There are 11 repositories under ncnn topic.
ncnn is a high-performance neural network inference framework optimized for the mobile platform
超轻量级中文ocr,支持竖排文字识别, 支持ncnn、mnn、tnn推理 ( dbnet(1.8M) + crnn(2.5M) + anglenet(378KB)) 总模型仅4.7M
Video, Image and GIF upscale/enlarge(Super-Resolution) and Video frame interpolation. Achieved with Waifu2x, Real-ESRGAN, Real-CUGAN, SRMD, RealSR, Anime4K, RIFE, CAIN, DAIN, and ACNet.
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
💎1MB lightweight face detection model (1MB轻量级人脸检测模型)
A lossless video/GIF/image upscaler achieved with waifu2x, Anime4K, SRMD and RealSR. Started in Hack the Valley 2, 2018.
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.
Deep Learning API and Server in C++14 support for Caffe, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE
waifu2x converter ncnn version, runs fast on intel / amd / nvidia / apple-silicon GPU with vulkan
MobileNetV2-YoloV3-Nano: 0.5BFlops 3MB HUAWEI P40: 6ms/img, YoloFace-500k:0.1Bflops 420KB:fire::fire::fire:
🛠 A lite C++ toolkit of awesome AI models with ONNXRuntime, NCNN, MNN and TNN. YOLOX, YOLOP, MODNet, YOLOR, NanoDet, YOLOX, SCRFD, YOLOX . MNN, NCNN, TNN, ONNXRuntime, CPU/GPU.
🍅🍅🍅YOLOv5-Lite: lighter, faster and easier to deploy. Evolved from yolov5 and the size of model is only 930+kb (int8) and 1.7M (fp16). It can reach 10+ FPS on the Raspberry Pi 4B when the input size is 320×320~
🍅 Deploy ncnn on mobile phones. Support Android and iOS. 移动端ncnn部署,支持Android与iOS。
Add bisenetv2. My implementation of BiSeNet
OpenMMLab Model Deployment Framework
RealSR super resolution implemented with ncnn library
PFLD pytorch Implementation
mobilev2-yolov5s剪枝、蒸馏,支持ncnn,tensorRT部署。ultra-light but better performence!
Generate a quantization parameter file for ncnn framework int8 inference
Flowframes Windows GUI for video interpolation using DAIN (NCNN) or RIFE (CUDA/NCNN)
YOLOv5 Series Multi-backbone(TPH-YOLOv5, Ghostnet, ShuffleNetv2, Mobilenetv3Small, EfficientNetLite, PP-LCNet, SwinTransformer YOLO), Module(CBAM, DCN), Pruning (EagleEye, Network Slimming) and Quantization (MQBench) Compression Tool Box.
😎 A Collection of Awesome NCNN-based Projects
yolort is a runtime stack for yolov5 on specialized accelerators such as libtorch, onnxruntime, tensorrt, tvm and ncnn.
Realtime Face Detection and Head pose estimation on Windows、Ubuntu、Mac、Android and iOS
DAIN, Depth-Aware Video Frame Interpolation implemented with ncnn library
RIFE, Real-Time Intermediate Flow Estimation for Video Frame Interpolation implemented with ncnn library
real-cugan converter ncnn version, runs fast on intel / amd / nvidia / apple-silicon GPU with vulkan
yoloface大礼包 使用pytroch实现的基于yolov3的轻量级人脸检测(包含关键点)
基于insightface训练mobilefacenet的相关步骤及ncnn转换流程
SRMD super resolution implemented with ncnn library