' noCompress 'lite' } Add model and label files in the assets folder, also add them in  pubspec.yaml
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Model

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