Why does the image extracted from the Project Tango Tablet appear gray?

• I am using the Project Tango C API

• I am writing the entire buffer pointed to by TangoImageBuffer.data to a file.

  // open a file
  std::fstream f(app.getNextFileName(), std::ios::out | std::ios::binary);
  
  // write the entire stride * height * 4 buffer into the file
  f.write((const char *) tango_image_buffer->data, 
      tango_image_buffer->stride * buffer->height * 4 * sizeof(uint8_t)
  );
  
  f.close();
  
  

• I then export the file to my PC and visualize it using python-opencv and numpy:

  import sys
  
  import cv2
  import numpy as np
  
  # dimensions of the image
  stride    = 1280
  width     = 1280
  height    = 720
  
  # I am using 3 channels so that the resulting image is not
  # transluscent
  channels  = 3
  
  input_filename  = sys.argv[1]
  output_filename = sys.argv[2]
  
  # load the image buffer into a list
  data = np.fromfile(input_filename, dtype=np.uint8)
  
  # create a height x width x channels matrix with the datatype uint8 
  # and all elements set to zero
  img = np.zeros((height, width, channels), dtype=np.uint8);
  
  # map elements in array to image matrix
  for y in range(0, height):    
      for x in range(0, width):
          img[y, x, 0] = data[y * stride + x + 2] #blue
          img[y, x, 1] = data[y * stride + x + 1] #green
          img[y, x, 2] = data[y * stride + x + 0] #red
  
  # display and save the resulting image
  cv2.namedWindow("tango-rgba")
  cv2.imshow("tango-rgba", img)
  cv2.waitKey(0)
  cv2.destroyAllWindows()
  cv2.imwrite(output_filename, img)
  
  

• Unfortunately, the resulting image looks gray

• The image only appears to be gray. Upon closer inspection of the pixels, you will find that the red, green, and blue components of the pixels are different.

• EDIT: I have changed this post to specify that the buffer I am using is in RGBA8888 format. From the Project Tango Reference, "Only RGBA 8888 is provided"

• EDIT: It actually seems RGBA8888 format is not used. rhashimoto suggests that the format is YV12.

via Chebli Mohamed