Convert rgb images to grayscale images









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I have a numpy array of rgb images as shown below



print(train_frames.shape) #(100, 40, 120, 140, 3)


which means 100 rows each of 40 frames contains an image of 120x140.



I need to convert that into gray scale images i.e,



print(train_frames.shape) #(100, 40, 120, 140, 1)


How to convert that ?










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    up vote
    -2
    down vote

    favorite












    I have a numpy array of rgb images as shown below



    print(train_frames.shape) #(100, 40, 120, 140, 3)


    which means 100 rows each of 40 frames contains an image of 120x140.



    I need to convert that into gray scale images i.e,



    print(train_frames.shape) #(100, 40, 120, 140, 1)


    How to convert that ?










    share|improve this question























      up vote
      -2
      down vote

      favorite









      up vote
      -2
      down vote

      favorite











      I have a numpy array of rgb images as shown below



      print(train_frames.shape) #(100, 40, 120, 140, 3)


      which means 100 rows each of 40 frames contains an image of 120x140.



      I need to convert that into gray scale images i.e,



      print(train_frames.shape) #(100, 40, 120, 140, 1)


      How to convert that ?










      share|improve this question













      I have a numpy array of rgb images as shown below



      print(train_frames.shape) #(100, 40, 120, 140, 3)


      which means 100 rows each of 40 frames contains an image of 120x140.



      I need to convert that into gray scale images i.e,



      print(train_frames.shape) #(100, 40, 120, 140, 1)


      How to convert that ?







      opencv image-processing deep-learning






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Nov 11 at 17:13









      Krishna Preetham

      15




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          If you want to do that in batch, one way is to use numpy.mean



          numpy.mean(train_frames, axis=-1)


          axis=-1 means the 3 rgb channels.



          If you want to get a better conversion, I guess you will need to convert image by image with opencv cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)






          share|improve this answer




















          • When I am using that cv2.cvtColor thing, I am getting array shape of only (100, 40, 120, 160) instead of (100, 40, 120, 160, 1)
            – Krishna Preetham
            Nov 12 at 4:09










          • To use cvtColor you must iterate on the (100, 40) matrix with 120x160x3 images. Each image should be converted to a 120x160x1. Got it?
            – Fred Guth
            Nov 12 at 17:00











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          1 Answer
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          active

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          1 Answer
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          active

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          up vote
          0
          down vote













          If you want to do that in batch, one way is to use numpy.mean



          numpy.mean(train_frames, axis=-1)


          axis=-1 means the 3 rgb channels.



          If you want to get a better conversion, I guess you will need to convert image by image with opencv cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)






          share|improve this answer




















          • When I am using that cv2.cvtColor thing, I am getting array shape of only (100, 40, 120, 160) instead of (100, 40, 120, 160, 1)
            – Krishna Preetham
            Nov 12 at 4:09










          • To use cvtColor you must iterate on the (100, 40) matrix with 120x160x3 images. Each image should be converted to a 120x160x1. Got it?
            – Fred Guth
            Nov 12 at 17:00















          up vote
          0
          down vote













          If you want to do that in batch, one way is to use numpy.mean



          numpy.mean(train_frames, axis=-1)


          axis=-1 means the 3 rgb channels.



          If you want to get a better conversion, I guess you will need to convert image by image with opencv cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)






          share|improve this answer




















          • When I am using that cv2.cvtColor thing, I am getting array shape of only (100, 40, 120, 160) instead of (100, 40, 120, 160, 1)
            – Krishna Preetham
            Nov 12 at 4:09










          • To use cvtColor you must iterate on the (100, 40) matrix with 120x160x3 images. Each image should be converted to a 120x160x1. Got it?
            – Fred Guth
            Nov 12 at 17:00













          up vote
          0
          down vote










          up vote
          0
          down vote









          If you want to do that in batch, one way is to use numpy.mean



          numpy.mean(train_frames, axis=-1)


          axis=-1 means the 3 rgb channels.



          If you want to get a better conversion, I guess you will need to convert image by image with opencv cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)






          share|improve this answer












          If you want to do that in batch, one way is to use numpy.mean



          numpy.mean(train_frames, axis=-1)


          axis=-1 means the 3 rgb channels.



          If you want to get a better conversion, I guess you will need to convert image by image with opencv cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)







          share|improve this answer












          share|improve this answer



          share|improve this answer










          answered Nov 12 at 2:11









          Fred Guth

          7561518




          7561518











          • When I am using that cv2.cvtColor thing, I am getting array shape of only (100, 40, 120, 160) instead of (100, 40, 120, 160, 1)
            – Krishna Preetham
            Nov 12 at 4:09










          • To use cvtColor you must iterate on the (100, 40) matrix with 120x160x3 images. Each image should be converted to a 120x160x1. Got it?
            – Fred Guth
            Nov 12 at 17:00

















          • When I am using that cv2.cvtColor thing, I am getting array shape of only (100, 40, 120, 160) instead of (100, 40, 120, 160, 1)
            – Krishna Preetham
            Nov 12 at 4:09










          • To use cvtColor you must iterate on the (100, 40) matrix with 120x160x3 images. Each image should be converted to a 120x160x1. Got it?
            – Fred Guth
            Nov 12 at 17:00
















          When I am using that cv2.cvtColor thing, I am getting array shape of only (100, 40, 120, 160) instead of (100, 40, 120, 160, 1)
          – Krishna Preetham
          Nov 12 at 4:09




          When I am using that cv2.cvtColor thing, I am getting array shape of only (100, 40, 120, 160) instead of (100, 40, 120, 160, 1)
          – Krishna Preetham
          Nov 12 at 4:09












          To use cvtColor you must iterate on the (100, 40) matrix with 120x160x3 images. Each image should be converted to a 120x160x1. Got it?
          – Fred Guth
          Nov 12 at 17:00





          To use cvtColor you must iterate on the (100, 40) matrix with 120x160x3 images. Each image should be converted to a 120x160x1. Got it?
          – Fred Guth
          Nov 12 at 17:00


















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