ThorPham / License Plate Detection
This project using yolo3 to detection license plate in street
Stars: ✭ 93
Programming Languages
python
139335 projects - #7 most used programming language
Projects that are alternatives of or similar to License Plate Detection
Ros yolo as template matching
Run 3 scripts to (1) Synthesize images (by putting few template images onto backgrounds), (2) Train YOLOv3, and (3) Detect objects for: one image, images, video, webcam, or ROS topic.
Stars: ✭ 32 (-65.59%)
Mutual labels: yolov3
3d Bounding Boxes From Monocular Images
A two stage multi-modal loss model along with rigid body transformations to regress 3D bounding boxes
Stars: ✭ 24 (-74.19%)
Mutual labels: yolov3
Tensornets
High level network definitions with pre-trained weights in TensorFlow
Stars: ✭ 982 (+955.91%)
Mutual labels: yolov3
Copyright
Copyright is a simple application for updating all the copyright info in your Swift or Obj-C projects.
Stars: ✭ 5 (-94.62%)
Mutual labels: license
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 (-69.89%)
Mutual labels: yolov3
Imagenet
Trial on kaggle imagenet object localization by yolo v3 in google cloud
Stars: ✭ 56 (-39.78%)
Mutual labels: yolov3
Add Copyright
This is a Script to Automate adding the Copyright text to one or more source files Recursively.
Stars: ✭ 27 (-70.97%)
Mutual labels: license
Tensorflow Yolo V3
Implementation of YOLO v3 object detector in Tensorflow (TF-Slim)
Stars: ✭ 862 (+826.88%)
Mutual labels: yolov3
Licensir
An Elixir mix task that lists all the licenses used by your Mix project dependencies.
Stars: ✭ 48 (-48.39%)
Mutual labels: license
Initior
A command line application that let's you initialize your new projects the right way, replaces npm and yarn's init 🎆
Stars: ✭ 17 (-81.72%)
Mutual labels: license
Scancode Toolkit
🔎 ScanCode detects licenses, copyrights, package manifests & dependencies and more by scanning code ... to discover and inventory open source and third-party packages used in your code.
Stars: ✭ 1,134 (+1119.35%)
Mutual labels: license
Mobilenet Yolo
A caffe implementation of MobileNet-YOLO detection network
Stars: ✭ 825 (+787.1%)
Mutual labels: yolov3
Gh License
Scan your online repo, check if it is missing the license or install the Git Hooks
Stars: ✭ 35 (-62.37%)
Mutual labels: license
Lc
licensechecker (lc) a command line application which scans directories and identifies what software license things are under producing reports as either SPDX, CSV, JSON, XLSX or CLI Tabular output. Dual-licensed under MIT or the UNLICENSE.
Stars: ✭ 93 (+0%)
Mutual labels: license
Pytorch Onnx Tensorrt
A set of tool which would make your life easier with Tensorrt and Onnxruntime. This Repo is designed for YoloV3
Stars: ✭ 66 (-29.03%)
Mutual labels: yolov3
Onnx tflite yolov3
A Conversion tool to convert YOLO v3 Darknet weights to TF Lite model (YOLO v3 PyTorch > ONNX > TensorFlow > TF Lite), and to TensorRT (YOLO v3 Pytorch > ONNX > TensorRT).
Stars: ✭ 52 (-44.09%)
Mutual labels: yolov3
License-plate-detection
This project using yolov3 to detection license plate in street using repo : https://github.com/ultralytics/yolov3
Description
Python 3.7 or later with the following pip3 install -U -r requirements.txt packages:
numpytorch >= 1.0.0opencv-pythontqdm
Data
- Data training :3600 images (size 1000x2000)
- Data test : 900 images
How to training
- Start Training: Run train.py --cfg cfg/yolov3.cfg --img-size 416
Inference
-
Run
detect.pyto apply trained weights to an image, such ascar.jpgfrom thetestfolder. -
Link weight : https://drive.google.com/file/d/1hTH0Qj-fpxMnqnSzRTq64KPwkrPnGxsJ/view?usp=sharing
Some demo
Webcam
- Run
detect.pywithwebcam=Trueto show a live webcam feed.
Test
-
- Use
test.py --weights weights/weight.ptto test YOLOv3 weights.
- Use
mAP
- MAP YOLOv3-416 : 97
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].