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Reading images in RGB #6

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@ehofesmann

Description

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

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