Develop Reference

cv2.findcontours returning none in Motion Detector App

I followed a video online about motion detection using openCV however I came across the problem that the findContours function is not returning a value. Any help is appreceated.
Here is the code:
import cv2
import time
import datetime
import imutils
def motion_detection():
video_capture = cv2.VideoCapture(0, cv2.CAP_DSHOW)
time.sleep(2)
first_frame = None
while True:
frame = video_capture.read()[1]
text = 'Unoccupied'
greyscale_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gaussian_frame = cv2.GaussianBlur(greyscale_frame, (21, 21), 0)
blur_frame = cv2.blur(gaussian_frame, (5, 5))
greyscale_image = blur_frame
if first_frame is None:
first_frame = greyscale_image
else:
pass
frame = imutils.resize(frame, width=500)
frame_delta = cv2.absdiff(first_frame, greyscale_image)
# edit the ** thresh ** depending on the light/dark in room,
# change the 100(anything pixel value over 100 will become 255(white)
thresh = cv2.threshold(frame_delta, 100, 255, cv2.THRESH_BINARY)[1]
dilate_image = cv2.dilate(thresh, None, iterations=2)
cnt = cv2.findContours(dilate_image.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[1]
for c in cnt:
if cv2.contourArea(c) > 800:
(x, y, w, h) = cv2.boundingRect(
c)
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
text = 'Occupied'
# text that appears when there is motion in video feed
else:
pass
''' now draw text and timestamp on security feed '''
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(frame, '{+} Room Status: %s' % text, (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
cv2.putText(frame, datetime.datetime.now().strftime('%A %d %B %Y %I:%M:%S%p'),
(10, frame.shape[0] - 10), font, 0.35, (0, 0, 255), 1)
cv2.imshow('Security Feed', frame)
cv2.imshow('Threshold(foreground mask)', dilate_image)
cv2.imshow('Frame_delta', frame_delta)
key = cv2.waitKey(1) & 0xFF
if key == ord('q'):
cv2.destroyAllWindows()
break
if __name__ == '__main__':
motion_detection()
I have tried to debug and find the problem the code is exactly what the video said to write and I have had no luck.

Opencv Why does the contour remain if the object has disappeared?

I found a pre-written object detection program on the internet. I would like to use this to make a plastic bottle cap sensor on an assembly line that will tell me the size. Only when you move the cap out of the conveyor belt the coordinates taken from the contour stay there. Any ideas?
import cv2
from object_detector import *
import numpy as np
import time
# Load Object Detector
detector = HomogeneousBgDetector()
# Load Cap
cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 800)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 600)
while True:
_, img = cap.read()
img = img[0:600, 60:700 ]
contours = []
contours = detector.detect_objects(img)
# Draw objects boundaries
for cnt in contours:
# Get rect
rect = cv2.minAreaRect(cnt)
(x, y), (w, h), angle = rect
# Get Width and Height of the Objects by applying the Ratio pixel to cm
object_width = w
object_height = h
# Display rectangle
box = cv2.boxPoints(rect)
box = np.int0(box)
cv2.circle(img, (int(x), int(y)), 5, (0, 0, 255), -1)
cv2.polylines(img, [box], True, (255, 0, 0), 2)
cv2.putText(img, "Width {} px".format(round(object_width, 1)), (int(x - 100), int(y - 20)), cv2.FONT_HERSHEY_PLAIN, 2, (100, 200, 0), 2)
cv2.putText(img, "Height {} px".format(round(object_height, 1)), (int(x - 100), int(y + 15)), cv2.FONT_HERSHEY_PLAIN, 2, (100, 200, 0), 2)
cv2.imshow("Image", img)
key = cv2.waitKey(1)
if key == 27:
break
cap.release()
cv2.destroyAllWindows()
object_detector.py
import cv2
class HomogeneousBgDetector():
def __init__(self):
pass
def detect_objects(self, frame):
def difference_of_Gaussians(img, k1, s1, k2, s2):
b1 = cv2.GaussianBlur(img,(k1, k1), s1)
b2 = cv2.GaussianBlur(img,(k2, k2), s2)
return b1 - b2
# Convert Image to grayscale
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
DoG_img = difference_of_Gaussians(gray, 7, 7, 17, 13)
# Create a Mask with adaptive threshold
#mask = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY_INV, 19, 5)
mask = cv2.threshold(DoG_img ,130,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)[1]
# Find contours
contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cv2.imshow("mask", mask)
objects_contours = []
for cnt in contours:
area = cv2.contourArea(cnt)
if area > 2000:
objects_contours.append(cnt)
return objects_contours
I tried to create the contour variable empty before, but failed:
....
_, img = cap.read()
img = img[0:600, 60:700 ]
contours = []# here
contours = detector.detect_objects(img)
# Draw objects boundaries
for cnt in contours:
.....
the picture:

