I'm using Opencv python in raspberry pi, to analize a heatmap, i'm looking for color red, which represents the highest temperature, i need to detect if in an specific area exist red color, in case it does i can use this information to activate a condition, i'm using a heatmap like this:
for the red color detection i'm using this code:
import cv2
import numpy as np
while(1):
# Take each frame
frame = cv2.imread('heatmap.png')
# Convert BGR to HSV
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
# define range of blue color in HSV
lower_red = np.array([-20, 100, 100])
upper_red = np.array([13, 255, 255])
# Threshold the HSV image to get only blue colors
mask = cv2.inRange(hsv, lower_red, upper_red)
# Bitwise-AND mask and original image
res = cv2.bitwise_and(frame,frame, mask= mask)
cv2.imshow('heatmap',frame)
cv2.imshow('mask',mask)
cv2.imshow('res',res)
k = cv2.waitKey(5) & 0xFF
if k == 27:
break
cv2.destroyAllWindows()
the code above give me al the pixels in red, but i need to determine if the heatmap contour is red, i mean the image contour or border would be a red color not permited area, does anyone how i can do that?
Your HSV range is not right. For red, (0,20,20)~(8,255,255), (170,20,20) ~ (180,255,255)
.
Here is my result:
The code:
#!/usr/bin/python3
# 2018/05/16 13:54:09
import cv2
import numpy as np
img = cv2.imread('heatmap.png')
# Convert BGR to HSV
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
mask1 = cv2.inRange(hsv, (0,20,20), (8,255,255))
mask2 = cv2.inRange(hsv, (170,20,20), (180,255,255))
mask = cv2.bitwise_or(mask1, mask2)
dst = cv2.bitwise_and(img, img, mask=mask)
cv2.imshow("dst", dst)
cv2.imwrite("__.png", dst)
cv2.waitKey()
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