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ml kit image labeler
MLKIT Image Labeler #
Plugin which provides native ML Kit ImageLabeler API
Requirements #
Android
Set minSdkVersion 21 in android/app/build.gradle
Add <meta-data android:name="com.google.mlkit.vision.DEPENDENCIES" android:value="ica" /> in android/src/main/AndroidManifest.xml
Note: In case you are using multiple models separate them with commas android:value="ica,ocr"
Set ext.kotlin_version = '1.6.10' in android/build.gradle
App size impact: 700KB(Using Unbundled Model, downloads model using Google play services for the first time when app launches), refer here
iOS
Minimum iOS Deployment Target: 10.0
Xcode 12.5.1 or greater.
ML Kit only supports 64-bit architectures (x86_64 and arm64). Check this list to see if your device has the required device capabilities.
Since ML Kit does not support 32-bit architectures (i386 and armv7) Read more, you need to exclude amrv7 architectures in Xcode in order to build iOS, refer here
Usage #
// Create an Instance of [MlKitImageLabeler]
final imageLabeler = MlKitImageLabeler();
//...
// Pick Image using image picker
//...
// Call `processImage()` and pass params as `InputImage` [check example for more info]
final labels = await imageLabeler.processImage(
InputImage.fromFilePath(image.path));
String predictedLabels = '';
// Iterate over Labels
for (var label in labels) {
predictedLabels +=
'\n${label.label} ${(label.confidence * 100).toStringAsPrecision(2)}%';
}
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This plugin is basically a trimmed down version of google_ml_kit. As google_ml_kit contains all the NLP and Vison APIs, the App size increases drastically. So, I created this plugin and now the example app's fat apk is of 17MB and splitted apks are 6MB.
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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