CODEWITHSUNDEEP
pythonnumpy
curie
curie

Reputation: 33

How can I change a color channel in an image using numpy?

I have an image where some color channels in the pixels have a value of zero (ie 255, 146, 0). I want to be able to change any value equal to zero in the array to a different value, but I do not know how to access these values. Any help with this?

This is the image array:

[[[ 76 163 168]
  [109 166 168]
  [173 172 167]
  ..., 
  [ 83 182 144]
  [ 78 172 134]
  [ 82 150 131]]

 [[ 51 151 168]
  [ 99 157 171]
  [173 195 159]
  ..., 
  [ 56 165 144]
  [ 25 198 125]
  [ 35 185 121]]

 [[ 76 163 121]
  [112 147 120]
  [175 151 118]
  ..., 
  [ 57 162 159]
  [ 36 185 132]
  [ 32 194  97]]

 ..., 
 [[ 78 189 126]
  [ 68 173 129]
  [ 58 171 150]
  ..., 
  [ 41 188 163]
  [ 34 176 126]
  [ 35 176 102]]

 [[131 155 161]
  [101 141 161]
  [ 42 151 177]
  ..., 
  [ 56 178 122]
  [ 45 192 114]
  [ 46 184 112]]

 [[130 157 185]
  [ 83 141 185]
  [ 42 158 185]
  ..., 
  [ 63 187  88]
  [ 45 194 102]
  [ 45 184 129]]]

Upvotes: 2

Views: 1796

Answers (1)

Divakar
Divakar

Reputation: 221514

Use masking -

img[(img==zero_val).all(-1)] = new_val

, where zero_val is the zero color and new_val is the new color to be assigned at those places where we have zero colored pixels.

Sample run -

# Random image array
In [112]: img = np.random.randint(0,255,(4,5,3))

# Define sample zero valued and new valued arrays
In [113]: zero_val = [255,146,0]
     ...: new_val = [255,255,255]
     ...: 

# Set two random points/pixels to be zero valued
In [114]: img[0,2] = zero_val

In [115]: img[2,3] = zero_val

# Use proposed approach
In [116]: img[(img==zero_val).all(-1)] = new_val

# Verify that new values have been assigned
In [117]: img[0,2]
Out[117]: array([255, 255, 255])

In [118]: img[2,3]
Out[118]: array([255, 255, 255])

Upvotes: 1

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