'''
Number from 1 to 3 expected as an argument
to determine which MatchShapes version to use
'''

import cv2
import numpy as np
import os, os.path, time, sys

def main():
    if len(sys.argv) > 1:
        matching_method = str(sys.argv[1])
    else:
        matching_method = 1
    final_result = {}
    for file in sorted(os.listdir("routes")): # iterate through all the routes
        rotation = 0
        result_list = {}
        smallest = 100
        for i in range (0,1): # determine rotations (default 0)

            route_name = str(file)
            route = cv2.imread('routes/' + route_name)
            route = cv2.cvtColor(route, cv2.COLOR_BGR2GRAY)
            blank_route = np.zeros((140,140,3), np.uint8) # blank image to draw contours on

            rows,cols = route.shape
            M = cv2.getRotationMatrix2D((cols/2,rows/2),rotation,1)
            dst = cv2.warpAffine(route,M,(cols,rows))
            route = cv2.resize(dst, (140,140))

            kernel = np.ones((2,25),np.uint8)
            route = cv2.dilate(route,kernel,iterations = 1) # apply dilation to make routes a bit simpler

            route_ret, route_thresh = cv2.threshold(route, 127, 255,0)

            route_contours,route_hierarchy = cv2.findContours(route_thresh,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE) # find contours

            route_cnt1 = route_contours[0] # take first contour

            cv2.drawContours(blank_route, route_cnt1, -1, (0,255,0), 3)

            result_list = comparison(matching_method, route_name, blank_route, route_cnt1, result_list, rotation)
            #rotation = rotation + 90

            smallest_distance = min(result_list, key=result_list.get)
            value_of_smallest = result_list.get(smallest_distance, "none")

            if value_of_smallest <= smallest:
                smallest = value_of_smallest
                final_result[route_name] = smallest_distance, value_of_smallest
    for k,v in sorted(final_result.items()):
        print(k, v)

def comparison(matching_method, route_name, blank_route, route_cnt1, result_list, rotation):

    combined_image = np.zeros((140,140,3), np.uint8)
    sample_images = np.zeros((140,140,3), np.uint8)
    
    for file in os.listdir("samples"):
        sample_name = str(file)
        blank_sample = np.zeros((140,140,3), np.uint8) # blank image to draw contours on
        sample = cv2.imread('samples/' + sample_name)
        sample = cv2.cvtColor(sample, cv2.COLOR_BGR2GRAY)
        sample = cv2.resize(sample, (140,140))
        sample = cv2.bitwise_not(sample) # invert black and white

        
        sample_ret, sample_thresh = cv2.threshold(sample, 127, 255,0) # thresholding
        sample_contours,sample_hierarchy = cv2.findContours(sample_thresh,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
        sample_cnt1 = sample_contours[0] # take first contour
        approx2 = cv2.approxPolyDP(sample_cnt1, 0.01*cv2.arcLength(sample_cnt1, True), True) # approximation can be used for contours

        cv2.drawContours(blank_sample, sample_cnt1, -1, (0,255,0), 3)
        
        sample_images = np.concatenate((sample_images, blank_sample), axis=1) # show all the sample images
        #cv2.imshow("sample", sample_images)
        
        if(int(matching_method) == 1):
            #result = cv2.matchShapes(route_cnt1, sample_cnt1,cv2.CONTOURS_MATCH_I1,0.0)
            result = cv2.matchShapes(route_cnt1, sample_cnt1,1,0.0)
            result_list[str(file)] = result
            
        elif(int(matching_method) == 2):
            result = cv2.matchShapes(route_cnt1,sample_cnt1,cv2.CONTOURS_MATCH_I2,0.0)
            result_list[str(file)] = result
            
        elif(int(matching_method) == 3):
            result = cv2.matchShapes(route_cnt1,sample_cnt1,cv2.CONTOURS_MATCH_I3,0.0)
            result_list[str(file)] = result
        
        print("Difference between ", sample_name, "and ", route_name, result)
    
    combined_image = np.concatenate(( blank_route,combined_image), axis=0)
    #cv2.imshow("Comparison", combined_image)
    #cv2.waitKey(0)

    return result_list  
    
main()