Develop Reference

How to make a mesh within rectangle using drawing functions of the OpenCV?

This is my full code.
import cv2
import numpy as np
cap = cv2.VideoCapture(0)
width = cap.get(3) # float
height = cap.get(4) # float
print (width, height)
while (1):
_, img = cap.read()
if _ is True:
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
else:
continue
# blue color
blue_lower = np.array([86,0,90], np.uint8)
blue_upper = np.array([163, 64, 145], np.uint8)
blue = cv2.inRange(hsv, blue_lower, blue_upper)
kernal = np.ones((9, 9), "uint8")
blue = cv2.dilate(blue, kernal)
res_blue = cv2.bitwise_and(img, img, mask=blue)
# Tracking blue
(_, contours, hierarchy) = cv2.findContours(blue, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for pic, contour in enumerate(contours):
area = cv2.contourArea(contour)
if (area > 2000):
print (area)
x, y, w, h = cv2.boundingRect(contour)
img = cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
cv2.putText(img, "Blue Colour", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 0, 0))
# cv2.putText(img, "Blue Colour", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 0, 0))
cv2.imshow("Color Tracking", img)
if cv2.waitKey(10) & 0xFF == ord('q'):
cap.release()
cv2.destroyAllWindows()
break
I would like to mesh all rectangles as these pictures.
you can see the mesh of the contour next to them.
In my case, I would like to mesh rectangles themselves.
This picture is taken from this video

detect a single shape and colour in realtime using opencv

I'm working on a project that requires me to detect a red rectangle in real time. so far I've managed to get the colour and shape detected together but it can't differentiate between other objects that are red.
How might I go about doing this?
import cv2
import numpy as np
def nothing():
pass
cap = cv2.VideoCapture(0)
font = cv2.FONT_HERSHEY_COMPLEX
while True:
_, frame = cap.read()
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
# Red color
low_red = np.array([175, 50, 20])
high_red = np.array([180, 255, 255])
mask1 = cv2.inRange(hsv, low_red, high_red)
kernel = np.ones((5, 5), np.uint8)
mask2 = cv2.erode(mask1, kernel)
red = cv2.bitwise_and(frame, frame, mask=mask2)
contours, _ = cv2.findContours(mask2, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for cnt in contours:
area = cv2.contourArea(cnt)
approx = cv2.approxPolyDP(cnt, 0.02 * cv2.arcLength(cnt, True), True)
hull = cv2.convexHull(cnt)
x = approx.ravel()[0]
y = approx.ravel()[1]
if area > 400:
cv2.drawContours(frame, [approx], 0, (0, 0, 0), 5)
if len(approx) == 4:
cv2.putText(frame, "Rectangle", (x, y), font, 1, (0, 0, 0))
edges = cv2.Canny(frame, 100, 200)
_, threshold_binary = cv2.threshold(frame, 128, 255, cv2.THRESH_BINARY)
_, threshold_binary_inv = cv2.threshold(frame, 128, 255, cv2.THRESH_BINARY_INV)
_, threshold_trunc = cv2.threshold(frame, 128, 255, cv2.THRESH_TRUNC)
_, threshold_to_zero = cv2.threshold(frame, 12, 255, cv2.THRESH_TOZERO)
cv2.imshow("Frame", frame)
cv2.imshow('edges', edges)
cv2.imshow('red', red)
cv2.imshow("mask", mask1)
key = cv2.waitKey(1)
if key == 27:
cap.release()
cv2.destroyAllWindows()
break
Output image:

How do I fix openCV cvtColor error in my project?

