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hello anyone answer me how to pass command line arguments through python and how this error occurs usage: object_size.py [-h] -i IMAGE -w WIDTH object_size.py: error: argument -i/--image is required in this below code

from scipy.spatial import distance as dist from imutils import perspective from imutils import contours import numpy as np import argparse import imutils import cv2

def midpoint(ptA, ptB): return ((ptA[0] + ptB[0]) * 0.5, (ptA[1] + ptB[1]) * 0.5)

construct the argument parse and parse the arguments

ap = argparse.ArgumentParser() ap.add_argument("-i", "--image", required=True, help="path to the input image") ap.add_argument("-w", "--width", type=float, required=True, help="width of the left-most object in the image (in inches)") args = vars(ap.parse_args()) image = cv2.imread(args["image"]) gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) gray = cv2.GaussianBlur(gray, (7, 7), 0)

perform edge detection, then perform a dilation + erosion to

close gaps in between object edges

edged = cv2.Canny(gray, 50, 100) edged = cv2.dilate(edged, None, iterations=1) edged = cv2.erode(edged, None, iterations=1)

find contours in the edge map

cnts = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) cnts = cnts[0] if imutils.is_cv2() else cnts[1]

sort the contours from left-to-right and initialize the

'pixels per metric' calibration variable

(cnts, _) = contours.sort_contours(cnts) pixelsPerMetric = None for c in cnts: # if the contour is not sufficiently large, ignore it if cv2.contourArea(c) < 100: continue

# compute the rotated bounding box of the contour
orig = image.copy()
box = cv2.minAreaRect(c)
box = cv2.cv.BoxPoints(box) if imutils.is_cv2() else cv2.boxPoints(box)
box = np.array(box, dtype="int")

# order the points in the contour such that they appear
# in top-left, top-right, bottom-right, and bottom-left
# order, then draw the outline of the rotated bounding
# box
box = perspective.order_points(box)
cv2.drawContours(orig, [box.astype("int")], -1, (0, 255, 0), 2)

# loop over the original points and draw them
for (x, y) in box:
    cv2.circle(orig, (int(x), int(y)), 5, (0, 0, 255), -1)

(tl, tr, br, bl) = box (tltrX, tltrY) = midpoint(tl, tr) (blbrX, blbrY) = midpoint(bl, br)

compute the midpoint between the top-left and top-right points,

followed by the midpoint between the top-righ and bottom-right

(tlblX, tlblY) = midpoint(tl, bl) (trbrX, trbrY) = midpoint(tr, br)

draw the midpoints on the image

cv2.circle(orig, (int(tltrX), int(tltrY)), 5, (255, 0, 0), -1) cv2.circle(orig, (int(blbrX), int(blbrY)), 5, (255, 0, 0), -1) cv2.circle(orig, (int(tlblX), int(tlblY)), 5, (255, 0, 0), -1) cv2.circle(orig, (int(trbrX), int(trbrY)), 5, (255, 0, 0), -1)

draw lines between the midpoints

cv2.line(orig, (int(tltrX), int(tltrY)), (int(blbrX), int(blbrY)), (255, 0, 255), 2) cv2.line(orig, (int(tlblX), int(tlblY)), (int(trbrX), int(trbrY)), (255, 0, 255), 2) dA = dist.euclidean((tltrX, tltrY), (blbrX, blbrY)) dB = dist.euclidean((tlblX, tlblY), (trbrX, trbrY))

if the pixels per metric has not been initialized, then

compute it as the ratio of pixels to supplied metric

(in this case, inches)

if pixelsPerMetric is None: pixelsPerMetric = dB / args["width"] dimA = dA / pixelsPerMetric dimB = dB / pixelsPerMetric

draw the object sizes on the image

cv2.putText(orig, "{:.1f}in".format(dimA), (int(tltrX - 15), int(tltrY - 10)), cv2.FONT_HERSHEY_SIMPLEX, 0.65, (255, 255, 255), 2) cv2.putText(orig, "{:.1f}in".format(dimB), (int(trbrX + 10), int(trbrY)), cv2.FONT_HERSHEY_SIMPLEX, 0.65, (255, 255, 255), 2)

show the output image

cv2.imshow("Image", orig) cv2.waitKey(0)

