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src/helpers/template_extraction/input/whack.jpg
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src/helpers/template_extraction/output/template.jpg
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@ -1,53 +1,14 @@
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"""
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Script to extract 10cm x 10cm images from the template
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Accounts for (minor) rotation.
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command:
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python template.py input_folder output_folder
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volgorde maakt uit! heb niet die fancy library gebruikt
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Auteurs:
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Tom Selier
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Arne van Iterson
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"""
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import cv2
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import numpy as np
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import sys
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import os
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import math as m
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## Parameters ##
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# [%] Schaal output in percentages
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SCHAAL = 25
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# [mm] 120 op calib a4, 180 op template
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CALIB_AFSTAND = 120
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# [mm] design foutje, 10 op a4, 15 op template
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CORRECTIE = 15
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# [mm] mm om af te snijden
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OFFSET = 20
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# Toon plaatjes (forceert pauze)
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PLAATJES = False
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# Wacht na elke plaatje op toets
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PAUZE = False
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# Sla plaatjes op
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SAVE = False
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# extra info
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VERBOSE = True
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# command:
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# python template.py input_folder output_folder
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# Returns the correct corner based on IDs
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def getCorner(id):
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"""
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Returns the correct corner based on IDs
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"""
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if(id == 0):
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return 2
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if(id == 1):
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@ -57,25 +18,8 @@ def getCorner(id):
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if(id == 3):
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return 1
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def findMax(array, index):
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"""
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Vind max voor een rare list van tuples
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"""
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max_val = int(0)
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for element in array:
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if element[index] > max_val:
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max_val = element[index]
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return max_val
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def findMin(array, index):
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"""
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Vind min voor een rare list van tuples
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"""
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min_val = int(10e6)
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for element in array:
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if element[index] < min_val:
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min_val = element[index]
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return min_val
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if(len(sys.argv) != 3):
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print("Wrong amount of arguments")
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input_folder = sys.argv[1]
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output_folder = sys.argv[2]
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@ -88,42 +32,36 @@ if(not os.path.isdir(output_folder)):
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print("Output folder not found")
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exit()
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scale_percentage = 25
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### ARUCO PARAMETERS ###
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# Aruco params
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detector_params = cv2.aruco.DetectorParameters()
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dictionary = cv2.aruco.getPredefinedDictionary(cv2.aruco.DICT_ARUCO_ORIGINAL)
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detector = cv2.aruco.ArucoDetector(dictionary, detector_params)
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### IMAGE CONVERSIE ###
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for file in os.listdir(input_folder):
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## Laad plaatjes in kleur ##
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# Laad een plaatje
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filename = input_folder + '/' + file
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out_filename = output_folder + '/' + file
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img = cv2.imread(filename, 1)
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img = cv2.imread(filename, 0)
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if VERBOSE:
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print(file)
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# Rescaling
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x_scale = int(img.shape[0]/100*scale_percentage)
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y_scale = int(img.shape[1]/100*scale_percentage)
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# print("X_scale:", x_scale)
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# print("Y_scale:", y_scale)
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## Herschaal de fotos ##
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(h, w) = img.shape[:2]
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x_scale = int(w/100*SCHAAL)
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y_scale = int(h/100*SCHAAL)
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# Detecteer markers
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small_img = cv2.resize(img, (x_scale, y_scale))
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(h_small, w_small) = small_img.shape[:2]
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if VERBOSE:
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print("Van %dx%dpx naar %dx%dpx geschaald"%(h,w,h_small,w_small))
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## Detecteer aruco markers ##
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(corners, ids, rejected) = detector.detectMarkers(small_img)
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new_image = cv2.aruco.drawDetectedMarkers(
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small_img,
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corners,
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ids)
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assert len(ids) == 4, "Not enough markers found in " + str(file)
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if VERBOSE:
