CVT, a Computer Vision Toolkit.
-
Updated
Aug 24, 2022 - C
CVT, a Computer Vision Toolkit.
A header-only neural network library for microcontrollers, with partial bare-metal & native-os support.
Winner solution of mobile AI (CVPRW 2021).
FrostNet: Towards Quantization-Aware Network Architecture Search
Quantization Aware Training
ATtiny85 arduino example, running an RNN MNIST model via the (internal) 512-Byte EEPROM with ~95% accuracy
将端上模型部署过程中,常见的问题以及解决办法记录并汇总,希望能给其他人带来一点帮助。
Silicon-proven INT8 systolic NPU (8×8 MAC array) taped out on SkyWater 130nm via LibreLane. Features a custom 32-bit ISA, UART–APB host interface, and fused streaming datapath. Validated on chest X-ray pneumonia detection. Silicon Sprint 2026 — AUC.
A tool-calling layer, not a language model — your schemas in, validated calls out, at 48M parameters. Malformed JSON, invented parameter names, and undeclared tools are structurally unreachable on any catalog. Adapt it to your own catalog; 11 negative results included.
Garuda: CVXIF coprocessor optimizing batch-1 attention microkernels with 7.5-9× lower p99 latency. RISC-V INT8 MAC accelerator for transformer inference.
Tooling for dataset captioning, model merging and quantizing.
VB.NET api wrapper for llm-inference chatllm.cpp
C# api wrapper for llm-inference chatllm.cpp
Generating tensorrt model using onnx
Corrects your grammar in 5 languages directly in your browser. Powered by an open-source AI model.
Python ML for training a custom on-device cry model (knowledge-distilled from YAMNet, INT8, deployed on ESP32-S3)
Central Proteus simulation and Git submodule tracker for the STM32 Smart Car network.
TinyML project. This system monitors your room or surrounding with an onboard microphone of Arduino nano BLE sense. Still Under Developement
PyTorch-to-ONNX-to-C++ object detection engine for low-latency automotive and robotics edge inference using YOLO, MLflow, ONNX Runtime, OpenCV, CMake, INT8 quantization, and benchmarking.
To associate your repository with the int8-quantization topic, visit your repo's landing page and select "manage topics."