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tensorflow-lite
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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.
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
A fully open source cross-platform diary app written by flutter and rust.
TensorFlow Lite Samples on Unity
🔥 High-performance TensorFlow Lite library for React Native with GPU acceleration
Self-Created Tools to convert ONNX files (NCHW) to TensorFlow/TFLite/Keras format (NHWC). The purpose of this tool is to solve the massive Transpose extrapolation problem in onnx-tensorflow (onnx-tf). I don't need a Star, but give me a pull request.
Android TensorFlow Lite Machine Learning Example
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.
Real-time portrait segmentation for mobile devices
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.
Dual Edge TPU Adapter to use it on a system with single PCIe port on m.2 A/B/E/M slot