learning
The easy way to use Machine Learning Kit (Vision & NLP) in Flutter.
The easy way to use Machine Learning Kit in Flutter.
English project snapshot. Visit GitHub for the latest content.
The easy way to use Machine Learning Kit in Flutter.
Add dependency to your flutter project:
$ pub add learning
Optimization
For best performance (and to minimize application size), it's better to add dependency directly from each of sub-package you want to use in your application.
Learning consists of 13 different sub-packages that we can add separately based on our application needs. Please reference to each link below to learn more about the usage of each learning package.
| Vision | Version | Links | Example |
|---|---|---|---|
learning_text_recognition |
^0.0.4 |
Pub.dev Github |
Example text_recognition.apk |
learning_face_detection |
^0.0.3 |
Pub.dev Github |
Example face_detection.apk |
learning_pose_detection |
^0.0.2 |
Pub.dev Github |
Example pose_detection.apk |
learning_selfie_segmentation |
^0.0.3 |
Pub.dev Github |
Example selfie_segmentation.apk |
learning_image_labeling |
^0.0.2 |
Pub.dev Github |
Example image_labeling.apk |
learning_barcode_scanning |
^0.0.3 |
Pub.dev Github |
Example barcode_scanning.apk |
learning_object_detection |
^0.0.2 |
Pub.dev Github |
Example object_detection.apk |
learning_digital_ink_recognition |
^0.0.2 |
Pub.dev Github |
Example digital_ink_recognition.apk |
| NLP | Version | Links | Example |
|---|---|---|---|
learning_language |
^0.0.4 |
Pub.dev Github |
Example language.apk |
learning_translate |
^0.0.4 |
Pub.dev Github |
Example translate.apk |
learning_entity_extraction |
^0.0.3 |
Pub.dev Github |
Example entity_extraction.apk |
learning_smart_reply |
^0.0.3 |
Pub.dev Github |
Example |
| Helper | Version | Links |
|---|---|---|
learning_input_image |
^0.0.6+2 |
Pub.dev Github |
You can learn more from example project here.
Dependency list 15 items
{"sdk":"flutter"}^0.0.6+2^0.0.3^0.0.2^0.0.3^0.0.3^0.0.2^0.0.4^0.0.2^0.0.2^0.0.3^0.0.3^0.0.4^0.0.4{"sdk":"flutter"}Start with your use case, compare repository activity, and check the original project before adopting it.
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