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@benmarwick
Last active April 23, 2024 01:28
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Python 3 script to take live video, detect the largest object, trace an outline (contour) and measure linear dimensions, using OpenCV
# in a terminal
# python -m pip install --user opencv-contrib-python numpy scipy matplotlib ipython jupyter pandas sympy nose
import cv2
import pandas as pd
import numpy as np
import imutils
from scipy.spatial import distance as dist
from imutils import perspective
from imutils import contours
# using cam built-in to computer
videocapture=cv2.VideoCapture(0)
# using IP camera address from my mobile phone, with Android 'IP Webcam' app over WiFi
# videocapture=cv2.VideoCapture("http://xxx.xxx.xxx.xxx:8080/video")
def safe_div(x,y): # so we don't crash so often
if y==0: return 0
return x/y
def nothing(x): # for trackbar
pass
def rescale_frame(frame, percent=25): # make the video windows a bit smaller
width = int(frame.shape[1] * percent/ 100)
height = int(frame.shape[0] * percent/ 100)
dim = (width, height)
return cv2.resize(frame, dim, interpolation=cv2.INTER_AREA)
if not videocapture.isOpened():
print("can't open camera")
exit()
windowName="Webcam Live video feed"
cv2.namedWindow(windowName)
# Sliders to adjust image
# https://medium.com/@manivannan_data/set-trackbar-on-image-using-opencv-python-58c57fbee1ee
cv2.createTrackbar("threshold", windowName, 75, 255, nothing)
cv2.createTrackbar("kernel", windowName, 5, 30, nothing)
cv2.createTrackbar("iterations", windowName, 1, 10, nothing)
showLive=True
while(showLive):
ret, frame=videocapture.read()
frame_resize = rescale_frame(frame)
if not ret:
print("cannot capture the frame")
exit()
thresh= cv2.getTrackbarPos("threshold", windowName)
ret,thresh1 = cv2.threshold(frame_resize,thresh,255,cv2.THRESH_BINARY)
kern=cv2.getTrackbarPos("kernel", windowName)
kernel = np.ones((kern,kern),np.uint8) # square image kernel used for erosion
itera=cv2.getTrackbarPos("iterations", windowName)
dilation = cv2.dilate(thresh1, kernel, iterations=itera)
erosion = cv2.erode(dilation,kernel,iterations = itera) # refines all edges in the binary image
opening = cv2.morphologyEx(erosion, cv2.MORPH_OPEN, kernel)
closing = cv2.morphologyEx(opening, cv2.MORPH_CLOSE, kernel)
closing = cv2.cvtColor(closing,cv2.COLOR_BGR2GRAY)
_,contours,hierarchy = cv2.findContours(closing,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE) # find contours with simple approximation cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE
closing = cv2.cvtColor(closing,cv2.COLOR_GRAY2RGB)
cv2.drawContours(closing, contours, -1, (128,255,0), 1)
# focus on only the largest outline by area
areas = [] #list to hold all areas
for contour in contours:
ar = cv2.contourArea(contour)
areas.append(ar)
max_area = max(areas)
max_area_index = areas.index(max_area) # index of the list element with largest area
cnt = contours[max_area_index - 1] # largest area contour is usually the viewing window itself, why?
cv2.drawContours(closing, [cnt], 0, (0,0,255), 1)
def midpoint(ptA, ptB):
return ((ptA[0] + ptB[0]) * 0.5, (ptA[1] + ptB[1]) * 0.5)
# compute the rotated bounding box of the contour
orig = frame_resize.copy()
box = cv2.minAreaRect(cnt)
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), 1)
# 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)
# unpack the ordered bounding box, then compute the midpoint
# between the top-left and top-right coordinates, followed by
# the midpoint between bottom-left and bottom-right coordinates
(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), 1)
cv2.line(orig, (int(tlblX), int(tlblY)), (int(trbrX), int(trbrY)),(255, 0, 255), 1)
cv2.drawContours(orig, [cnt], 0, (0,0,255), 1)
# compute the Euclidean distance between the midpoints
dA = dist.euclidean((tltrX, tltrY), (blbrX, blbrY))
dB = dist.euclidean((tlblX, tlblY), (trbrX, trbrY))
# compute the size of the object
pixelsPerMetric = 1 # more to do here to get actual measurements that have meaning in the real world
dimA = dA / pixelsPerMetric
dimB = dB / pixelsPerMetric
# draw the object sizes on the image
cv2.putText(orig, "{:.1f}mm".format(dimA), (int(tltrX - 15), int(tltrY - 10)), cv2.FONT_HERSHEY_SIMPLEX, 0.65, (255, 255, 255), 2)
cv2.putText(orig, "{:.1f}mm".format(dimB), (int(trbrX + 10), int(trbrY)), cv2.FONT_HERSHEY_SIMPLEX, 0.65, (255, 255, 255), 2)
# compute the center of the contour
M = cv2.moments(cnt)
cX = int(safe_div(M["m10"],M["m00"]))
cY = int(safe_div(M["m01"],M["m00"]))
# draw the contour and center of the shape on the image
cv2.circle(orig, (cX, cY), 5, (255, 255, 255), -1)
cv2.putText(orig, "center", (cX - 20, cY - 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2)
cv2.imshow(windowName, orig)
cv2.imshow('', closing)
if cv2.waitKey(30)>=0:
showLive=False
videocapture.release()
cv2.destroyAllWindows()
@benmarwick
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quick-test-opencv-live-measurement

@sowmiyadharmalingam86
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HI

@sowmiyadharmalingam86
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Can you give me the step by step procedure to run the code. how to fix the threshold etc...

@A7med01
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A7med01 commented Nov 14, 2019

Can you give me the step by step procedure to run the code. how to fix the threshold etc...

at line 69 remove ' _,' from _,contours,hierarchy = cv2.findContours(closing,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)

@cemakgungor
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Can you help me I get this error ValueError: max() arg is an empty sequence

@ranajoy19
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hello can any one tell me why after doing the morphology operations the closing binary image is converted in to grayscale and then into RGB

@plv8419
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plv8419 commented Feb 8, 2021

Hello,
I keep getting the error: "ValueError: max() arg is an empty sequence". Anyone have a solution?

@GeraZerbetto
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Nice! Pretty handy!

@BakedBeans7
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I got this error, anyone know how to fix it?

Traceback (most recent call last):
File "C:\Users\rapto\Desktop\live video tracking.py", line 69, in
_,contours,hierarchy = cv2.findContours(closing,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE) # find contours with simple approximation cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE
ValueError: not enough values to unpack (expected 3, got 2)
[Finished in 5.7s]

@GeraZerbetto
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line 69, erase the first two characters ( _, )
Regards!

@husnejahan
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Hi
I got this error.

thresh= cv2.getTrackbarPos("threshold", windowName)
cv2.error: OpenCV(4.3.0) /io/opencv/modules/highgui/src/window_QT.cpp:462: error: (-27:Null pointer) NULL window handler in function 'icvFindTrackBarByName'

@benmarwick
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