No project description provided
Project description
gooder-cv
基于python-opencv2查找图像中对象位置
Find object position based on python-opencv2 for python2.7+
Usage
import gooder_cv as ac
imsrc = ac.imread('youimage.png') # 原始图像
imsch = ac.imread('searched.png') # 带查找的部分
SIFT查找图像
print ac.find_sift(imsrc, imsch)
# - when Not found
@return None
# 之前是返回的 []
# - when found
@return {'point': (203, 245), 'rectangle': [(160, 24), (161, 66), (270, 66), (269, 24)], 'confidence': 0.09}
# point: 查找到的点
# rectangle: 目标图像周围四个点的坐标
# confidence: 查找图片匹配成功的特征点 除以 总的特征点
SIFT多个相同的部分查找
print ac.find_all_sift(imsrc, imsch, maxcnt = 0)
# - when not found
@return []
# - when found
@return [{..}, {..}]
# {..}的内容跟SIFT查找到单个图像的格式一样
maxcnt是可选参数,限制最多匹配的数量。
直接匹配查找图像
print ac.find_template(imsrc, imsch)
期望输出 (目标图片的中心点,相似度), 相似度是电脑计算出来的一个值,跟平常所说的相似97%不是一个意思。对于这个值,达到0.999以上才算是图片一样。
(294, 13), 0.9715
查找多个相同的图片,如在图形
中查找
print ac.find_all_template(imsrc, imsch)
期望输出 (目标图片的中心点,相似度)
[((294, 13), 0.9715), ...]
效果
开发规范
LICENSE
LICENCE under MIT
Some other idea. Not implemented
example
import gooder_cv
imsrc = gooder_cv.Image('demo.png')
imobj = gooder_cv.Image('object.png')
print(imsrc.find(imobj, method=gooder_cv.FIND_TMPL)) # or method=gooder_cv.FIND_SIFT
# expect gooder_cv.Position(x=10, y=20, extra={'method': gooder_cv.FIND\_TMPL, 'result': 0.98})
print(imobj.find_in(imsrc, method=gooder_cv.FIND_TMPL))
# expect gooder_cv.Position(x=10, y=20)
rect = gooder_cv.Rect(left=80, top=10, width=50, height=90)
# Rect define: Rect(left=0, top=0, right=None, bottom=None, width='100%', height='100%')
pos = imsrc.find(imobj, rect=rect, method=gooder_cv.FIND_TMPL)
print(pos)
# expect gooder_cv.Position(x=10, y=20)
print(imsrc.draw_point(pos)) # .draw_point(pos2)
# expect gooder_cv.Image object
print(imsrc.draw_rectangle(gooder_cv.Rect(left=80)))
# expect gooder_cv.Image object
print(imsrc.draw_circle('??'))
print(imsrc.cv_object)
# expect numpy object
imsrc.save('source.png')
# An Exception raised when file exists
print(imsrc.rect() == imobj.rect())
# expect True or False
print(imsrc.percent(imobj))
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
No source distribution files available for this release.See tutorial on generating distribution archives.
Built Distribution
Close
Hashes for gooder_cv-1.2.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | f3029985d023a97e57ee2f7848f73f9b1c5203fee1296ea27bc8563abf8cfd4b |
|
MD5 | 8f905734e3554d2a7096d070f325b1b3 |
|
BLAKE2b-256 | dc5b6af6204cb22f564091813ec7ab45933a3cd9e3661187878d4f916b097800 |