I am posting the same question for the second time. please don't give copy and paste answers. this code is for shape detection. it doesn't work because there are unnecessary lines and dots in the image I uploaded. can you improve this code and try it on the image I uploaded?

import cv$2$

import numpy as np

import argparse

def angle$($pt$1,$ pt$2,$ pt$0)$:

# pt$1$ ve pt$0$ aras$$ndaki kenar$$n x$\text{'}$i $($pt$1$x $-$ pt$0$x$)$

dx$1=$ pt$1[0]-$ pt$0[0]$

# pt$1$ ve pt$0$ aras$$ndaki kenar$$n y'si $($pt$1$y $-$ pt$0$y$)$

dy$1=$ pt$1[1]-$ pt$0[1]$

# pt$2$ ve pt$0$ aras$$ndaki kenar$$n x$\text{'}$i $($pt$2$x $-$ pt$0$x$)$

dx$2=$ pt$2[0]-$ pt$0[0]$

# pt$2$ ve pt$0$ aras$$ndaki kenar$$n y'si $($pt$2$y $-$ pt$0$y$)$

dy$2=$ pt$2[1]-$ pt$0[1]$

return $($dx$1*$ dx$2+$ dy$1*$ dy$2)/$ np$.$sqrt$(($dx$1*$ dx$1+$ dy$1*$ dy$1)*($dx$2*$ dx$2+$ dy$2*$ dy$2))$

def main$($input$\_$image$)$:

input$\_$path $="$C:$/$Users$/$burak$/$Desktop$/$Shape Recognition & Detection$/$data$/$input$/"$

output$\_$path $="$C:$/$Users$/$burak$/$Desktop$/$Shape Recognition & Detection$/$data$/$output$"$

image $=$ cv$2.$imread$($input$\_$path $+$ input$\_$image$)$

if image is None:

print$("$Resim a$$lamad$$ ya da y$$klenemedi$.")$

return

# gri

gray $=$ cv$2.$cvtColor$($image$,$ cv$2.$COLOR$\_$BGR$2$GRAY$)$

cv$2.$imwrite$($output$\_$path $+"\backslash \backslash$output$\_$gray.png$",$ gray$)$

# blurlama

blurred $=$ cv$2.$GaussianBlur$($gray$,(5,5),0)$

cv$2.$imwrite$($output$\_$path $+"\backslash \backslash$output$\_$blurred.png$",$ blurred$)$

# kenar alg$$lama

edged $=$ cv$2.$Canny$($blurred$,100,200)$

cv$2.$imwrite$($output$\_$path $+"\backslash \backslash$output$\_$edged.png$",$ edged$)$

# kontor bulma

contours, $\_=$ cv$2.$findContours$($edged$,$ cv$2.$RETR$\_$EXTERNAL, cv$2.$CHAIN$\_$APPROX$\_$SIMPLE$)$

# $$ekil alg$$lama

for contour in contours:

shape $=""$

peri $=$ cv$2.$arcLength$($contour$,$ True$)$

approx $=$ cv$2.$approxPolyDP$($contour$,0\mathrm{.}02*$ peri, True$)$

if len$($approx$)==3$:

shape $=$ "triangle"

elif len$($approx$)==4$:

max$\_$cosine $=0$

for j in range$(2,5)$:

cosine $=$ abs$($angle$($approx$[$j $\%4][0],$ approx$[$j $-2][0],$ approx$[$j $-1][0]))$

max$\_$cosine $=$ max$($max$\_$cosine, cosine$)$

if max$\_$cosine $<mtext\; id="EditorElement\_3205786"></mtext><mn\; id="EditorElement\_3205787">0</mn><mn\; id="EditorElement\_3205788">.</mn><mn\; id="EditorElement\_3205789">3</mn>$:

# kare

edges $=[]$

for i in range$(4)$:

pt$1=$ approx$[$i$][0]$

pt$2=$ approx$[($i $+1)\%4][0]$

edge$\_$length $=$ np$.$sqrt$(($pt$1[0]-$ pt$2[0])**2+($pt$1[1]-$ pt$2[1])**2)$

edges.append$($edge$\_$length$)$

# kenarlar e$$it mi

if max$($edges$)-$ min$($edges$)<mtext\; id="EditorElement\_3206182"></mtext><mn\; id="EditorElement\_3206183">1</mn><mn\; id="EditorElement\_3206184">0</mn>$:

shape $=$ "square"

else:

shape $=$ "rectangle"

else:

edges $=[]$

for i in range$(4)$:

pt$1=$ approx$[$i$][0]$

pt$2=$ approx$[($i $+1)\%4][0]$

edge$\_$length $=$ np$.$sqrt$(($pt$1[0]-$ pt$2[0])**2+($pt$1[1]-$ pt$2[1])**2)$

edges.append$($edge$\_$length$)$

edges $=$ sorted$($edges$)$

if abs$($edges$[0]-$ edges$[1])<mtext\; id="EditorElement\_3206675"></mtext><mn\; id="EditorElement\_3206676">5</mn><mn\; id="EditorElement\_3206677">0</mn>$ and abs$($edges$[2]-$ edges$[3])<mtext\; id="EditorElement\_3206709"></mtext><mn\; id="EditorElement\_3206710">5</mn><mn\; id="EditorElement\_3206711">0</mn>$:

shape $=$ "parallelogram"

elif abs$($edges$[0]-$ edges$[1])<mtext\; id="EditorElement\_3206805"></mtext><mn\; id="EditorElement\_3206806">5</mn><mn\; id="EditorElement\_3206807">0</mn>$ or abs$($edges$[2]-$ edges$[3])<mtext\; id="EditorElement\_3206838"></mtext><mn\; id="EditorElement\_3206839">5</mn><mn\; id="EditorElement\_3206840">0</mn>$:

shape $=$ "trapezoid"

elif len$($approx$)>4$:

shape $=$ "circle"

cv$2.$drawContours$($image$,[$contour$],-1,(0,255,0),2)$

M $=$ cv$2.$moments$($contour$)$

cX $=$ int$($M$["$m$10"]/$ M$["$m$00"])$

cY $=$ int$($M$["$m$01"]/$ M$["$m$00"])$

cv$2.$putText$($image$,$ shape, $($cX $-50,$ cY$),$ cv$2.$FONT$\_$HERSHEY$\_$SIMPLEX, $0\mathrm{.}5,(255,0,0),1)$

# output

cv$2.$imwrite$($output$\_$path $+"\backslash \backslash$output$\_$shapes.png$",$ image$)$

cv$2.$imshow$("$Shapes$",$ image$)$

cv$2.$waitKey$(0)$

cv$2.$destroyAllWindows$()$

if $\_\_$name$\_\_=="\_\_$main$\_\_"$:

parser $=$ argparse.ArgumentParser$($description$=$"Shape detection in an image."$)$

parser.add$\_$argument$("$input$\_$image", type$=$str$,$ help$=$"Input'un dosya yolu."$)$

args $=$ parser.parse$\_$args$()$

main$($args$.$input$\_$image$)$

#python sekilalgilama.py resimad$$