I am building handwriting recognition project but I am getting this error of cvtColor while trying to change the image from BGR2HSV.
cap = cv2.VideoCapture(0)
Lower_blue = np.array([110, 50, 50])
Upper_blue = np.array([130, 255, 255])
pred_class = 0
pts = deque(maxlen = 512)
blackboard = np.zeros((480, 640, 3), dtype = np.uint8)
digit = np.zeros((200, 200, 3), dtype = np.uint8)
while(cap.isOpened()):
ret, img = cap.read()
img = cv2.flip(img, 1)
imgHSV = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(imgHSV, Lower_blue, Upper_blue)
blur = cv2.medianBlur(mask, 15)
blur = cv2.GaussianBlur(blur, (5, 5), 0)
thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
cnts = cv2.findContours(thresh.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)[1]
center = None
if len(cnts) >= 1:
contour = max(cnts, key = cv2.contourArea)
if cv2.contourArea(contour) > 250:
((x, y), radius) = cv2.minEnclosingCircle(contour)
cv2.circle(img, (int(x), int(y)), int(radius), (0, 255, 255), 2)
cv2.circle(img, center, 5, (0, 255, 255), -1)
M = cv2.moments(contour)
center = (int(M['m10'] / M['m00']), int(M['m01'] / M['m00']))
pts.appendleft(center)
for i in range (1, len(pts)):
if pts[i - 1] is None or pts[i] is None:
continue
cv2.line(blackboard, pts[i - 1], pts[i], (255, 255, 255), 10)
cv2.line(img, pts[i - 1], pts[i], (0, 0,255), 5)
elif len(cnts) == 0:
if len(pts) != []:
blackboard_gray = cv2.cvtColor(blackboard, cv2.COLOR_BGR2GRAY)
blur1 = cv2.medianBlur(blackboard_gray, 15)
blur1 = cv2.GaussianBlur(blur1, (5, 5), 0)
thresh1 = cv2.threshold(blur1, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
blackboard_cnts = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)[1]
if len(blackboard_cnts) >= 1:
cnt = max(blackboard_cnts, key = cv2.contourArea)
print(cv2.contourArea(cnt))
if cv2.contourArea(cnt) > 2000:
x, y, w, h = cv2.boundingRect(cnt)
digit = blackboard_gray[y:y + h, x:x + w]
#new Image = process_letter(digit)
pred_probab, pred_class = keras_predict(model1, digit)
print(pred_class, pred_probab)
pts = deque(maxlen = 512)
blackboard = np.zeros((480, 640, 3), dtype = uint8)
cv2.putText(img, "Conv Network : " + str(letter_count [pred_class]), (10, 470),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
cv2.imshow("Frame", img)
cv2.imshow("Contours", thresh)
k = cv2.waitkey(10)
if k == 27:
break
How do I fix this issue of OpenCV error? Please help!
I am getting following error:
error: OpenCV(3.4.1) C:\Miniconda3\conda-bld\opencv-suite_1533128839831\work\modules\imgproc\src\color.cpp:11214: error: (-215) (scn == 3 || scn == 4) && (depth == 0 || depth == 5) in function cv::cvtColor

