Python ML library for person fall detection. Intended for IoT deployments with on-device inference and on-device transfer learning.
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Updated
Oct 5, 2021 - Jupyter Notebook
Python ML library for person fall detection. Intended for IoT deployments with on-device inference and on-device transfer learning.
2022 D.Com 동아리 대항전 Team "AEye" - Android Native App 개발을 위한 Repo.
Firebase MLkit vision demo app
SponsorMe is a project to help provide access to digital tools for learning, powered by on-device machine learning, innovation and willingness, to those people that have limited access to technology due to demographics, disabilities, economy or other multiple reasons.
A python framework for designing high-performance Computer Vision pipelines at the Edge. Supports Coral Edge TPU, Raspberry Pi Camera, and more.
On-device LLM inference powered by x-bit quantization
BLOCKSET: Efficient out of core tree ensemble inference
A Google Photos alternative, where your pictures never leave your phone! Classification happens on-device, leveraging pre-trained models. Available for Android and iOS.
Object detection inference with Roboflow Train models on NVIDIA Jetson devices.
Source code for my blog post series "On-device training with Core ML"
Binary Neural Network on IceStick FPGA.
AubAI brings you on-device gen-AI capabilities, including offline text generation and more, directly within your app.
This is a web demo for camera-based PPG sensing (rPPG).
[ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices
Official PyTorch implementation of "EdgeSAM: Prompt-In-the-Loop Distillation for On-Device Deployment of SAM"
Android Voice Activity Detection (VAD) library. Supports WebRTC VAD GMM, Silero VAD DNN, Yamnet VAD DNN models.
Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement (NeurIPS 2020)
TinyChatEngine: On-Device LLM Inference Library
[ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices
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