|
| 1 | +# To detect the position, shape and color of an image. |
| 2 | + |
| 3 | +import cv2 |
| 4 | +import numpy as np |
| 5 | +import os |
| 6 | +import argparse |
| 7 | +import imutils |
| 8 | +import math |
| 9 | +from os.path import join,isfile |
| 10 | +filename = 'outputimage.csv' |
| 11 | + |
| 12 | +#subroutine to write results to a csv |
| 13 | +def writecsv(color,shape,(cx,cy)): |
| 14 | + global filename |
| 15 | + |
| 16 | + filep = open(filename,'a') |
| 17 | + |
| 18 | + datastr = "," + color + "-" + shape + "-" + str(cx) + "-" + str(cy) |
| 19 | + |
| 20 | + filep.write(datastr) |
| 21 | + filep.close() |
| 22 | + |
| 23 | +def detectShape(image, c, cX, cY, color, ll): |
| 24 | + peri = cv2.arcLength(c, True) |
| 25 | + approx = cv2.approxPolyDP(c, 0.04 * peri, True) |
| 26 | + # CHECKING NO. OF VERTICES |
| 27 | + if len(approx) == 3: |
| 28 | + shape = "TRIANGLE" |
| 29 | + |
| 30 | + elif len(approx) == 4: |
| 31 | + |
| 32 | + (x, y, w, h) = cv2.boundingRect(approx) |
| 33 | + ar = w / float(h) |
| 34 | + rect_diagonal = math.sqrt(w * w + h * h) |
| 35 | + |
| 36 | + (x, y), radius = cv2.minEnclosingCircle(c) |
| 37 | + center = (int(x), int(y)) |
| 38 | + |
| 39 | + radius = int(radius) |
| 40 | + diameter = 2 * radius |
| 41 | + error = diameter / rect_diagonal |
| 42 | + if ar >= 0.95 and ar <= 1.05: |
| 43 | + shape = 'SQUARE' |
| 44 | + |
| 45 | + elif error >= 0.9 and error <= 1.1: |
| 46 | + shape = 'RHOMBUS' |
| 47 | + else: |
| 48 | + shape = 'TRAPEZIUM' |
| 49 | + elif len(approx) == 5: |
| 50 | + shape = "PENTAGON" |
| 51 | + |
| 52 | + elif len(approx) == 6: |
| 53 | + shape = "HEXAGON" |
| 54 | + else: |
| 55 | + shape = "CIRCLE" |
| 56 | + |
| 57 | + cv2.putText(image, shape, (cX-25, cY), cv2.FONT_HERSHEY_SIMPLEX,0.5, (255, 255, 255), 1) |
| 58 | + writecsv(color, shape, (cX,cY)) |
| 59 | + ll.append([color+'-'+shape+'-'+str(cX)+'-'+str(cY)]) |
| 60 | + |
| 61 | +def main(path): |
| 62 | + image = cv2.imread(path) |
| 63 | + |
| 64 | + resized = imutils.resize(image, width=300) |
| 65 | + ratio = image.shape[0] / float(resized.shape[0]) |
| 66 | + hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) |
| 67 | + # CONVERT IN GRAYSCALE THEN BLURRED IT THEN FIND THRESHOLD |
| 68 | + gray = cv2.cvtColor(resized, cv2.COLOR_BGR2GRAY) |
| 69 | + blurred = cv2.GaussianBlur(gray, (5, 5), 0) |
| 70 | + thresh = cv2.threshold(blurred, 100, 255, cv2.THRESH_BINARY)[1] |
| 71 | + |
| 72 | + cnts = cv2.findContours(thresh, 1, 2) |
| 73 | + cnts = cnts[0] if imutils.is_cv2() else cnts[1] |
| 74 | + |
| 75 | + |
| 76 | + #DETECTING COLOUR |
| 77 | + |
| 78 | + # define range of green color in HSV |
| 79 | + lower = np.array([50, 50, 120]) |
| 80 | + upper = np.array([70, 255, 255]) |
| 81 | + shapemask = cv2.inRange(hsv, lower, upper) |
| 82 | + |
| 83 | + # define range of blue color in HSV |