I think following error: error: (-215) (scn == 3 || scn == 4) && (depth == 0 || depth == 5) in function cv::cvtColor is because of camera unable to capture frame correctly. Check this by printing ret value. It camera is able to capture frame correctly, it will return True, else False. Above error is happening because None is passed to cv2.cvtColor function. You can use below code as a safety check:
if ret is True:
# your code goes here
else:
break
Moreover, please consider below points:
It's cv2.waitKey(10), not cv2.waitkey(10)[Capital 'K']
cv2.findContours function return 3 values(i.e. image, contours and hierarchy) in OpenCV 3.x but just 2 values(i.e. contours, hierarchy) in openCV 4.x
len(pts) != [] doesn't make sense. Here, you are trying to compare a number to an empty list. Change it to len(pts) != 0.
What's letter_count inside cv2.putText function. Kindly recheck it.
In place of re-initializing deque(pts = deque(maxlen = 512)) in case of len(cnts)==0 and len(pts) != 0, you can use the old pts by simply clearing it using pts.clear(). Just a thought!
Also, add below code at the end:
cap.release()
cv2.destroyAllWindows()
Try below modified code(Tested using openCV v4.0.0):
import cv2
import numpy as np
from collections import deque
cap = cv2.VideoCapture(0)
Lower_blue = np.array([110, 50, 50])
Upper_blue = np.array([130, 255, 255])
pred_class = 0
pts = deque(maxlen = 512)
blackboard = np.zeros((480, 640, 3), dtype = np.uint8)
digit = np.zeros((200, 200, 3), dtype = np.uint8)
while(cap.isOpened()):
ret, img = cap.read()
img = cv2.flip(img, 1)
imgHSV = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(imgHSV, Lower_blue, Upper_blue)
blur = cv2.medianBlur(mask, 15)
blur = cv2.GaussianBlur(blur, (5, 5), 0)
thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
cnts = cv2.findContours(thresh.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)[0]
center = None
if len(cnts) >= 1:
contour = max(cnts, key = cv2.contourArea)
if cv2.contourArea(contour) > 250:
((x, y), radius) = cv2.minEnclosingCircle(contour)
cv2.circle(img, (int(x), int(y)), int(radius), (0, 255, 255), 2)
cv2.circle(img, center, 5, (0, 255, 255), -1)
M = cv2.moments(contour)
center = (int(M['m10'] / M['m00']), int(M['m01'] / M['m00']))
pts.appendleft(center)
# print(pts)
for i in range (1, len(pts)):
if pts[i - 1] is None or pts[i] is None:
print("Continue")
continue
cv2.line(blackboard, pts[i - 1], pts[i], (255, 255, 255), 10)
cv2.line(img, pts[i - 1], pts[i], (0, 0,255), 5)
cv2.imshow("Frame", img)
cv2.imshow("Contours", thresh)
# press q to stop
if cv2.waitKey(1) & 0xFF == ord('q'):
break
else:
if len(pts) != 0:
blackboard_gray = cv2.cvtColor(blackboard, cv2.COLOR_BGR2GRAY)
blur1 = cv2.medianBlur(blackboard_gray, 15)
blur1 = cv2.GaussianBlur(blur1, (5, 5), 0)
thresh1 = cv2.threshold(blur1, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
print('Hello')
blackboard_cnts = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)[0]
if len(blackboard_cnts) >= 1:
cnt = max(blackboard_cnts, key = cv2.contourArea)
print(cv2.contourArea(cnt))
if cv2.contourArea(cnt) > 2000:
x, y, w, h = cv2.boundingRect(cnt)
digit = blackboard_gray[y:y + h, x:x + w]
#new Image = process_letter(digit)
#pred_probab, pred_class = keras_predict(model1, digit)
print(digit.shape)
#pts = deque(maxlen = 512)
pts.clear()
blackboard = np.zeros((480, 640, 3), dtype = np.uint8)
#cv2.putText(img, "Conv Network : " + str(letter_count[pred_class]), (10, 470), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
cv2.putText(img, "Conv Network :", (10, 470), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
cv2.imshow("Frame", img)
cv2.imshow("Contours", thresh)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()

