eric612 / Caffe Yolov3 Windows
Licence: other
A windows caffe implementation of YOLO detection network
Stars: ✭ 210
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
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
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
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
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].