def fbresnet_augmentor(isTrain):
    """
    Augmentor used in fb.resnet.torch, for BGR images in range [0,255].
    """
    interpolation = cv2.INTER_CUBIC
    # linear seems to have more stable performance.
    # but we keep cubic for compatibility with old models
    if isTrain:
        augmentors = [
            imgaug.GoogleNetRandomCropAndResize(interp=interpolation),
            imgaug.ToFloat32(),  # avoid frequent casting in each color augmentation
            # It's OK to remove the following augs if your CPU is not fast enough.
            # Removing brightness/contrast/saturation does not have a significant effect on accuracy.
            # Removing lighting leads to a tiny drop in accuracy.
            imgaug.RandomOrderAug(
                [imgaug.BrightnessScale((0.6, 1.4)),
                 imgaug.Contrast((0.6, 1.4), rgb=False),
                 imgaug.Saturation(0.4, rgb=False),
                 # rgb-bgr conversion for the constants copied from fb.resnet.torch
                 imgaug.Lighting(0.1,
                                 eigval=np.asarray(
                                     [0.2175, 0.0188, 0.0045][::-1]) * 255.0,
                                 eigvec=np.array(
                                     [[-0.5675, 0.7192, 0.4009],
                                      [-0.5808, -0.0045, -0.8140],
                                      [-0.5836, -0.6948, 0.4203]],
                                     dtype='float32')[::-1, ::-1]
                                 )]),
            imgaug.ToUint8(),
            imgaug.Flip(horiz=True),
        ]
    else:
        augmentors = [
            imgaug.ResizeShortestEdge(256, interp=interpolation),
            imgaug.CenterCrop((224, 224)),
        ]
    return augmentors

    Augmentor used in fb.resnet.torch, for BGR images in range [0,255].
    
examples/ImageNetModels/imagenet_utils.py