Eran and Christoph are right. If no contour is found, the last position remains in the global x and y variables. Perhaps you want to increase the indent of the four lines that draw circle, lines and text so that it belongs to the for-loop above?
....
img = img[0:600, 60:700 ]
contours = detector.detect_objects(img)
# Draw objects boundaries
for cnt in contours:
....
# Display rectangle
box = cv2.boxPoints(rect)
box = np.int0(box)
# keep indent here
cv2.circle(img, (int(x), int(y)), 5, (0, 0, 255), -1)
cv2.polylines(img, [box], True, (255, 0, 0), 2)
cv2.putText(img, "Width {} px".format(round(object_width, 1)), (int(x - 100), int(y - 20)), cv2.FONT_HERSHEY_PLAIN, 2, (100, 200, 0), 2)
cv2.putText(img, "Height {} px".format(round(object_height, 1)), (int(x - 100), int(y + 15)), cv2.FONT_HERSHEY_PLAIN, 2, (100, 200, 0), 2)
....

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

where add cv2.resize to get appropriate resolution?

I have a problem with my code. I don't know where I could put cv.resize() in order to get requirement resolution. I want to change it because the file which I upload is full HD resolution and I want to get smaller resolution. I will be glad of solution and explanation.
Below I show my code:
import cv2
import numpy as np
cap = cv2.VideoCapture('DJI_0037.MP4')
while cap.isOpened():
ret, frame = cap.read()
if ret == True:
frame_resize = cv2.resize(frame, (640, 480), interpolation=cv2.INTER_CUBIC)
else:
break
ret, frame_resize1 = cap.read(frame_resize)
ret, frame_resize2 = cap.read(frame_resize)
diff = cv2.absdiff(frame_resize1, frame_resize2)
gray = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (5, 5), 0)
_, thresh = cv2.threshold(blur, 20, 255, cv2.THRESH_BINARY)
dilated = cv2.dilate(thresh, None, iterations=3)
contours, _ = cv2.findContours(dilated, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for contour in contours:
(x, y, w, h) = cv2.boundingRect(contour)
if cv2.contourArea(contour) < 2000:
continue
cv2.rectangle(frame_resize1, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.putText(frame_resize1, "Status: {}".format('Movement'), (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255),3)
cv2.imshow("feed", frame_resize1)
frame_resize1 = frame_resize2
ret, frame_resize2 = cap.read()
if cv2.waitKey(40) == 27:
break
cap.release()
cv2.destroyAllWindows()

OpenCV Background Subtraction Get Color Objects (Python)

Background subtraction method (BackgroundSubtractorMOG2) will normally return the output in binary image.
Is there a solution on how I can get the original colour of the object after implementing the BackgroundSubtractorMOG2 ?
import cv2
import numpy as np
cap = cv2.VideoCapture("people.mkv")
kernel_dil = np.ones((10,10), np.uint8)
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3,3))
fgbg = cv2.createBackgroundSubtractorMOG2(history=0, varThreshold=444, detectShadows=False)
while True:
ret, frame1 = cap.read()
frame = cv2.resize(frame1,(1364,700),fx=0,fy=0, interpolation = cv2.INTER_CUBIC)
mask = np.zeros(frame.shape, dtype=np.uint8)
mask.fill(255)
roi_corners = np.array([[(11,652), (1353,652), (940,84), (424,84)]], dtype=np.int32)
cv2.fillPoly(mask, roi_corners, 0)
masking = cv2.bitwise_or(frame, mask)
if ret == True:
fgmask = fgbg.apply(masking,mask)
fgmask = cv2.morphologyEx(fgmask, cv2.MORPH_OPEN, kernel)
dilation = cv2.dilate(fgmask2, kernel_dil, iterations = 1)
(contours,hierarchy) = cv2.findContours(dilation, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for pic, contour in enumerate(contours):
area = cv2.contourArea(contour)
x,y,w,h = cv2.boundingRect(contour)
if(area>0.001):
cv2.rectangle(frame, (x,y), (x+w,y+h), (0,0,255), 2)
cv2.putText(frame, 'People', (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255,0,0), 2, cv2.LINE_AA)
cv2.imshow("FullScreen", frame)
cv2.imshow("FGMask1", fgmask)
cv2.imshow("FGMask2", dilation)
key = cv2.waitKey(12)
if key == ord("q"):
break

If you consider the output as binary mask, you could just do a bitwise and with your original image
cv.bitwise_and(input, input, mask = yourMOG_output);