All Projects → eric612 → Caffe Yolov3 Windows

eric612 / Caffe Yolov3 Windows

Licence: other
A windows caffe implementation of YOLO detection network

Projects that are alternatives of or similar to Caffe Yolov3 Windows

Mobilenet Yolo
A caffe implementation of MobileNet-YOLO detection network
Stars: ✭ 825 (+292.86%)
Mutual labels:  caffe, yolo, yolov3
Alturos.yolo
C# Yolo Darknet Wrapper (real-time object detection)
Stars: ✭ 308 (+46.67%)
Mutual labels:  visual-studio, yolo, yolov3
Maskyolo caffe
YOLO V2 & V3 , YOLO Combined with RCNN and MaskRCNN
Stars: ✭ 101 (-51.9%)
Mutual labels:  caffe, yolo
Yolov5
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Stars: ✭ 19,914 (+9382.86%)
Mutual labels:  yolo, yolov3
Darknet2caffe
Convert darknet weights to caffemodel
Stars: ✭ 127 (-39.52%)
Mutual labels:  caffe, yolov3
Yolo Vehicle Counter
This project aims to count every vehicle (motorcycle, bus, car, cycle, truck, train) detected in the input video using YOLOv3 object-detection algorithm.
Stars: ✭ 28 (-86.67%)
Mutual labels:  yolo, yolov3
Tensornets
High level network definitions with pre-trained weights in TensorFlow
Stars: ✭ 982 (+367.62%)
Mutual labels:  yolo, yolov3
Yolo V3 Iou
YOLO3 动漫人脸检测 (Based on keras and tensorflow) 2019-1-19
Stars: ✭ 116 (-44.76%)
Mutual labels:  yolo, yolov3
Yolo annotation tool
Annotation tool for YOLO in opencv
Stars: ✭ 17 (-91.9%)
Mutual labels:  yolo, yolov3
Bmw Labeltool Lite
This repository provides you with a easy to use labeling tool for State-of-the-art Deep Learning training purposes.
Stars: ✭ 145 (-30.95%)
Mutual labels:  yolo, yolov3
Vehicle Detection
Compare FasterRCNN,Yolo,SSD model with the same dataset
Stars: ✭ 130 (-38.1%)
Mutual labels:  yolo, yolov3
Pine
🌲 Aimbot powered by real-time object detection with neural networks, GPU accelerated with Nvidia. Optimized for use with CS:GO.
Stars: ✭ 202 (-3.81%)
Mutual labels:  yolo, yolov3
Yolov3
YOLOv3 in PyTorch > ONNX > CoreML > TFLite
Stars: ✭ 8,159 (+3785.24%)
Mutual labels:  yolo, yolov3
Pytorch Caffe Darknet Convert
convert between pytorch, caffe prototxt/weights and darknet cfg/weights
Stars: ✭ 867 (+312.86%)
Mutual labels:  caffe, yolo
Imagenet
Trial on kaggle imagenet object localization by yolo v3 in google cloud
Stars: ✭ 56 (-73.33%)
Mutual labels:  yolo, yolov3
Tensorflow Yolo V3
Implementation of YOLO v3 object detector in Tensorflow (TF-Slim)
Stars: ✭ 862 (+310.48%)
Mutual labels:  yolo, yolov3
Mobilenet Yolo
MobileNetV2-YoloV3-Nano: 0.5BFlops 3MB HUAWEI P40: 6ms/img, YoloFace-500k:0.1Bflops 420KB🔥🔥🔥
Stars: ✭ 1,566 (+645.71%)
Mutual labels:  yolo, yolov3
Yolo Tf2
yolo(all versions) implementation in keras and tensorflow 2.4
Stars: ✭ 695 (+230.95%)
Mutual labels:  yolo, yolov3
Object Detection Api
Yolov3 Object Detection implemented as APIs, using TensorFlow and Flask
Stars: ✭ 177 (-15.71%)
Mutual labels:  yolo, yolov3
Yolo label
GUI for marking bounded boxes of objects in images for training neural network Yolo v3 and v2 https://github.com/AlexeyAB/darknet, https://github.com/pjreddie/darknet
Stars: ✭ 128 (-39.05%)
Mutual labels:  yolo, yolov3

caffe-yolov3-windows

A caffe implementation of MobileNet-YOLO detection network , first train on COCO trainval35k then fine-tune on 07+12 , test on VOC2007

Network mAP Resolution Download NetScope Inference time (GTX 1080) Inference time (i5-4440)
MobileNet-YOLOv3-Lite 0.747 320 caffemodel graph 6 ms 150 ms
MobileNet-YOLOv3-Lite 0.757 416 caffemodel graph 11 ms 280 ms
  • the benchmark of cpu performance on Tencent/ncnn framework
  • the deploy model was made by merge_bn.py , or you can try my custom version
  • bn_model download here

Linux Version

MobileNet-YOLO

Performance

Compare with YOLO , (IOU 0.5)

Network mAP Weight size Resolution NetScope
MobileNet-YOLOv3-Lite 34.0* 21.5 mb 320 graph
MobileNet-YOLOv3-Lite 37.3* 21.5 mb 416 graph
MobileNet-YOLOv3 40.3* 22.5 mb 416 graph
YOLOv3-Tiny 33.1 33.8 mb 416
  • (*) testdev-2015 server was closed , here use coco 2014 minival

Oringinal darknet-yolov3

Converter

test on coco_minival_lmdb (IOU 0.5)

Network mAP Resolution Download NetScope
yolov3 54.4 416 caffemodel graph
yolov3-spp 59.3 608 caffemodel graph

Other models

You can find non-depthwise convolution network here , Yolo-Model-Zoo

network mAP resolution macc param
PVA-YOLOv3 0.703 416 2.55G 4.72M
Pelee-YOLOv3 0.703 416 4.25G 3.85M

Configuring and Building Caffe

Requirements

  • Visual Studio 2013 or 2015
  • CMake 3.4 or higher (Visual Studio and Ninja generators are supported)
  • Anaconda

The build step was the same as MobileNet-SSD-windows

> cd $caffe_root
> script/build_win.cmd 

Mobilenet-YOLO Demo

> cd $caffe_root/
> examples\demo_yolo_lite.cmd

If load success , you can see the image window like this

alt tag

Trainning Prepare

Download lmdb

Unzip into $caffe_root/

Please check the path exist "$caffe_root\examples\VOC0712\VOC0712_trainval_lmdb"

Trainning Mobilenet-YOLOv3

> cd $caffe_root/
> examples\train_yolov3_lite.cmd

Reference

https://github.com/weiliu89/caffe/tree/ssd

https://pjreddie.com/darknet/yolo/

https://github.com/gklz1982/caffe-yolov2

https://github.com/duangenquan/YoloV2NCS

https://github.com/eric612/Vehicle-Detection

https://github.com/eric612/MobileNet-SSD-windows

License and Citation

Please cite MobileNet-YOLO in your publications if it helps your research:

@article{MobileNet-YOLO,
  Author = {eric612,Avisonic},
  Year = {2018}
}
Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].