All Projects â†’ digitalbrain79 â†’ Pyyolo

digitalbrain79 / Pyyolo

Simple python wrapper for YOLO.

Programming Languages

python
139335 projects - #7 most used programming language
c
50402 projects - #5 most used programming language

Projects that are alternatives of or similar to Pyyolo

Yolo annotation tool
Annotation tool for YOLO in opencv
Stars: ✭ 17 (-86.72%)
Mutual labels:  yolo, darknet
Mobilenet Yolo
MobileNetV2-YoloV3-Nano: 0.5BFlops 3MB HUAWEI P40: 6ms/img, YoloFace-500k:0.1Bflops 420KB🔥🔥🔥
Stars: ✭ 1,566 (+1123.44%)
Mutual labels:  yolo, darknet
Pytorch Yolo2
Convert https://pjreddie.com/darknet/yolo/ into pytorch
Stars: ✭ 941 (+635.16%)
Mutual labels:  yolo, darknet
Openlabeling
Label images and video for Computer Vision applications
Stars: ✭ 706 (+451.56%)
Mutual labels:  yolo, darknet
Yolo Custom Object Detector
Making custom object detector using Yolo (Java and Python)
Stars: ✭ 84 (-34.37%)
Mutual labels:  yolo, darknet
Mobilenet Yolo
A caffe implementation of MobileNet-YOLO detection network
Stars: ✭ 825 (+544.53%)
Mutual labels:  yolo, darknet
Yolov2.pytorch
YOLOv2 algorithm reimplementation with pytorch
Stars: ✭ 31 (-75.78%)
Mutual labels:  yolo, darknet
Yolo3 4 Py
A Python wrapper on Darknet. Compatible with YOLO V3.
Stars: ✭ 504 (+293.75%)
Mutual labels:  yolo, darknet
Opendatacam
An open source tool to quantify the world
Stars: ✭ 1,214 (+848.44%)
Mutual labels:  yolo, darknet
Darknet ros
YOLO ROS: Real-Time Object Detection for ROS
Stars: ✭ 1,101 (+760.16%)
Mutual labels:  yolo, darknet
Ssds.pytorch
Repository for Single Shot MultiBox Detector and its variants, implemented with pytorch, python3.
Stars: ✭ 570 (+345.31%)
Mutual labels:  yolo, darknet
Easy Yolo
Yolo (Real time object detection) model training tutorial with deep learning neural networks
Stars: ✭ 98 (-23.44%)
Mutual labels:  yolo, darknet
Bmw Yolov4 Training Automation
This repository allows you to get started with training a state-of-the-art Deep Learning model with little to no configuration needed! You provide your labeled dataset or label your dataset using our BMW-LabelTool-Lite and you can start the training right away and monitor it in many different ways like TensorBoard or a custom REST API and GUI. NoCode training with YOLOv4 and YOLOV3 has never been so easy.
Stars: ✭ 533 (+316.41%)
Mutual labels:  yolo, darknet
Yolo2 Pytorch
YOLOv2 in PyTorch
Stars: ✭ 1,393 (+988.28%)
Mutual labels:  yolo, darknet
Tracking With Darkflow
Real-time people Multitracker using YOLO v2 and deep_sort with tensorflow
Stars: ✭ 515 (+302.34%)
Mutual labels:  yolo, darknet
Pytorch Caffe Darknet Convert
convert between pytorch, caffe prototxt/weights and darknet cfg/weights
Stars: ✭ 867 (+577.34%)
Mutual labels:  yolo, darknet
Tensorflow 2.x Yolov3
YOLOv3 implementation in TensorFlow 2.3.1
Stars: ✭ 300 (+134.38%)
Mutual labels:  yolo, darknet
Node Yolo
Node bindings for YOLO/Darknet image recognition library
Stars: ✭ 364 (+184.38%)
Mutual labels:  yolo, darknet
Yolo 9000
YOLO9000: Better, Faster, Stronger - Real-Time Object Detection. 9000 classes!
Stars: ✭ 1,057 (+725.78%)
Mutual labels:  yolo, darknet
Holocron
PyTorch implementations of recent Computer Vision tricks
Stars: ✭ 95 (-25.78%)
Mutual labels:  yolo, darknet

pyyolo

pyyolo is a simple wrapper for YOLO (compatible with YOLOv3).

Building

  1. git clone --recursive [email protected]:rayhou0710/pyyolo.git
  2. (optional) Set GPU=1 and CUDNN=1 in Makefile to use GPU.
  3. make
  4. rm -rf build
  5. python setup.py build (use setup_gpu.py for GPU)
  6. sudo python setup.py install (use setup_gpu.py for GPU)

Test

Edit parameters in example.py

python example.py

Result

{'right': 194, 'bottom': 353, 'top': 264, 'class': 'dog', 'prob': 0.8198755383491516, 'left': 71}
{'right': 594, 'bottom': 338, 'top': 109, 'class': 'horse', 'prob': 0.6106302738189697, 'left': 411}
{'right': 274, 'bottom': 381, 'top': 101, 'class': 'person', 'prob': 0.702547550201416, 'left': 184}
{'right': 583, 'bottom': 347, 'top': 137, 'class': 'sheep', 'prob': 0.7186083197593689, 'left': 387}
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].