Opencv python distance calculation strange square detection

Heii Im unisng raspberry pi and pi camera to read the distance between pi cand object (square box). im using perimeter of the contour and divide by 4 and getting one side length , then by Distance = (length x known length) / calculated one side length.
I'm always having a square which is the whole frame of the camera window and getting a distance. How to avoid the whole frame window square.
https://drive.google.com/open?id=15-kd32Zd_tZeMPWQ2I1s9_NJGYg3v_9l
any idea why it comes and how to eliminate it ?
import cv2
import numpy as np
import time
def nothing(x):
# any operation
pass
cap = cv2.VideoCapture(0)
font = cv2.FONT_HERSHEY_COMPLEX
while True:
_, frame = cap.read()
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
l_h = 0
l_s = 0
l_v = 42
u_h = 180
u_s = 255
u_v = 255
lower_red = np.array([l_h, l_s, l_v])
upper_red = np.array([u_h, u_s, u_v])
mask = cv2.inRange(hsv, lower_red, upper_red)
kernel = np.ones((5, 5), np.uint8)
mask = cv2.erode(mask, kernel)
# Contours detection
contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for cnt in contours:
area = cv2.contourArea(cnt)
approx = cv2.approxPolyDP(cnt, 0.02*cv2.arcLength(cnt, True), True)
x = approx.ravel()[0]
y = approx.ravel()[1]
perimeter = cv2.arcLength(cnt,True)
if area > 200:
cv2.drawContours(frame, [approx], 0, (0, 0, 0), 5)
if len(approx) == 3:
cv2.putText(frame, "triangle " , (x, y), font, 1, (0, 0, 0))
print("Traingle is detected and distance is = ",((154*58)/(perimeter/3))*0.2645 , "mm")
elif len(approx) == 4:
cv2.putText(frame, "square", (x, y), font, 1, (0, 0, 0))
#print(perimeter/4)
print("Square is detected and distance is = ",((154*58)/(perimeter/4))*0.2645 , "mm")
#print("square distance is = ",((149*58)/(perimeter/4))*0.2645 , "mm")
elif len(approx) == 5:
cv2.putText(frame, "Pentogon", (x, y), font, 1, (0, 0, 0))
print("Pentogon is detected and distance is = ",((151*58)/(perimeter/5))*0.2645 , "mm")
elif len(approx) == 6:
cv2.putText(frame, "6angle", (x, y), font, 1, (0, 0, 0))
cv2.imshow("Frame", frame)
cv2.imshow("Mask", mask)
key = cv2.waitKey(1)
if key == 0:
break
cap.release()
cv2.destroyAllWindows()

"no module named imutils" when it says imutils is installed?

