Popular GitHub Repositories for Efficientdet Lite

Visualizer for neural network, deep learning and machine learning models

Google Brain AutoML

Tengine is a lite, high performance, modular inference engine for embedded device

? A lite C++ toolkit of 100+ Awesome AI models, support ORT, MNN, NCNN, TNN and TensorRT. ??

A LITE BERT FOR SELF-SUPERVISED LEARNING OF LANGUAGE REPRESENTATIONS, 海量中文预训练ALBERT模型

???YOLOv5-Lite: Evolved from yolov5 and the size of model is only 900+kb (int8) and 1.7M (fp16). Reach 15 FPS on the Raspberry Pi 4B~

Open-Source AI Camera. Empower any camera/CCTV with state-of-the-art AI, including facial recognition, person recognition(RE-ID) car detection, fall detection and more

???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

DELTA is a deep learning based natural language and speech processing platform. LF AI & DATA Projects: https://lfaidata.foundation/projects/delta/

Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch

MobileNetV1, MobileNetV2, VGG based SSD/SSD-lite implementation in Pytorch 1.0 / Pytorch 0.4. Out-of-box support for retraining on Open Images dataset. ONNX and Caffe2 support. Experiment Ideas like CoordConv.

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

TensorFlow Lite Samples on Unity

Lite & Super-fast re-ranking for your search & retrieval pipelines. Supports SoTA Listwise and Pairwise reranking based on LLMs and cross-encoders and more. Created by Prithivi Da, open for PRs & Collaborations.

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.

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.

Android TensorFlow Lite Machine Learning Example

A Lite Bert For Self-Supervised Learning Language Representations