| 84 | + lower_blue = np.array([110, 50, 50]) |
| 85 | + upper_blue = np.array([130, 255, 255]) |
| 86 | + blue_mask = cv2.inRange(hsv, lower_blue, upper_blue) |
| 87 | + |
| 88 | + # define range of red color in HSV |
| 89 | + lower_red = np.array([0, 50, 50]) |
| 90 | + upper_red = np.array([10, 255, 255]) |
| 91 | + red_mask = cv2.inRange(hsv, lower_red, upper_red) |
| 92 | + |
| 93 | + hsv, cnts, _ = cv2.findContours(shapemask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) |
| 94 | + hsv, cnts1, _ = cv2.findContours(blue_mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) |
| 95 | + hsv, cnts2, _ = cv2.findContours(red_mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) |
| 96 | + |
| 97 | + ll = [path] |
| 98 | + for c in cnts: |
| 99 | + M = cv2.moments(c) |
| 100 | + cgX = int((M["m10"] / M["m00"])) |
| 101 | + cgY = int((M["m01"] / M["m00"])) |
| 102 | + cv2.putText(image, '('+str(cgX)+','+str(cgY)+')', (cgX-25, cgY+15), cv2.FONT_HERSHEY_SIMPLEX,0.5, (255, 255, 255), 1) |
| 103 | + cv2.putText(image, 'GREEN', (cgX - 20, cgY + 30), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1) |
| 104 | + detectShape(image, c, cgX, cgY, 'GREEN', ll) |
| 105 | + for c in cnts1: |
| 106 | + M = cv2.moments(c) |
| 107 | + cbX = int((M["m10"] / M["m00"])) |
| 108 | + cbY = int((M["m01"] / M["m00"])) |
| 109 | + cv2.putText(image, '('+str(cbX)+','+str(cbY)+')', (cbX-25, cbY+15), cv2.FONT_HERSHEY_SIMPLEX,0.5, (255, 255, 255), 1) |
| 110 | + cv2.putText(image, 'BLUE', (cbX - 20, cbY + 30), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1) |
| 111 | + detectShape(image, c, cbX, cbY, 'BLUE', ll) |
| 112 | + |
| 113 | + for c in cnts2: |
| 114 | + M = cv2.moments(c) |
| 115 | + crX = int((M["m10"] / M["m00"])) |
| 116 | + crY = int((M["m01"] / M["m00"])) |
| 117 | + font = cv2.FONT_HERSHEY_SIMPLEX |
| 118 | + cv2.putText(image, '('+str(crX)+','+str(crY)+')', (crX-25, crY+15), cv2.FONT_HERSHEY_SIMPLEX,0.5, (255, 255, 255), 1) |
| 119 | + cv2.putText(image, 'RED', (crX - 25, crY + 30), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1) |
| 120 | + detectShape(image, c, crX, crY, 'RED', ll) |
| 121 | + |
| 122 | + cv2.imshow("image", image) |
| 123 | + cv2.imwrite( path[0:len(path)-4]+"output.png", image ); |
| 124 | + cv2.waitKey(0) |
| 125 | + return ll |
| 126 | +if __name__ == "__main__": |
| 127 | + mypath = '.' |
| 128 | + |
| 129 | + onlyfiles = [join(mypath, f) for f in os.listdir(mypath) if f.endswith(".png")] |
| 130 | + |
| 131 | + for fp in onlyfiles: |
| 132 | + |
| 133 | + filep = open('outputimage.csv','a') |
| 134 | + |
| 135 | + filep.write(fp) |
| 136 | + |
| 137 | + filep.close() |
| 138 | + |
| 139 | + data = main(fp) |
| 140 | + print data |
| 141 | + |
| 142 | + filep = open('outputimage.csv','a') |
| 143 | + |
| 144 | + filep.write('\n') |
| 145 | + |
| 146 | + filep.close() |
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