Reading images in RGB

[ehofesmann]

The example from the TF2 Model Zoo inference tutorial notebook loads images in RGB format with:

def load_image_into_numpy_array(path):
  """Load an image from file into a numpy array.

  Puts image into numpy array to feed into tensorflow graph.
  Note that by convention we put it into a numpy array with shape
  (height, width, channels), where channels=3 for RGB.

  Args:
    path: the file path to the image

  Returns:
    uint8 numpy array with shape (img_height, img_width, 3)
  """
  img_data = tf.io.gfile.GFile(path, 'rb').read()
  image = Image.open(BytesIO(img_data))
  (im_width, im_height) = image.size
  return np.array(image.getdata()).reshape(
      (im_height, im_width, 3)).astype(np.uint8)

In this tutorial you just use cv2.imread() which will produce numpy arrays in BGR format.

Not sure if this is has been accounted for and I just missed it but if not then it should be fixed. It should be as easy as adding

img = img[...,::-1]

here https://github.com/abdelrahman-gaber/tf2-object-detection-api-tutorial/blob/91f6e167417227b4d5fe42cf3ac770f3b0a3c3b2/detector.py#L22