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()
Related
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)
....
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
I'm trying to save the output imgCanny as an image/screenshot. How do I incorporate this so a screenshot of that window can be captured when a certain key is pressed. I am taking the live feed from the webcam and processing it. I would then like to be able to press a key on the keyboard to capture and save a screenshot of the imgCanny Window.
cap = cv2.VideoCapture(1)
cv2.waitKey(0)
cap.set(3, frameWidth)
cap.set(4, frameHeight)
def empty(a):
pass
cv2.namedWindow("Parameters")
cv2.resizeWindow("Parameters", 640, 240)
cv2.createTrackbar("Threshold1", "Parameters", 150, 500, empty)
cv2.createTrackbar("Threshold2", "Parameters", 255, 500, empty)
def getContours(img, imgContour):
contours, hierarchy = cv2.findContours(img, cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_NONE) #retreival method. External, only extreme
outer contours
#change APPROX to simple for less points
#remove small bits of noise
for cnt in contours:
area = cv2.contourArea(cnt)
# Used to flatted the array containing
# the co-ordinates of the vertices.
approx = cv2.approxPolyDP(cnt, 0.009 * cv2.arcLength(cnt, True),
True)
n = approx.ravel()
i = 0
for j in n:
if (i % 2 == 0):
x = n[i]
y = n[i + 1]
# String containing the co-ordinates.
string = str(int(x / 3.5)) + " " + str(int(y / 3.5))
print(string)
if (i == 0):
# text on topmost co-ordinate.
cv2.putText(imgContour, "", (x, y),
font, 0.5, (255, 0, 0))
else:
# text on remaining co-ordinates.
cv2.putText(imgContour, string, (x, y),
font, 0.5, (0, 255, 0))
i = i + 1
if area > 3000:
cv2.drawContours(imgContour, cnt, -1, (255, 0, 255), 1)
peri = cv2.arcLength(cnt, True) #true means contour is closed
while True:
success, img = cap.read()
imgContour = img.copy()
imgBlur = cv2.GaussianBlur(img, (31, 31), 1)
imgGray = cv2.cvtColor(imgBlur, cv2.COLOR_BGR2GRAY)
threshold1 = cv2.getTrackbarPos("Threshold1", "Parameters")
threshold2 = cv2.getTrackbarPos("Threshold2", "Parameters")
imgCanny = cv2.Canny(imgGray, threshold1, threshold2)
kernel = np.ones((5, 5))
imgDil = cv2.dilate(imgCanny, kernel, iterations=1)
getContours(imgDil, imgContour)
#cv2.imshow("Results", img )
#cv2.imshow("Mask", imgGray)
cv2.imshow("Canny", imgCanny)
cv2.imshow("Dilated", imgContour)
cv2.imshow("Test", imgDil)
key = cv2.waitKey(100)
if key == 27: #kills with Esc
break
cap.release()
cv2.destroyAllWindows()
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:
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.