Chinese license plate recognition

Related tags

Deep LearningAgentCLPR
Overview

AgentCLPR

GitHub forks GitHub Repo stars Pypi Downloads GitHub release (latest by date including pre-releases) GitHub

简介

车牌识别效果

  • 支持多种车牌的检测和识别（其中单层车牌识别效果较好）：

    • 单层车牌：

        [[[[373, 282], [69, 284], [73, 188], [377, 185]], ['苏E05EV8', 0.9923506379127502]]]
  [[[[393, 278], [318, 279], [318, 257], [393, 255]], ['VA30093', 0.7386096119880676]]]
  [[[[[487, 366], [359, 372], [361, 331], [488, 324]], ['皖K66666', 0.9409016370773315]]]]
  [[[[304, 500], [198, 498], [199, 467], [305, 468]], ['鲁QF02599', 0.995299220085144]]]
  [[[[309, 219], [162, 223], [160, 181], [306, 177]], ['使198476', 0.9938704371452332]]]
  [[[[957, 918], [772, 920], [771, 862], [956, 860]], ['陕A06725D', 0.9791222810745239]]]

    • 双层车牌：

        [[[[399, 298], [256, 301], [256, 232], [400, 230]], ['浙G66666', 0.8870148431461757]]]
  [[[[398, 308], [228, 305], [227, 227], [398, 230]], ['陕A00087', 0.9578166644088313]]]
  [[[[352, 234], [190, 244], [190, 171], [352, 161]], ['宁A66666', 0.9958433652812175]]]

快速使用

  • 快速安装

    # 安装 AgentCLPR
$ pip install agentclpr

# 根据设备平台安装合适版本的 ONNXRuntime

# CPU 版本（推荐非 win10 系统，无 CUDA 支持的设备安装）
$ pip install onnxruntime

# GPU 版本（推荐有 CUDA 支持的设备安装）
$ pip install onnxruntime-gpu

# DirectML 版本（推荐 win10 系统的设备安装，可实现通用的显卡加速）
$ pip install onnxruntime-directml

# 更多版本的安装详情请参考 ONNXRuntime 官网

  • 简单调用：

    # 导入 CLPSystem 模块
from agentclpr import CLPSystem

# 初始化车牌识别模型
clp = CLPSystem()

# 使用模型对图像进行车牌识别
results = clp('test.jpg')

  • 服务器部署：

    • 启动 AgentCLPR Server 服务

      $ agentclpr server

    • Python 调用

      import cv2
import json
import base64
import requests

# 图片 Base64 编码
def cv2_to_base64(image):
    data = cv2.imencode('.jpg', image)[1]
    image_base64 = base64.b64encode(data.tobytes()).decode('UTF-8')
    return image_base64

# 读取图片
image = cv2.imread('test.jpg')
image_base64 = cv2_to_base64(image)

# 构建请求数据
data = {
    'image': image_base64
}

# 发送请求
url = "http://127.0.0.1:5000/ocr"
r = requests.post(url=url, data=json.dumps(data))

# 打印预测结果
print(r.json())

Contact us

Email : [email protected]
QQ Group : 1005109853

You might also like...
EmoTag helps you train emotion detection model for Chinese audios

emoTag emoTag helps you train emotion detection model for Chinese audios. Environment pip install -r requirement.txt Data We used Emotional Speech Dat

_zza 4 Sep 7, 2022
Code for the paper
Code for the paper "MASTER: Multi-Aspect Non-local Network for Scene Text Recognition" (Pattern Recognition 2021)

MASTER-PyTorch PyTorch reimplementation of "MASTER: Multi-Aspect Non-local Network for Scene Text Recognition" (Pattern Recognition 2021). This projec

Wenwen Yu 255 Dec 29, 2022
Face-Recognition-Attendence-System - This face recognition Attendence system using Python