hello anyone answer me how to pass command line arguments through python and how this error occurs usage: object_size.py [-h] -i IMAGE -w WIDTH object_size.py: error: argument -i/--image is required in this below code

from scipy.spatial import distance as dist from imutils import perspective from imutils import contours import numpy as np import argparse import imutils import cv2cv2 ... def midpoint(ptA, ptB): return ((ptA[0] + ptB[0]) * 0.5, (ptA[1] + ptB[1]) * 0.5) # construct the argument parse and parse the arguments arguments ap = argparse.ArgumentParser() ap.add_argument("-i", "--image", required=True, help="path to the input image") ap.add_argument("-w", "--width", type=float, required=True, help="width of the left-most object in the image (in inches)") args = vars(ap.parse_args()) image = cv2.imread(args["image"]) gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) gray = cv2.GaussianBlur(gray, (7, 7), 0) perform edge detection, then perform a dilation + erosion to close gaps in between object edges edged = cv2.Canny(gray, 50, 100) edged = cv2.dilate(edged, None, iterations=1) edged = cv2.erode(edged, None, iterations=1) find contours in the edge map cnts = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) cnts = cnts[0] if imutils.is_cv2() else cnts[1] sort the contours from left-to-right and initialize the 'pixels per metric' calibration variable (cnts, _) = contours.sort_contours(cnts) pixelsPerMetric = None for c in cnts: # if the contour is not sufficiently large, ignore it if cv2.contourArea(c) < 100: continue # compute the rotated bounding box of the contour orig = image.copy() box = cv2.minAreaRect(c) box = cv2.cv.BoxPoints(box) if imutils.is_cv2() else cv2.boxPoints(box) box = np.array(box, dtype="int") # order the points in the contour such that they appear # in top-left, top-right, bottom-right, and bottom-left # order, then draw the outline of the rotated bounding # box box = perspective.order_points(box) cv2.drawContours(orig, [box.astype("int")], -1, (0, 255, 0), 2) # loop over the original points and draw them for (x, y) in box: cv2.circle(orig, (int(x), int(y)), 5, (0, 0, 255), -1) ... (tl, tr, br, bl) = box (tltrX, tltrY) = midpoint(tl, tr) (blbrX, blbrY) = midpoint(bl, br) compute the midpoint between the top-left and top-right points, followed by the midpoint between the top-righ and bottom-right (tlblX, tlblY) = midpoint(tl, bl) (trbrX, trbrY) = midpoint(tr, br) draw the midpoints on the image cv2.circle(orig, (int(tltrX), int(tltrY)), 5, (255, 0, 0), -1) cv2.circle(orig, (int(blbrX), int(blbrY)), 5, (255, 0, 0), -1) cv2.circle(orig, (int(tlblX), int(tlblY)), 5, (255, 0, 0), -1) cv2.circle(orig, (int(trbrX), int(trbrY)), 5, (255, 0, 0), -1) draw lines between the midpoints cv2.line(orig, (int(tltrX), int(tltrY)), (int(blbrX), int(blbrY)), (255, 0, 255), 2) cv2.line(orig, (int(tlblX), int(tlblY)), (int(trbrX), int(trbrY)), (255, 0, 255), 2) dA = dist.euclidean((tltrX, tltrY), (blbrX, blbrY)) dB = dist.euclidean((tlblX, tlblY), (trbrX, trbrY)) if the pixels per metric has not been initialized, then compute it as the ratio of pixels to supplied metric (in this case, inches) if pixelsPerMetric is None: pixelsPerMetric = dB / args["width"] dimA = dA / pixelsPerMetric dimB = dB / pixelsPerMetric draw the object sizes on the image cv2.putText(orig, "{:.1f}in".format(dimA), (int(tltrX - 15), int(tltrY - 10)), cv2.FONT_HERSHEY_SIMPLEX, 0.65, (255, 255, 255), 2) cv2.putText(orig, "{:.1f}in".format(dimB), (int(trbrX + 10), int(trbrY)), cv2.FONT_HERSHEY_SIMPLEX, 0.65, (255, 255, 255), 2) show the output image cv2.imshow("Image", orig) cv2.waitKey(0)