用Python进行RU计算

一、说明

Relative Uniformity的计算步骤：

1. RAW转Y进行计算
2. 按照公式要求进行点位的计算
3. 然后按照每个半径下值进行结果的判断

下图只是一个示例，

二、上代码

只上部分代码，请理解，有疑问可以沟通

import cv2

import numpy as np

import img_raw

for seq in range(ringNums):

r = (seq + 1.5) * ringSpacing

numSquares = 8 * (seq + 1)

for m in range(numSquares):

tempAngle = 2 * np.pi * m / numSquares

m_x = np.cos(tempAngle)

m_y = np.sin(tempAngle)

temppts_x = int(nImageWidth / 2 + r * m_x - blockSize // 2)

temppts_y = int(nImageHeight / 2 + r * m_y - blockSize // 2)

if 0 <= temppts_x < nImageWidth - blockSize and 0 <= temppts_y < nImageHeight - blockSize:

block = img[temppts_y:temppts_y + blockSize, temppts_x:temppts_x + blockSize]

rings_blockMeanY[seq].append(np.mean(block))

#= 绘制ROI（如果需要）

cv2.rectangle(rgb_image, (temppts_x, temppts_y), (temppts_x + blockSize, temppts_y + blockSize), (0,0,0), 5)

#将RAW10转换为RAW8，用于画图

raw_data_8bit = (img1 / 4).astype(np.uint8)

rgb_image = cv2.cvtColor(raw_data_8bit, cv2.COLOR_BAYER_BG2RGB)

cv2.namedWindow('RU', cv2.WINDOW_NORMAL)

cv2.imshow('RU', rgb_image)

cv2.waitKey(0)

cv2.destroyAllWindows()