# check other adjustments (contrast, luminance)
# check if you can disable auto adjustments in camera
# check for all these to be adaptively applied

import cv2
import numpy as np
import math

# get image
img = cv2.imread('C:\\Users\\calin\\Desktop\\Bosch\\lateralControl\\sampleImage.jpg', -1)

# scale down
# check other dimensions
# check other interpolation methods
# check speed without resizing
width = 700
height = 400

img = cv2.resize(img, (width, height), interpolation = cv2.INTER_AREA)

# crop to region of interest
# check other shapes for RoI
"""
def cropRegion(img, vertices):
    mask = np.zeros_like(img)
    channelCount = img.shape[2]
    matchMaskColor = (255,) * channelCount
    cv2.fillPoly(mask, vertices, matchMaskColor)
    maskedImage = cv2.bitwise_and(img, mask)
    return maskedImage

roiVertices = [
    (30, height - 30),
    (width / 2, height / 2),
    (width - 30, height - 30)
]

img = cropRegion(img, np.array([roiVertices], np.int32),)
img = img[(int(height/2)):(height - 30), 30:(width - 30)]
"""
# grayscale
# check performance without grayscale
# check selecting a single channel (R, G, B) instead of grayscale
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# otsu - works only without cropping
# check different values of blur
# check with/without blur
# check with/without
img = img[(int(height/1.8)):(height - 30), (int(width*0.2)):(width - (int(width*0.15)))]

img = cv2.GaussianBlur(img, (5,1), 0)
img1, img = cv2.threshold(img, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)

# adaptive mean threshold
# check different values
#img = cv2.adaptiveThreshold(img, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 11, -10)

# adaptive gaussian threshold
# check different values
#img = cv2.adaptiveThreshold(img, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, -15)

# opening/closing (erosion + dilation)
# check different values for kernel
#kernel = np.ones((1,2), np.uint8)
#img = cv2.morphologyEx(img, cv2.MORPH_OPEN, kernel)

#kernel = np.ones((3,3), np.uint8)
#img = cv2.morphologyEx(img, cv2.MORPH_CLOSE, kernel)

# canny
#img = cv2.Canny(img, 100, 200)

# crop
def cropRegion(img, vertices):
    mask = np.zeros_like(img)
    channelCount = 1
    matchMaskColor = (255,) * channelCount
    cv2.fillPoly(mask, vertices, matchMaskColor)
    maskedImage = cv2.bitwise_and(img, mask)
    return maskedImage

roiVertices = [
    (0, len(img)),
    (len(img[0]) / 2, 0),
    (len(img[0]), len(img))
]

img = cropRegion(img, np.array([roiVertices], np.int32),)

# custom method
"""
m = len(img)
n = len(img[0])

bigSm = 0
bigNm = 0

for i in range(m):
    sm = 0
    nm = 0
    for j in range (n):
        if img[i][j] != 0 :
            sm = sm + j
            nm = nm + 1
    if nm != 0:
        aux = int(sm/nm)
        bigSm = bigSm + aux
        bigNm = bigNm + 1
        img[i][aux] = 255

bigAux = int(bigSm/bigNm)
for i in range(m):
    img[i][bigAux] = 255
"""

cv2.imshow('image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()