TensorFlow Lite is a set of tools that help convert and optimize TensorFlow models to run on mobile and edge devices. It's currently running on more than 4 billion devices! With TensorFlow 2.x, you can train a model with tf.Keras, easily convert a model to .tflite and deploy it; or you can download a pretrained TensorFlow Lite model from the model zoo.
This is an awesome list of TensorFlow Lite models with sample apps, helpful tools and learning resources -
Please submit a PR if you would like to contribute and follow the guidelines here.
Here are the new features and tools of TensorFlow Lite:
Here are the TensorFlow Lite models with app / device implementations, and references. Note: pretrained TensorFlow Lite models from MediaPipe are included, which you can implement with or without MediaPipe.
| Task | Model | App | Reference | Source | | ------------------------------- |-------------------------------------------------------------------------------------------------------------------------------------------------------------------| ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------| | Classification | MobileNetV1 (download) | Android | iOS | Raspberry Pi | Overview | tensorflow.org | | Classification | MobileNetV2 | Recognize Flowers on Android Codelab | Android | TensorFlow team | | Classification | MobileNetV2 | Skin Lesion Detection Android | Community | | Classification | EfficientNet-Lite0 (download) | Icon Classifier Colab & Android | tutorial 1 | tutorial 2 | Community | | Object detection | Quantized COCO SSD MobileNet v1 (download) | Android | iOS | Overview | tensorflow.org | | Object detection | YOLO | Flutter | Paper | Community | | Object detection | MobileNetV2 SSD (download) | Reference | MediaPipe | | Object detection | MobileDet (Paper) | Blog post (includes the TFLite conversion process) | MobileDet is from University of Wisconsin-Madison and Google and the blog post is from the Community | | License Plate detection | SSD MobileNet (download) | Flutter | Community | | Face detection | BlazeFace (download) | Paper | MediaPipe | | Hand detection & tracking | Palm detection & hand landmarks (download) | Blog post | Model card | MediaPipe | | Pose estimation | Posenet (download) | Android | iOS | Overview | tensorflow.org | | Segmentation | DeepLab V3 (download) | Android & iOS | Overview | Flutter Image | Realtime | Paper | tf.org & Community | | Segmentation | Different variants of DeepLab V3 models | Models on TF Hub with Colab Notebooks | Community | | Hair Segmentation | Download | Paper | MediaPipe | | Style transfer | Arbitrary image stylization | Overview | Android | Flutter | tf.org & Community | | Style transfer | Better-quality style transfer models in .tflite | Models on TF Hub with Colab Notebooks | Community | | GANs | U-GAT-IT (Selfie2Anime) | Project repo | Android | Tutorial | Community | | GANs | White-box CartoonGAN (download) | Project repo | Android | Tutorial | Community | | Video Style Transfer | Download: Dynamic range models) | Android | Tutorial | Community | | Segmentation & Style transfer | DeepLabV3 & Style Transfer models | Project repo | Android | Tutorial | Community | | Low-light image enhancement | Models on TF Hub | Project repo | Original Paper | | Community | | Text Detection | CRAFT Text Detector (Paper) |Download | Project Repository | Blog1-Conversion to TFLite | Blog2-EAST vs CRAFT | Models on TF Hub | Android (Coming Soon) | Community | | Text Detection | EAST Text Detector (Paper) |Models on TF Hub | Conversion and Inference Notebook | Community | | Image Extrapolation | Models on TF Hub | Colab Notebook | Original Paper | Community | | OCR |Models on TF Hub | Project Repository | Community
| Task | Model | Sample apps | Source | | ------------------- |---------------------------------------------------------------------------------------------------------------------------------| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------ | | Question & Answer | DistilBERT | Android | Hugging Face | | Text Generation | GPT-2 / DistilGPT2 | Android | Hugging Face | | Text Classification | Download | Android |iOS | Flutter | tf.org & Community |
| Task | Model | App | Reference | Source | | ------------------ |------------------------------------| ------------------------------------------------------------------------------------- | ------------ | | Speech Recognition | DeepSpeech | Reference | Mozilla | | Speech Synthesis | Tacotron-2, FastSpeech2, MB-Melgan | Android | TensorSpeech | | Speech Synthesis(TTS) | Tacotron2, FastSpeech2, MelGAN, MB-MelGAN, HiFi-GAN, Parallel WaveGAN | Inference Notebook | Project Repository | Community |
These are the TensorFlow Lite models that could be implemented in apps and things:
These are TensorFlow models that could be converted to .tflite and then implemented in apps and things:
ML Kit is a mobile SDK that brings Google's ML expertise to mobile developers.
Interested but not sure how to get started? Here are some learning resources that will help you whether you are a beginner or a practitioner in the field for a while.