可生成Windows平台动态库(DLL)的HyperLPR项目
原库:https://github.com/szad670401/HyperLPR
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8 years ago | |
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Font | 8 years ago | |
cache | 8 years ago | |
dataset | 8 years ago | |
hyperlpr | 8 years ago | |
model | 8 years ago | |
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README.md | 8 years ago | |
batch.py | 8 years ago | |
benchmark.py | 8 years ago | |
upload.py | 8 years ago | |
wxpy_uploader.py | 8 years ago |
README.md
车牌识别
Pipeline
step1. 使用opencv 的 HAAR cascade 检测车牌大致位置
step2. Extend 检测到的大致位置的矩形区域
step3. 使用类似于mser的方式的多级二值化+ransac拟合车牌的上下边界
step4. 使用CNN regression回归车牌左右边界
step5. 使用CNN滑动窗切割字符
step6. 使用CNN识别字符
简单测试方式
from hyperlpr import pipline as pp
import cv2
image = cv2.imread("filename")
image,res = pp.SimpleRecognizePlate(image)