Choosing the correct upper and lower HSV boundaries for color detection with cv inRange OpenCV

Question

I have an image of a coffee can with an orange lid position of which I want to find  Here is it    gcolor2 utility shows HSV at the center of the lid to be  22  59  100   The question is how to choose the limits of the color then  I tried min    18  40  90  and max    27  255  255   but have got unexpected   Here is the Python code   import cv  in image    kaffee png  out image    kaffee out png  out image thr    kaffee thr png   ORANGE MIN   cv Scalar 18  40  90  ORANGE MAX   cv Scalar 27  255  255  COLOR MIN   ORANGE MIN COLOR MAX   ORANGE MAX  def test1        frame   cv LoadImage in image      frameHSV   cv CreateImage cv GetSize frame   8  3      cv CvtColor frame  frameHSV  cv CV RGB2HSV      frame threshed   cv CreateImage cv GetSize frameHSV   8  1      cv InRangeS frameHSV  COLOR MIN  COLOR MAX  frame threshed      cv SaveImage out image thr  frame threshed   if   name         main         test1

User · Answer

OpenCV HSV range is  H  0 to 179 S  0 to 255 V  0 to 255  On Gimp  or other photo manipulation sw  Hue range from 0 to 360  since opencv put color info in a single byte  the maximum number value in a single byte is 255 therefore openCV Hue values are equivalent to Hue values from gimp divided by 2   I found when trying to do object detection based on HSV color space that a range of 5  opencv range  was sufficient to filter out a specific color  I would advise you to use an HSV color palate to figure out the range that works best for your application

User · Answer

To find the HSV value of Green  try following commands in Python terminal  green   np uint8    0 255 0      hsv green   cv2 cvtColor green cv2 COLOR BGR2HSV  print hsv green     60 255 255

User · Answer

Here s a simple HSV color thresholder script to determine the lower upper color ranges using trackbars for any image on the disk  Simply change the image path in cv2 imread      import cv2 import numpy as np  def nothing x       pass    Load image image   cv2 imread  1 jpg      Create a window cv2 namedWindow  image      Create trackbars for color change   Hue is from 0-179 for Opencv cv2 createTrackbar  HMin    image   0  179  nothing  cv2 createTrackbar  SMin    image   0  255  nothing  cv2 createTrackbar  VMin    image   0  255  nothing  cv2 createTrackbar  HMax    image   0  179  nothing  cv2 createTrackbar  SMax    image   0  255  nothing  cv2 createTrackbar  VMax    image   0  255  nothing     Set default value for Max HSV trackbars cv2 setTrackbarPos  HMax    image   179  cv2 setTrackbarPos  SMax    image   255  cv2 setTrackbarPos  VMax    image   255     Initialize HSV min max values hMin   sMin   vMin   hMax   sMax   vMax   0 phMin   psMin   pvMin   phMax   psMax   pvMax   0  while 1         Get current positions of all trackbars     hMin   cv2 getTrackbarPos  HMin    image       sMin   cv2 getTrackbarPos  SMin    image       vMin   cv2 getTrackbarPos  VMin    image       hMax   cv2 getTrackbarPos  HMax    image       sMax   cv2 getTrackbarPos  SMax    image       vMax   cv2 getTrackbarPos  VMax    image          Set minimum and maximum HSV values to display     lower   np array  hMin  sMin  vMin       upper   np array  hMax  sMax  vMax          Convert to HSV format and color threshold     hsv   cv2 cvtColor image  cv2 COLOR BGR2HSV      mask   cv2 inRange hsv  lower  upper      result   cv2 bitwise and image  image  mask mask         Print if there is a change in HSV value     if  phMin    hMin     psMin    sMin     pvMin    vMin     phMax    hMax     psMax    sMax     pvMax    vMax             print   hMin    d   sMin    d  vMin    d    hMax    d   sMax    d  vMax    d      hMin   sMin   vMin  hMax  sMax   vMax           phMin   hMin         psMin   sMin         pvMin   vMin         phMax   hMax         psMax   sMax         pvMax   vMax        Display result image     cv2 imshow  image   result      if cv2 waitKey 10   amp  0xFF    ord  q            break  cv2 destroyAllWindows

