from pyclustering.nnet.som import som, type_conn, type_init, som_parameters
from ann.function.sompy import SOMFactory
import numpy as np
import pandas as pd
import glob
import os
# 1. load image
img = cv.imread('C:/flashwoman/Object-detection/EyeCandy/img/img_book_only.png')
img_org = cv.imread('C:/flashwoman/Object-detection/EyeCandy/img/bookshelf_04.jpg')
# 2. preprocess images
img = preprocessing(img)
img, rect = contours(img,img_org)
# 3. bring mid coordinates
coord = []
for i in range(len(rect)):
# extracting colour by using mid-coordinates of the book
x = (list(rect[i][0])[0] + list(rect[i][1])[0])/2
y = (list(rect[i][0])[1] + list(rect[i][1])[1])/2
coord.append([x, y])
print('book_mid_coordinates :\n', coord)
# 4. get 'bgr' from coordinates
bgr_val = []
for i in range(len(coord)):
## 1. x, y 좌표값 받아오기
path = 'C:/flashwoman/EyeCandy/img/source/detect-bookshelf/origin/bookshelf_03.jpg'
img_color = cv.imread(path)
display('img_color', img_color)
img_gray = cv.cvtColor(img_color, cv.COLOR_BGR2GRAY)
display('img_gray', img_gray)
# deal with no-background colors
ret, thresh = cv.threshold(img_gray, 127, 255, cv.THRESH_BINARY)
display('sep_threshold', thresh)
img_color = preprocessing(img_color, 3, 3)
img_write('1_thresh', img_color)
# deal with similar-background colors
ret, thresh = cv.threshold(img_gray, 127, 255, cv.THRESH_BINARY_INV)
# display('sep_threshold', thresh)
# img_color = preprocessing(img_color)
# img_write('2_thresh', img_color)
# do contour
path = 'C:/flashwoman/Object-detection/EyeCandy/img/img_book_only.png'
img_book_only = cv.imread(path)
img_book_only = preprocessing(img_book_only)
img_color = contours(img_book_only, img_color)
img_write('3_contour', img_color)
# do watershed
img_watershed = watershed(img_color)
display('watershed img', img_watershed)
img_write('watershed', img_watershed)
cv.destroyAllWindows()