There are 22 repositories under tensorflow-lite topic.
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.
🔥🔥🔥色情图片离线识别,基于TensorFlow实现。识别只需20ms,可断网测试,成功率99%,调用只要一行代码,从雅虎的开源项目open_nsfw移植,该模型文件可用于iOS、java、C++等平台
Faking your webcam background under GNU/Linux, now supports background blurring, animated background, colour map effect, hologram effect and on-demand processing.
The challenge projects for Inferencing machine learning models on iOS
An awesome list of TensorFlow Lite models, samples, tutorials, tools and learning resources.
TensorFlow Lite Samples on Unity
Android TensorFlow Lite Machine Learning Example
Real-time portrait segmentation for mobile devices
🔥 High-performance TensorFlow Lite library for React Native with GPU acceleration
GPU accelerated deep learning inference applications for RaspberryPi / JetsonNano / Linux PC using TensorflowLite GPUDelegate / TensorRT
State-of-the-art (ranked #1 Aug 2022) German Speech Recognition in 284 lines of C++. This is a 100% private 100% offline 100% free CLI tool.
DistilBERT / GPT-2 for on-device inference thanks to TensorFlow Lite with Android demo apps
Sample projects for TensorFlow Lite in C++ with delegates such as GPU, EdgeTPU, XNNPACK, NNAPI
This script converts the ONNX/OpenVINO IR model to Tensorflow's saved_model, tflite, h5, tfjs, tftrt(TensorRT), CoreML, EdgeTPU, ONNX and pb. PyTorch (NCHW) -> ONNX (NCHW) -> OpenVINO (NCHW) -> openvino2tensorflow -> Tensorflow/Keras (NHWC/NCHW) -> TFLite (NHWC/NCHW). And the conversion from .pb to saved_model and from saved_model to .pb and from .pb to .tflite and saved_model to .tflite and saved_model to onnx. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support.
Android On_device 1:1 Face Recognition And Alive Detect;1:N & M:N Face Search SDK 。 🧒 离线版设备端Android1:1人脸识别动作活体检测,静默活体检测 以及1:N M:N 人脸搜索 SDK 封装
Generate saved_model, tfjs, tf-trt, EdgeTPU, CoreML, quantized tflite, ONNX, OpenVINO, Myriad Inference Engine blob and .pb from .tflite. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support. Supports inverse quantization of INT8 quantization model.
Dual Edge TPU Adapter to use it on a system with single PCIe port on m.2 A/B/E/M slot
物体検出を用いてNARUTOの印(子~亥、壬、合掌)を検出するモデルとサンプルプログラムです。このリポジトリでは、YOLOXを使用しています(This is a model and sample program that detects NARUTO's hand sign using object detection. This repository use YOLOX.)
MNIST with TensorFlow Lite on Android
High performance, cross-platform machine learning for Unity Engine. Register at https://hub.natml.ai
The Qualcomm® AI Hub Models are a collection of state-of-the-art machine learning models optimized for performance (latency, memory etc.) and ready to deploy on Qualcomm® devices.
benchmark for embededded-ai deep learning inference engines, such as NCNN / TNN / MNN / TensorFlow Lite etc.
Pytorch to Keras/Tensorflow conversion made intuitive
This repository contains notebooks that show the usage of TensorFlow Lite for quantizing deep neural networks.
:dancer: Pose estimation for iOS and android using TensorFlow 2.0
Realtime face recognition with Flutter
The baseline project for inferencing various Pose Estimation tflite models with TFLiteSwift on iOS
GPU Accelerated TensorFlow Lite applications on Android NDK. Higher accuracy face detection, Age and gender estimation, Human pose estimation, Artistic style transfer