Face-Recognition-Attendence-System I have developed this face recognition Attend

Riya Gupta 4 May 10, 2022
The world's simplest facial recognition api for Python and the command line
The world's simplest facial recognition api for Python and the command line

Face Recognition You can also read a translated version of this file in Chinese 简体中文版 or in Korean 한국어 or in Japanese 日本語. Recognize and manipulate fa

Adam Geitgey 46.9k Jan 3, 2023
PyTorch implementation of
PyTorch implementation of "Conformer: Convolution-augmented Transformer for Speech Recognition" (INTERSPEECH 2020)

PyTorch implementation of Conformer: Convolution-augmented Transformer for Speech Recognition. Transformer models are good at capturing content-based

Soohwan Kim 565 Jan 4, 2023
TDN: Temporal Difference Networks for Efficient Action Recognition
TDN: Temporal Difference Networks for Efficient Action Recognition

TDN: Temporal Difference Networks for Efficient Action Recognition Overview We release the PyTorch code of the TDN(Temporal Difference Networks).

Multimedia Computing Group, Nanjing University 326 Dec 13, 2022
Bottleneck Transformers for Visual Recognition
Bottleneck Transformers for Visual Recognition

Bottleneck Transformers for Visual Recognition Experiments Model Params (M) Acc (%) ResNet50 baseline (ref) 23.5M 93.62 BoTNet-50 18.8M 95.11% BoTNet-

Myeongjun Kim 236 Jan 3, 2023
A PyTorch Toolbox for Face Recognition
A PyTorch Toolbox for Face Recognition

FaceX-Zoo FaceX-Zoo is a PyTorch toolbox for face recognition. It provides a training module with various supervisory heads and backbones towards stat

JDAI-CV 1.6k Jan 6, 2023
AI grand challenge 2020 Repo (Speech Recognition Track)
AI grand challenge 2020 Repo (Speech Recognition Track)

KorBERT를 활용한 한국어 텍스트 기반 위협 상황인지(2020 인공지능 그랜드 챌린지) 본 프로젝트는 ETRI에서 제공된 한국어 korBERT 모델을 활용하여 폭력 기반 한국어 텍스트를 분류하는 다양한 분류 모델들을 제공합니다. 본 개발자들이 참여한 2020 인공지

Young-Seok Choi 23 Jan 25, 2022
Owner
AgentMaker
Focus on deep learning tools
AgentMaker
GitHub Repository
Practical tutorials and labs for TensorFlow used by Nvidia, FFN, CNN, RNN, Kaggle, AE

TensorFlow Tutorial - used by Nvidia Learn TensorFlow from scratch by examples and visualizations with interactive jupyter notebooks. Learn to compete

Alexander R Johansen 1.9k Dec 19, 2022
PyTorch Language Model for 1-Billion Word (LM1B / GBW) Dataset

PyTorch Large-Scale Language Model A Large-Scale PyTorch Language Model trained on the 1-Billion Word (LM1B) / (GBW) dataset Latest Results 39.98 Perp

Ryan Spring 114 Nov 04, 2022
Official PyTorch code for the paper: "Point-Based Modeling of Human Clothing" (ICCV 2021)

Point-Based Modeling of Human Clothing Paper | Project page | Video This is an official PyTorch code repository of the paper "Point-Based Modeling of

Visual Understanding Lab @ Samsung AI Center Moscow 64 Nov 22, 2022
Meshed-Memory Transformer for Image Captioning. CVPR 2020

M²: Meshed-Memory Transformer This repository contains the reference code for the paper Meshed-Memory Transformer for Image Captioning (CVPR 2020). Pl

AImageLab 422 Dec 28, 2022
[ICCV'21] PlaneTR: Structure-Guided Transformers for 3D Plane Recovery

PlaneTR: Structure-Guided Transformers for 3D Plane Recovery This is the official implementation of our ICCV 2021 paper News There maybe some bugs in

