zhreshold / Mxnet Yolo
Licence: mit
YOLO: You only look once real-time object detector
Stars: ✭ 240
Programming Languages
python
139335 projects - #7 most used programming language
Projects that are alternatives of or similar to Mxnet Yolo
Tracking With Darkflow
Real-time people Multitracker using YOLO v2 and deep_sort with tensorflow
Stars: ✭ 515 (+114.58%)
Mutual labels: object-detection, yolo, yolo2
Alturos.yolo
C# Yolo Darknet Wrapper (real-time object detection)
Stars: ✭ 308 (+28.33%)
Mutual labels: object-detection, yolo, yolo2
Satellite Image Object Detection
YOLO/YOLOv2 inspired deep network for object detection on satellite images (Tensorflow, Numpy, Pandas).
Stars: ✭ 115 (-52.08%)
Mutual labels: object-detection, yolo, yolo2
Yolo Tf
TensorFlow implementation of the YOLO (You Only Look Once)
Stars: ✭ 200 (-16.67%)
Mutual labels: object-detection, yolo, yolo2
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 (-46.67%)
Mutual labels: object-detection, yolo
Yolo V3 Iou
YOLO3 动漫人脸检测 (Based on keras and tensorflow) 2019-1-19
Stars: ✭ 116 (-51.67%)
Mutual labels: object-detection, yolo
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 (-39.58%)
Mutual labels: object-detection, yolo
Deepstream Yolo
NVIDIA DeepStream SDK 5.1 configuration for YOLO models
Stars: ✭ 166 (-30.83%)
Mutual labels: object-detection, yolo
Pytorch cpp
Deep Learning sample programs using PyTorch in C++
Stars: ✭ 114 (-52.5%)
Mutual labels: object-detection, yolo
Simrdwn
Rapid satellite imagery object detection
Stars: ✭ 159 (-33.75%)
Mutual labels: object-detection, yolo
Yoloncs
YOLO object detector for Movidius Neural Compute Stick (NCS)
Stars: ✭ 176 (-26.67%)
Mutual labels: object-detection, yolo
Caffe2 Ios
Caffe2 on iOS Real-time Demo. Test with Your Own Model and Photos.
Stars: ✭ 221 (-7.92%)
Mutual labels: object-detection, yolo
Yolov3 Tf2
YoloV3 Implemented in Tensorflow 2.0
Stars: ✭ 2,327 (+869.58%)
Mutual labels: object-detection, yolo
Tf2 Yolov4
A TensorFlow 2.0 implementation of YOLOv4: Optimal Speed and Accuracy of Object Detection
Stars: ✭ 133 (-44.58%)
Mutual labels: object-detection, yolo
Yolo mark
GUI for marking bounded boxes of objects in images for training neural network Yolo v3 and v2
Stars: ✭ 1,624 (+576.67%)
Mutual labels: object-detection, yolo
Map
mean Average Precision - This code evaluates the performance of your neural net for object recognition.
Stars: ✭ 2,324 (+868.33%)
Mutual labels: object-detection, yolo
Object Detection Api
Yolov3 Object Detection implemented as APIs, using TensorFlow and Flask
Stars: ✭ 177 (-26.25%)
Mutual labels: object-detection, yolo
Viseron
Self-hosted NVR with object detection
Stars: ✭ 192 (-20%)
Mutual labels: object-detection, yolo
Yolov5
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Stars: ✭ 19,914 (+8197.5%)
Mutual labels: object-detection, yolo
Mobilenet Yolo
MobileNetV2-YoloV3-Nano: 0.5BFlops 3MB HUAWEI P40: 6ms/img, YoloFace-500k:0.1Bflops 420KB🔥🔥🔥
Stars: ✭ 1,566 (+552.5%)
Mutual labels: object-detection, yolo
YOLO-v2: Real-Time Object Detection
Still under development. 71 mAP(darknet) and 74mAP(resnet50) on VOC2007 achieved so far.
This is a pre-released version.
What's new
This repo is now deprecated, I am migrating to the latest Gluon-CV which is more user friendly and has a lot more algorithms in development.
-
Pretrained YOLOv3 models which achiveve 81%+ mAP on VOC and near 37% mAP on COCO: Model Zoo.
-
Object Detection model tutorials.
This repo will not receive active development, however, you can continue use it with the mxnet 1.1.0(probably 1.2.0).
Disclaimer
This is a re-implementation of original yolo v2 which is based on darknet. The arXiv paper is available here.
Demo
Getting started
- Build from source, this is required because this example is not merged, some custom operators are not presented in official MXNet. Instructions
- Install required packages:
cv2
,matplotlib
Try the demo
- Download the pretrained model(darknet as backbone), or this model(resnet50 as backbone) and extract to
model/
directory. - Run
# cd /path/to/mxnet-yolo
python demo.py --cpu
# available options
python demo.py -h
Train the model
- Grab a pretrained model, e.g.
darknet19
- (optional) Grab a pretrained resnet50 model,
resnet-50-0000.params
,resnet-50-symbol.json
, this will produce slightly better mAP thandarknet
in my experiments. - Download PASCAL VOC dataset.
cd /path/to/where_you_store_datasets/
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtrainval_06-Nov-2007.tar
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtest_06-Nov-2007.tar
# Extract the data.
tar -xvf VOCtrainval_11-May-2012.tar
tar -xvf VOCtrainval_06-Nov-2007.tar
tar -xvf VOCtest_06-Nov-2007.tar
ln -s /path/to/VOCdevkit /path/to/mxnet-yolo/data/VOCdevkit
- Create packed binary file for faster training
# cd /path/to/mxnet-ssd
bash tools/prepare_pascal.sh
# or if you are using windows
python tools/prepare_dataset.py --dataset pascal --year 2007,2012 --set trainval --target ./data/train.lst
python tools/prepare_dataset.py --dataset pascal --year 2007 --set test --target ./data/val.lst --shuffle False
- Start training
python train.py --gpus 0,1,2,3 --epoch 0
# choose different networks, such as resnet50_yolo
python train.py --gpus 0,1,2,3 --network resnet50_yolo --data-shape 416 --pretrained model/resnet-50 --epoch 0
# see advanced arguments for training
python train.py -h
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].