I have the below code which gives me the diameter of the shaft in pixels, could you help ammend this so I can get it in mm instead? import cv$2$

import numpy as np

import matplotlib.pyplot as plt

# Function to safely load images and resize if they don't match

def load$\_$and$\_$resize$\_$images$($left$\_$image$\_$path, right$\_$image$\_$path$)$:

left$\_$image $=$ cv$2.$imread$($left$\_$image$\_$path, cv$2.$IMREAD$\_$GRAYSCALE$)$

right$\_$image $=$ cv$2.$imread$($right$\_$image$\_$path, cv$2.$IMREAD$\_$GRAYSCALE$)$

if left$\_$image is None or right$\_$image is None:

print$("$Error loading images"$)$

return None, None

try:

# Resize the images to a common size if they don't match

if left$\_$image.shape $!=$ right$\_$image.shape:

common$\_$size $=($min$($left$\_$image.shape$[1],$ right$\_$image.shape$[1]),$ min$($left$\_$image.shape$[0],$ right$\_$image.shape$[0]))$

left$\_$image $=$ cv$2.$resize$($left$\_$image, common$\_$size$)$

right$\_$image $=$ cv$2.$resize$($right$\_$image, common$\_$size$)$

except Exception as e:

print$($f$"$Error resizing images: $\{$e$\}")$

return None, None

return left$\_$image, right$\_$image

# Paths to the images

left$\_$image$\_$path $=$ 'left$\_$frame.png$\text{'}$

right$\_$image$\_$path $=$ 'right$\_$frame.png$\text{'}$

# Your camera parameters are already defined in your code.

intrinsic$\_$matrix$\_1=$ np$.$array$([[1024\mathrm{.}08777,0.,601\mathrm{.}806702],$

$[0,1023\mathrm{.}89478,508\mathrm{.}131683],$

$[0,0,1]])$

distortion$\_$coeffs$\_1=$ np$.$array$([-2\mathrm{.}52257544$e$-03,4\mathrm{.}38565714$e$-03,0,0,9\mathrm{.}21500759$e$-05])$

intrinsic$\_$matrix$\_2=$ np$.$array$([[1024\mathrm{.}19836,0.,696\mathrm{.}750427],$

$[0,1023\mathrm{.}987498,507\mathrm{.}4942636],$

$[0,0,1]])$

distortion$\_$coeffs$\_2=$ np$.$array$([-3\mathrm{.}26306466$e$-03,5\mathrm{.}70008671$e$-03,0,0,7\mathrm{.}57322850$e$-05])$

R $=$ np$.$array$([[9\mathrm{.}9999404$e$-01,-1\mathrm{.}24093054$e$-06,-1\mathrm{.}11142127$e$-03],$

$[1\mathrm{.}29263049$e$-06,1,4\mathrm{.}65405355$e$-05],$

$[1\mathrm{.}11142127$e$-03,-4\mathrm{.}65419434$e$-05,9\mathrm{.}9999404$e$-01]])$

T $=$ np$.$array$([[4\mathrm{.}34818459],[2\mathrm{.}83608016$e$-02],[9\mathrm{.}00963729$e$-04]])$

# Load, undistort, and rectify images

left$\_$image, right$\_$image $=$ load$\_$and$\_$resize$\_$images$(\text{'}$left$\_$frame.png$\text{'},$ 'right$\_$frame.png$\text{'})$

# Check if the images were loaded correctly

if left$\_$image is None or right$\_$image is None:

raise ValueError$("$Images could not be loaded or found."$)$

def undistort$\_$and$\_$rectify$\_$images$($left$\_$image, right$\_$image, intrinsic$\_$matrix$\_1,$ distortion$\_$coeffs$\_1,$ intrinsic$\_$matrix$\_2,$ distortion$\_$coeffs$\_2,$ R$,$ T$)$:

# Load images

left$\_$image $=$ cv$2.$imread$($left$\_$image$\_$path, cv$2.$IMREAD$\_$GRAYSCALE$)$

right$\_$image $=$ cv$2.$imread$($right$\_$image$\_$path, cv$2.$IMREAD$\_$GRAYSCALE$)$

# Undistort images

left$\_$image$\_$undistorted $=$ cv$2.$undistort$($left$\_$image, intrinsic$\_$matrix$\_1,$ distortion$\_$coeffs$\_1)$

right$\_$image$\_$undistorted $=$ cv$2.$undistort$($right$\_$image, intrinsic$\_$matrix$\_2,$ distortion$\_$coeffs$\_2)$

# Stereo rectification $($computes the rotation matrices for each camera$)$

R$1,$ R$2,$ P$1,$ P$2,$ Q$,\_,\_=$ cv$2.$stereoRectify$($intrinsic$\_$matrix$\_1,$ distortion$\_$coeffs$\_1,$ intrinsic$\_$matrix$\_2,$ distortion$\_$coeffs$\_2,$

left$\_$image.shape$[$::$-1],$ R$,$ T$)$

# Apply rectification

map$1\_$x$,$ map$1\_$y $=$ cv$2.$initUndistortRectifyMap$($intrinsic$\_$matrix$\_1,$ distortion$\_$coeffs$\_1,$ R$1,$ P$1,$ left$\_$image.shape$[$::$-1],$ cv$2.$CV$\_32$FC$1)$

map$2\_$x$,$ map$2\_$y $=$ cv$2.$initUndistortRectifyMap$($intrinsic$\_$matrix$\_2,$ distortion$\_$coeffs$\_2,$ R$2,$ P$2,$ right$\_$image.shape$[$::$-1],$ cv$2.$CV$\_32$FC$1)$

left$\_$image$\_$rectified $=$ cv$2.$remap$($left$\_$image$\_$undistorted, map$1\_$x$,$ map$1\_$y$,$ cv$2.$INTER$\_$LINEAR$)$

right$\_$image$\_$rectified $=$ cv$2.$remap$($right$\_$image$\_$undistorted, map$2\_$x$,$ map$2\_$y$,$ cv$2.$INTER$\_$LINEAR$)$

return left$\_$image$\_$rectified, right$\_$image$\_$rectified, Q

# Perform stereo rectification and undistortion using the provided camera parameters

left$\_$image$\_$rectified, right$\_$image$\_$rectified, Q $=$ undistort$\_$and$\_$rectify$\_$images$($left$\_$image, right$\_$image, intrinsic$\_$matrix$\_1,$ distortion$\_$coeffs$\_1,$ intrinsic$\_$matrix$\_2,$ distortion$\_$coeffs$\_2,$ R$,$ T$)$

# Tune these parameters for better results

min$\_$disparity $=0$

num$\_$disparities $=6*16$ # Increase in multiples of $16$

block$\_$size $=11$ # Must be odd, increase for smoother but less detailed images

uniqueness$\_$ratio $=15$ # Increase to discard more false matches

speckle$\_$window$\_$size $=50$ # Increase to discard more noise but risk losing detail

speckle$\_$range $=2$ # Increase for wider range of disparity changes to consider as belonging to the same object

# Initialize the stereo block matching object

stereo $=$ cv$2.$StereoSGBM$\_$create$($

minDisparity$=$min$\_$disparity,

numDisparities$=$num$\_$disparities,

blockSize$=$block$\_$size,

uniquenessRatio$=$uniqueness$\_$ratio,

speckleWindowSize$=$speckle$\_$window$\_$size,

speckleRange$=$speckle$\_$range,

disp$12$MaxDiff$=1,$

P$1=8*3*$ block$\_$size $**$