I want to run this code on my Raspberry Pi 3. I have used pip install imutils on the Pi but, when I run the code via the CLI, it returns "No module named imutils". I do not wish to use virtual environments. I have cv2 running correctly on the Pi and that works no problem, is there a fix for this imutils problem?
Updating, upgrading, removing imutils but it is needed.
import numpy as np
import cv2
import Person
import time
import imutils
import datetime
cap = cv2.VideoCapture('testVideo.mp4')
fgbg = cv2.createBackgroundSubtractorMOG2(detectShadows=True) # Create the background substractor
kernelOp = np.ones((3, 3), np.uint8)
kernelOp1 = np.ones((7, 7), np.uint8)
kernelOp2 = np.ones((5, 5), np.uint8)
kernelCl = np.ones((11, 11), np.uint8)
kernelCl1 = np.ones((20, 20), np.uint8)
kernelCl2 = np.ones((25, 25), np.uint8)
# Variables
font = cv2.FONT_HERSHEY_SIMPLEX
persons = []
max_p_age = 5
pid = 1
areaTH = 5000
w_margin = 50
h_margin = 50
wmax = 500
import pdb;
pdb.set_trace() # debuginimo pradzia
# Atvaizdavimo kintamieji
cnt_up = 0
cnt_down = 0
line_down_color = (255, 0, 0)
line_up_color = (0, 0, 255)
pts_L1 = np.array([[0, 320], [480, 320]])
pts_L2 = np.array([[0, 400], [480, 400]])
counter = 0
while (cap.isOpened()):
ret, frame = cap.read() # read a frame
frame = imutils.resize(frame, width=min(640, frame.shape[1]))
fgmask = fgbg.apply(frame) # Use the substractor
try:
ret, imBin = cv2.threshold(fgmask, 200, 255, cv2.THRESH_BINARY)
mask0 = cv2.morphologyEx(imBin, cv2.MORPH_OPEN, kernelOp2)
mask = cv2.morphologyEx(mask0, cv2.MORPH_CLOSE, kernelCl2)
except:
# if there are no more frames to show...
print('EOF')
break
maskOriginal = mask
_, contours0, hierarchy = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
########if contour is too big cut in half
mask2_flag = 0
for cnt in contours0:
area = cv2.contourArea(cnt)
if area > areaTH:
M = cv2.moments(cnt)
cx = int(M['m10'] / M['m00'])
cy = int(M['m01'] / M['m00'])
x, y, w, h = cv2.boundingRect(cnt)
if w > wmax:
mask2 = cv2.line(mask, ((x + w / 2), 0), ((x + w / 2), 640), (0, 0, 0), 10)
mask2_flag = 1
if mask2_flag == 0:
mask2 = mask
cv2.imshow('Mask line', mask2)
cv2.imshow('mask to open', mask0)
cv2.imshow('Mask initialize', maskOriginal)
cv2.imshow('initial subtraction', imBin)
_, contours0, hierarchy = cv2.findContours(mask2, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
for cnt in contours0:
cv2.drawContours(frame, cnt, -1, (0, 255, 0), 3, 8)
area = cv2.contourArea(cnt)
for i in persons:
i.updateDingimas(i.getDingimas() + 1)
if i.getDingimas() > 25:
persons.remove(i)
if area > areaTH:
M = cv2.moments(cnt)
cx = int(M['m10'] / M['m00'])
cy = int(M['m01'] / M['m00'])
x, y, w, h = cv2.boundingRect(cnt)
print('x{} y{} w{} h{}'.format(x, y, w, h))
new = True
for i in persons:
if abs(x - i.getX()) <= w_margin and abs(y - i.getY()) <= h_margin:
new = False
i.updateCoords(cx, cy)
i.updateDingimas(0)
break
if new == True:
p = Person.MyPerson(pid, cx, cy, max_p_age)
persons.append(p)
pid += 1
cv2.circle(frame, (cx, cy), 5, (0, 0, 255), -1)
img = cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.drawContours(frame, cnt, -1, (0, 255, 0), 3)
cv2.imshow('img', img)
#########################
# Trajectory rendering
#########################
for i in persons:
if len(i.getTracks()) >= 2:
pts = np.array(i.getTracks(), np.int32)
pts = pts.reshape((-1, 1, 2))
frame = cv2.polylines(frame, [pts], False, i.getRGB())
if i.getDir() == None:
i.kurEina(pts_L2[0, 1], pts_L1[0, 1])
if i.getDir() == 'up':
cnt_up += 1
print('Timestamp: {:%H:%M:%S} UP {}'.format(datetime.datetime.now(), cnt_up))
elif i.getDir() == 'down':
cnt_down += 1
print('Timestamp: {:%H:%M:%S} DOWN {}'.format(datetime.datetime.now(), cnt_down))
cv2.putText(frame, str(i.getId()), (i.getX(), i.getY()), font, 0.7, i.getRGB(), 1, cv2.LINE_AA)
#########################
# Rendering
#########################
str_in = 'In: ' + str(cnt_up)
str_out = 'Out: ' + str(cnt_down)
frame = cv2.polylines(frame, [pts_L1], False, line_down_color, thickness=4)
frame = cv2.polylines(frame, [pts_L2], False, line_up_color, thickness=4)
cv2.putText(frame, str_in, (10, 50), font, 1, (0, 0, 255), 2, cv2.LINE_AA)
cv2.putText(frame, str_out, (10, 100), font, 1, (255, 0, 0), 2, cv2.LINE_AA)
cv2.imshow('Frame', frame)
# Abort and exit with 'Q' or ESC
k = cv2.waitKey(30) & 0xff
if k == 27:
break
cap.release() # release video file
cv2.destroyAllWindows() # close all openCV windows
I want to run this code without "No module named imutils" error.

If you intend to use the module with Python 3, you need to install it with pip3 so that it is installed in the correct location.