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print("%d markers gedetecteerd" %len(ids))
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## Zoek de 'binnenste' hoekjes ##
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assert len(ids) == 4, "Not enough markers found"
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# Zoek de "binneste" hoekjes
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i = 0
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x = np.zeros(4, dtype=np.int32)
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y = np.zeros(4, dtype=np.int32)
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@ -133,18 +71,15 @@ for file in os.listdir(input_folder):
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cv2.circle(
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new_image,
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(x[i], y[i]),
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radius=3,
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color=(0, 254, 254),
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radius=5,
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color=(255, 100, 255),
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thickness=-1)
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print("x[%d]: %d"%(i, x[i]))
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print("y[%d]: %d"%(i, y[i]))
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print()
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i += 1
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if VERBOSE:
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print("Gedecteerde hoekjes (recht): ")
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print("\t x: ", end='')
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print(x)
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print("\t y: ", end='')
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print(y)
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## Draai de plaatjes recht ##
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# Draai plaatje om 0 en 1 gelijk te trekken
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x0 = x[np.where(ids == 0)[0][0]]
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x1 = x[np.where(ids == 1)[0][0]]
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x_dif = x0-x1
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@ -153,69 +88,29 @@ for file in os.listdir(input_folder):
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y1 = y[np.where(ids == 1)[0][0]]
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y_dif = y0 - y1
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angle_rad = np.arctan(y_dif/x_dif)
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angle_deg = angle_rad * 180.0 / np.pi
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if(VERBOSE):
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print("%d graden gedraaid"%angle_deg)
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angle_error_rad = np.arctan(y_dif/x_dif)
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angle_error_deg = angle_error_rad * 180.0 / m.pi
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print("Hoek deg", angle_error_deg)
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(cX, cY) = (w_small // 2, h_small // 2)
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matrix = cv2.getRotationMatrix2D((cX, cY), angle_deg, 1.0)
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warp_img = cv2.warpAffine(new_image, matrix, (w_small, h_small))
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# Calibreer afstand tov afstand tussen 0 en 1
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## Herdetecteer de binnenste hoekjes op de gedraaide plaatjes ##
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mask = cv2.inRange(warp_img, (0, 253, 253), (0, 255, 255))
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warped_corners = []
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for i in range(4):
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coordinate = cv2.minMaxLoc(mask)[3]
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warped_corners.append(coordinate)
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cv2.circle(mask, warped_corners[i], 10, (0, 0, 0), -1)
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if VERBOSE:
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print("Gedecteerde hoekjes (gedraaid): ")
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print("\t", warped_corners)
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# Teken rode balken
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## Teken rode balken voor controle ##
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# feature voor ooit, nogal lastig
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## Calibratie van afstand met betrekking tot pixels ##
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x_min = w_small
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x_max = 0
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for corner in warped_corners:
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# vind x waarden bovenaan
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(x, y) = corner
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if y < (h_small // 2):
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if x < x_min:
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x_min = x
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else:
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x_max = x
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x_diff = x_max - x_min
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calib_scale = x_diff / CALIB_AFSTAND
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if VERBOSE:
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print("Berekende schaal: %d pixels/mm"%calib_scale)
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# Crop
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offset = 180
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crop_img = new_image[
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np.min(x+offset):np.max(x-offset),
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np.min(y+offset):np.max(y-offset)
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]
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## Crop de plaatjes ##
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top_left_x = findMin(warped_corners, 0)
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top_left_y = findMin(warped_corners, 1)
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bot_right_x = findMax(warped_corners, 0)
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bot_right_y = findMax(warped_corners, 1)
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offset = int((OFFSET+CORRECTIE)*calib_scale)
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crop_img = warp_img[
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top_left_y+offset:bot_right_y-offset,
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top_left_x+offset:bot_right_x-offset]
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## Check voor rode balken ##
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# zie boven
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## Output ##
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if PLAATJES:
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cv2.imshow('window', warp_img)
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# Check voor rode balken
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cv2.imshow('window', new_image)
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cv2.imshow('cropped', crop_img)
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if SAVE:
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cv2.imwrite(out_filename, crop_img)
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if PAUZE or PLAATJES:
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cv2.waitKey(0)
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if VERBOSE:
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print("=============================================")
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cv2.destroyAllWindows()
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# Keur af of sla op
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# cv2.imwrite(out_filename, new_image)
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cv2.waitKey(0)
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cv2.destroyAllWindows
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