Is random flip accomplished only in testing set?

[wave-transmitter]

According to following lines of code from dataset.py, it seems like random flip is triggered only for testing data.

pytorch-video-recognition/dataloaders/dataset.py

Lines 81 to 83 in a63b85f

	if self.split == 'test':
	# Perform data augmentation
	buffer = self.randomflip(buffer)

Do I get it wrong, or this is a bug where 'test' should be changed by 'train'?

[leftthomas]

@wave-transmitter It seems like a typo error, it should be on training process. And I think the function randomflip has a bug, in the for loop, it calls cv2.flip two times, it should call only once.

    def randomflip(self, buffer):
        """Horizontally flip the given image and ground truth randomly with a probability of 0.5."""
        if np.random.random() < 0.5:
            for i, frame in enumerate(buffer):
                frame = cv2.flip(buffer[i], flipCode=1)
                buffer[i] = cv2.flip(frame, flipCode=1)
        return buffer

[Taylor-X76]

II think so too
After two cv2.flip(...), the picture has no change.