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92 lines
2.8 KiB
Python
92 lines
2.8 KiB
Python
from scipy.spatial import distance as dist
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from imutils import perspective
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from imutils import contours
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import argparse
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import numpy as np
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import imutils
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import cv2
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def midpoint(ptA, ptB):
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return ((ptA[0] + ptB[0]) * 0.5, (ptA[1] + ptB[1]) * 0.5)
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def show_image(title, image, destroy_all=True):
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cv2.imshow(title, image)
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cv2.waitKey(0)
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if destroy_all:
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cv2.destroyAllWindows()
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ap = argparse.ArgumentParser()
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ap.add_argument("-i", "--image", required=True, help="path to the input image")
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ap.add_argument("-w", "--width", type=float, required=True, help="width of the left-most object in the image (in inches)")
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args = vars(ap.parse_args())
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image = cv2.imread(args["image"])
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gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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gray = cv2.GaussianBlur(gray, (7, 7), 0)
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edged = cv2.Canny(gray, 50, 100)
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show_image("Edged", edged, False)
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edged = cv2.dilate(edged, None, iterations=1)
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edged = cv2.erode(edged, None, iterations=1)
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show_image("erode and dilate", edged, True)
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cnts = cv2.findContours(edged, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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cnts = imutils.grab_contours(cnts)
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print("Total number of contours are: ", len(cnts))
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(cnts, _) = contours.sort_contours(cnts)
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pixelPerMetric = None
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count = 0
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for c in cnts:
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if cv2.contourArea(c) < 100:
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continue
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count += 1
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orig = image.copy()
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box = cv2.minAreaRect(c)
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box = cv2.cv.BoxPoints(box) if imutils.is_cv2() else cv2.boxPoints(box)
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box = np.array(box, dtype="int")
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box = perspective.order_points(box)
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cv2.drawContours(orig, [box.astype("int")], -1, (0, 255, 0), 2)
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for (x, y) in box:
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cv2.circle(orig, (int(x), int(y)), 5, (0, 0, 255), -1)
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(tl, tr, br, bl) = box
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(tltrX, tltrY) = midpoint(tl, tr)
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(blbrX, blbrY) = midpoint(bl, br)
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(tlblX, tlblY) = midpoint(tl, bl)
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(trbrX, trbrY) = midpoint(tr, br)
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cv2.circle(orig, (int(tltrX), int(tltrY)), 5, (255, 0, 0), -1)
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cv2.circle(orig, (int(blbrX), int(blbrY)), 5, (255, 0, 0), -1)
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cv2.circle(orig, (int(tlblX), int(tlblY)), 5, (255, 0, 0), -1)
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cv2.circle(orig, (int(trbrX), int(trbrY)), 5, (255, 0, 0), -1)
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cv2.line(orig, (int(tltrX), int(tltrY)), (int(blbrX), int(blbrY)), (255, 0, 255), 2)
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cv2.line(orig, (int(tlblX), int(tlblY)), (int(trbrX), int(trbrY)), (255, 0, 255), 2)
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dA = dist.euclidean((tltrX, tltrY), (blbrX, blbrY))
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dB = dist.euclidean((tlblX, tlblY), (trbrX, trbrY))
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if pixelPerMetric is None:
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pixelPerMetric = dB / args["width"]
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dimA = dA / pixelPerMetric
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dimB = dB / pixelPerMetric
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cv2.putText(orig, "{:.1f}in".format(dimA), (int(tltrX - 15), int(tltrY - 10)), cv2.FONT_HERSHEY_SIMPLEX, 0.65, (255, 255, 255), 2)
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cv2.putText(orig, "{:.1f}in".format(dimB), (int(trbrX + 10), int(trbrY)), cv2.FONT_HERSHEY_SIMPLEX, 0.65, (255, 255, 255), 2)
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cv2.imshow("Image", orig)
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cv2.waitKey(0)
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print("Total contours processed: ", count)
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