User · Answer

Ok  find color in HSV space is an old but common question  I made a hsv-colormap to fast look up special color  Here it is     The x-axis represents Hue in  0 180   the y-axis1 represents Saturation in  0 255   the y-axis2 represents S   255  while keep V   255   To find a color  usually just look up for the range of H and S  and set v in range 20  255    To find the orange color  we look up for the map  and find the best range  H   10  25   S   100  255   and V   20  255   So the mask is cv2 inRange hsv  10  100  20    25  255  255     Then we use the found range to look for the orange color  this is the result       The method is simple but common to use      usr bin python3   2018 01 21 20 46 41 CST import cv2  img   cv2 imread  test jpg   hsv   cv2 cvtColor img  cv2 COLOR BGR2HSV  mask   cv2 inRange hsv  10  100  20    25  255  255    cv2 imshow  orange   mask  cv2 waitKey   cv2 destroyAllWindows     Similar answers         How to define a threshold value to detect only green colour objects in an image  Opencv   Choosing correct HSV values for OpenCV thresholding with InRangeS

User · Answer

I Created this simple program to get HSV Codes in realtime  import cv2 import numpy as np   cap   cv2 VideoCapture 0   def nothing x       pass   Creating a window for later use cv2 namedWindow  result      Starting with 100 s to prevent error while masking h s v   100 100 100    Creating track bar cv2 createTrackbar  h    result  0 179 nothing  cv2 createTrackbar  s    result  0 255 nothing  cv2 createTrackbar  v    result  0 255 nothing   while 1           frame   cap read         converting to HSV     hsv   cv2 cvtColor frame cv2 COLOR BGR2HSV         get info from track bar and appy to result     h   cv2 getTrackbarPos  h   result       s   cv2 getTrackbarPos  s   result       v   cv2 getTrackbarPos  v   result          Normal masking algorithm     lower blue   np array  h s v       upper blue   np array  180 255 255        mask   cv2 inRange hsv lower blue  upper blue       result   cv2 bitwise and frame frame mask   mask       cv2 imshow  result  result       k   cv2 waitKey 5   amp  0xFF     if k    27          break  cap release    cv2 destroyAllWindows

User · Answer

Problem 1   Different applications use different scales for HSV  For example gimp uses H   0-360  S   0-100 and V   0-100  But OpenCV uses  H  0-179  S  0-255  V  0-255  Here i got a hue value of 22 in gimp  So I took half of it  11  and defined range for that  ie  5 50 50  -  15 255 255    Problem 2  And also  OpenCV uses BGR format  not RGB  So change your code which converts RGB to HSV as follows   cv CvtColor frame  frameHSV  cv CV BGR2HSV    Now run it  I got an output as follows     Hope that is what you wanted  There are some false detections  but they are small  so you can choose biggest contour which is your lid   EDIT   As Karl Philip told in his comment  it would be good to add new code  But there is change of only a single line  So  I would like to add the same code implemented in new cv2 module  so users can compare the easiness and flexibility of new cv2 module   import cv2 import numpy as np  img   cv2 imread  sof jpg    ORANGE MIN   np array  5  50  50  np uint8  ORANGE MAX   np array  15  255  255  np uint8   hsv img   cv2 cvtColor img cv2 COLOR BGR2HSV   frame threshed   cv2 inRange hsv img  ORANGE MIN  ORANGE MAX  cv2 imwrite  output2 jpg   frame threshed    It gives the same result as above  But code is much more simpler

[opencv] Choosing the correct upper and lower HSV boundaries for color detection with`cv::inRange` (OpenCV)

Examples related to opencv

Examples related to hsv

Examples related to color-detection