73 Nov 30, 2022
ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs

ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs This is the code of paper ConE: Cone Embeddings for Multi-Hop Reasoning over Knowl

MIRA Lab 33 Dec 07, 2022
PyTorch Implementation of CvT: Introducing Convolutions to Vision Transformers

CvT: Introducing Convolutions to Vision Transformers Pytorch implementation of CvT: Introducing Convolutions to Vision Transformers Usage: img = torch

Rishikesh (ऋषिकेश) 193 Jan 03, 2023
Hydra: an Extensible Fuzzing Framework for Finding Semantic Bugs in File Systems

Hydra: An Extensible Fuzzing Framework for Finding Semantic Bugs in File Systems Paper Finding Semantic Bugs in File Systems with an Extensible Fuzzin

gts3.org (<a href=[email protected])"> 129 Dec 15, 2022
Scrutinizing XAI with linear ground-truth data

This repository contains all the experiments presented in the corresponding paper: "Scrutinizing XAI using linear ground-truth data with suppressor va

braindata lab 2 Oct 04, 2022
TraSw for FairMOT - A Single-Target Attack example (Attack ID: 19; Screener ID: 24):

TraSw for FairMOT A Single-Target Attack example (Attack ID: 19; Screener ID: 24): Fig.1 Original Fig.2 Attacked By perturbing only two frames in this

Derry Lin 21 Dec 21, 2022
Official PyTorch implementation of Joint Object Detection and Multi-Object Tracking with Graph Neural Networks

This is the official PyTorch implementation of our paper: "Joint Object Detection and Multi-Object Tracking with Graph Neural Networks". Our project website and video demos are here.

Richard Wang 443 Dec 06, 2022
SSD-based Object Detection in PyTorch

SSD-based Object Detection in PyTorch 서강대학교 현대모비스 SW 프로그램에서 진행한 인공지능 프로젝트입니다. Jetson nano를 이용해 pre-trained network를 fine tuning시켜 차량 및 신호등 인식을 구현하였습니다

Haneul Kim 1 Nov 16, 2021
Official Code for "Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning"

CMSF Official Code for "Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning" Requirements Python = 3.7.6 PyTorch

4 Nov 25, 2022
NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem

NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem Liang Xin, Wen Song, Zhiguang

xinliangedu 33 Dec 27, 2022
Pytorch implementation of NeurIPS 2021 paper: Geometry Processing with Neural Fields.

Geometry Processing with Neural Fields Pytorch implementation for the NeurIPS 2021 paper: Geometry Processing with Neural Fields Guandao Yang, Serge B

Guandao Yang 162 Dec 16, 2022
Code for the paper "MASTER: Multi-Aspect Non-local Network for Scene Text Recognition" (Pattern Recognition 2021)

MASTER-PyTorch PyTorch reimplementation of "MASTER: Multi-Aspect Non-local Network for Scene Text Recognition" (Pattern Recognition 2021). This projec

Wenwen Yu 255 Dec 29, 2022
CyTran: Cycle-Consistent Transformers for Non-Contrast to Contrast CT Translation

CyTran: Cycle-Consistent Transformers for Non-Contrast to Contrast CT Translation We propose a novel approach to translate unpaired contrast computed

Nicolae Catalin Ristea 13 Jan 02, 2023
A Python package for faster, safer, and simpler ML processes

Bender 🤖 A Python package for faster, safer, and simpler ML processes. Why use bender? Bender will make your machine learning processes, faster, safe

Otovo 6 Dec 13, 2022
This is a Tensorflow implementation of Learning to See in the Dark in CVPR 2018

Learning-to-See-in-the-Dark This is a Tensorflow implementation of Learning to See in the Dark in CVPR 2018, by Chen Chen, Qifeng Chen, Jia Xu, and Vl

5.3k Jan 01, 2023
This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model inference.

PyTorch Infer Utils This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model infer

Alex Gorodnitskiy 11 Mar 20, 2022