#Tensorflow-lite
Showing 37 of 37 repositories tagged #tensorflow-lite, ranked by stars
Visualizer for neural network, deep learning and machine learning models
A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.
A fully open source cross-platform diary app written by flutter and rust.
DELTA is a deep learning based natural language and speech processing platform. LF AI & DATA Projects: https://lfaidata.foundation/projects/delta/
An awesome list of TensorFlow Lite models, samples, tutorials, tools and learning resources.
The challenge projects for Inferencing machine learning models on iOS
🧬 High-performance TensorFlow Lite library for React Native with GPU acceleration
Qualcomm® AI Hub Models is our collection of state-of-the-art machine learning models optimized for performance (latency, memory etc.) and ready to deploy on Qualcomm® devices.
A tool for converting ONNX files to LiteRT/TFLite/TensorFlow, PyTorch native code (nn.Module), TorchScript (.pt), state_dict (.pt), Exported Program (.pt2), and Dynamo ONNX. It also supports direct conversion from LiteRT to PyTorch.
TensorFlow Lite Samples on Unity
Android TensorFlow Lite Machine Learning Example
Real-time portrait segmentation for mobile devices
The Qualcomm® AI Hub apps are a collection of state-of-the-art machine learning models optimized for performance (latency, memory etc.) and ready to deploy on Qualcomm® devices.
Go binding for TensorFlow Lite
an architecture for neural network inference in real-time audio applications
NNtrainer is Software Framework for Training and Inferencing Neural Network Models on Devices.
benchmark for embededded-ai deep learning inference engines, such as NCNN / TNN / MNN / TensorFlow Lite etc.
Neural network inference template for real-time cricital audio environments - presented at ADC23
Real-time semantic image segmentation on mobile devices
Demo for training a convolutional neural network to classify words and deploy the model to a Raspberry Pi using TensorFlow Lite.
Learn how to code your own neural network in Python, then deploy it in an Image Classification App using TensorFlow Lite.
Energy Management Using Real-Time Non-Intrusive Load Monitoring
The official codebase for the Real-Time Video Super-Resolution Challenge in Mobile AI (MAI) Workshop@ CVPR 2022 & Advances in Image Manipulation (AIM) Workshop @ ECCV 2022
Examples of Tensorflow Lite on Android
Expose tensorflow-lite models via a rest API using FastAPI
📲 Transformers android examples (Tensorflow Lite & Pytorch Mobile)
Age + Gender Estimation on Android with TensorFlow Lite
How to create Selfie2Anime from tflite model to Android.
A repository demonstrating all that's new in Android 11 for ML and how you could try it out for your own use-cases
Flutter App real-time object detection with Tensorflow Lite
GPU tensor framework with support for running ONNX models
The TinyML "Hello World" sine wave model on Arduino Uno v3
Preprocessing and classify EMG signals, using Tensorflow and Tensorflow Lite to deploy an AI model in a ESP32C3
Converting the ONNX model representation to the TensorFlow Lite representation.
All-in-one Android security suite — deepfake detection, antivirus, Tor VPN, breach monitoring, phishing scanner, and 50+ security tools. On-device, no API keys, open source.
Example project showing how we can compare TensorFlow and TensorFlow Lite models
The AI model recognizes burned wounds, determines their severity, and shows the user the severity of the wounds and the first aid manual.