#import cv2 for vision
#numpy to generate backgrounds
import cv2
import numpy as np

#capture video from the webcam
cap = cv2.VideoCapture(0)
#read one frame
_, img = cap.read()

#define two points, used to make a mask
x1 = 100
y1 = 100
x2 = 200
y2 = 200
# create a mask
mask = np.zeros(img.shape[:2], np.uint8)
mask[y1:y2, x1:x2] = 255

#define the height of the graph
graph_height = 200
graph_length = 640

#main loop of
while True:

    #read image from the webcam
    _, img = cap.read()

    #convert image to hsv color space
    img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

    #calculate the histogram for the hue value in the masked area
    hist_mask = cv2.calcHist([img_hsv], [0], mask, [255], [0,256])

    #create a mask of the image
    masked_img = cv2.bitwise_and(img,img,mask = mask)

    #create gray background for graph
    graph = np.zeros((graph_height,graph_length,3),np.uint8)
    graph[::] = (123,123,123)

    #define values for graphing for graphing
    x_value = 0
    previous_x = 0
    previous_y = 640
    #scale the histogram
    hist_scaled = hist_mask*(graph.shape[0]/max(hist_mask))

    #make graph
    for y_value in hist_scaled:

        #tedious method to convert values to get color
        test = np.zeros((1,1,3), np.uint8)
        test[::] = int(x_value/3.0), 255,255
        test = cv2.cvtColor(test, cv2.COLOR_HSV2BGR)
        cvc = int(test[0][0][0]), int(test[0][0][1]), int(test[0][0][2])

        #spacing issues
        x_value+=3
        y_value =  graph_height-y_value

        #graph
        cv2.line(graph, (x_value, y_value),
                 (previous_x, previous_y), cvc, 8)

        #update previous values
        previous_x = x_value
        previous_y = y_value

    #put a rectangle on the image to show where the mask
    cv2.rectangle(img,(x1,y1), (x2,y2), (123,123,123), 2)

    #show image
    cv2.imshow('img', img)
    cv2.imshow('graph', graph)
    cv2.waitKey(1)

cv2.destroyAllWindows()
cap.release()