Contors.py

import cv2
import math
import numpy as np


#Cosine_Law 
def cosine_law(start,end):
 
       
    horizontal={"x": 1000 , "y": start["y"] }

    diff_x_start=(1000 - start["x"])
    diff_y_start=0

    diff_x_end=(end["x"]-start["x"])
    diff_y_end=(end["y"]-start["y"])

    adotb= (diff_x_start*diff_x_end) + (diff_y_start*diff_y_end)

   

    a_mag=math.hypot(diff_x_start,diff_y_start)
    b_mag=math.hypot(diff_x_end,diff_y_end)
    cos= (adotb/(a_mag * b_mag))
    angle=math.acos(cos)
    
    return  angle * (180/3.14)


#Testing Purposes

previous="down"
current= 0
startpoint=0
endpoint=0
first_time=1
img = cv2.imread("img.png", cv2.IMREAD_COLOR)
# detect red lines
# =======================================
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
min = np.array([150, 40, 40])
max = np.array([190, 255, 255])
mask = cv2.inRange(hsv, min, max)
res = cv2.bitwise_and(img, img, mask=mask)

gray_res = cv2.cvtColor(res, cv2.COLOR_BGR2GRAY)
kernal = np.ones((5, 5), np.uint8)
gray_res = cv2.morphologyEx(gray_res, cv2.MORPH_CLOSE, kernal)
# =======================================

# ============ get edges =======================
edges = cv2.Canny(gray_res, 100, 100)
# =============================================

#Detects the contors in the image
_,cnts,h  = cv2.findContours(edges.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
#Sorts them by area
cnts = sorted(cnts, key = cv2.contourArea, reverse = True)[:10]
#Gets the length of biggest contor
peri = cv2.arcLength(cnts[0], True)
#Approximates the Contor we have to one with less vertices
approx = cv2.approxPolyDP(cnts[0], 0.02 * peri, True)
#same thing
#check the documentation:
#https://docs.opencv.org/3.1.0/dd/d49/tutorial_py_contour_features.html
vertices = cv2.convexHull(approx, clockwise=False)

#we define variables , called Biggest X, Biggest Y , Smallest X , Smallest Y
smallest_x,smallest_y=vertices[0].ravel()
biggest_x=smallest_x
biggest_y=smallest_y

i=0

for corner in vertices:
    print(corner)
    x,y=corner[0].ravel()

    if(first_time==1):
        x_smallesty=x
        x_biggesty=x
        y_smallestx=y
        y_biggestx=y
        first_time=0

    
    if (x > biggest_x):
        biggest_x = x
        y_biggestx=y

    elif (x < smallest_x):
        smallest_x = x
        y_smallestx=y

    if (y > biggest_y):
        biggest_y = y
        x_biggesty =x

    elif (y < smallest_y):
        smallest_y = y
        x_smallesty=x

    i+=1

#==================================
#we want to make the rov able to find the next state 
#from the value of the previous state
#==================================

if (previous == "left"):
    startpoint= {"x":biggest_x,"y":y_biggestx}
    endpoint  = {"x":smallest_x,"y":y_smallestx}
    zawya= cosine_law(startpoint,endpoint)
    

elif (previous == "right"):
    startpoint= {"x": smallest_x,"y": y_smallestx}
    endpoint=   {"x": biggest_x,"y": y_biggestx}
    zawya= cosine_law(startpoint,endpoint)


elif (previous == "up"):
    startpoint= {"x":x_biggesty,"y": biggest_y}
    endpoint=   {"x":x_smallesty, "y": smallest_y}
    zawya= cosine_law(startpoint,endpoint)


elif (previous == "down"):
    startpoint= {"x":x_smallesty,"y":smallest_y}
    endpoint=   {"x":x_biggesty,"y":biggest_y}
    zawya= cosine_law(startpoint,endpoint)


#what needs to be done
#Implement the code written on the whiteboard
#testing.










cv2.imshow('Corner', img)


u = cv2.waitKey(0)