#!/usr/bin/python

import cv2
import numpy as np

# mesh image
imMesh = cv2.imread('new_refined2__DXF.png', -1)

# layer image
imLayer1 = cv2.imread('Layer1.png', -1)

"""
binary conversions
"""
imMeshGray = cv2.cvtColor(imMesh, cv2.COLOR_BGR2GRAY)
ret, imMeshBw = cv2.threshold(imMeshGray, 250, 255, cv2.THRESH_BINARY)

imLayer1Gray = cv2.cvtColor(imLayer1, cv2.COLOR_BGR2GRAY)
(thresh, imLayerBw) = cv2.threshold(imLayer1Gray, 128, 255,
                                    cv2.THRESH_BINARY | cv2.THRESH_OTSU)

connectivity = 4

output = cv2.connectedComponentsWithStats(imMeshBw, connectivity, cv2.CV_32S)
num_labels = output[0]
labels = output[1]
stats = output[2]

centroids = output[3]


print(labels)
print(num_labels)

# if I want for each label
for label in np.unique(labels):
    if label == 0:
        continue
    mask = np.zeros(imMeshGray.shape, dtype="uint8")
    mask[labels == label] = 255
    cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2]
    # c = max(cnts, key=cv2.contourArea)
    for c in cnts:
        M = cv2.moments(c)
        if M["m00"] != 0:
            cX = int(M["m10"] / M["m00"])
            cY = int(M["m01"] / M["m00"])
        else:
            cX, cY = 0, 0

    peri = cv2.arcLength(c, True)
    approx = cv2.approxPolyDP(c, 0.05 * peri, True)
    if (len(approx) == 3):
        cv2.drawContours(imMesh, [c], -1, (0, 255, 0), 1)
        cv2.putText(imMesh, "*", (cX, cY), cv2.FONT_HERSHEY_SIMPLEX,0.5, (0, 0, 0), 1)

cv2.imwrite('tstCountoursConnected.jpg', imMesh)