(
self,
crop_size: int = 224,
do_center_crop: bool = True,
do_normalize: bool = True,
do_resize: bool = True,
image_mean: List[float] = [0.48145466, 0.4578275, 0.40821073],
image_std: List[float] = [0.26862954, 0.26130258, 0.27577711],
size: int = 224,
**kwargs
)
| 16 | """ |
| 17 | |
| 18 | def __init__( |
| 19 | self, |
| 20 | crop_size: int = 224, |
| 21 | do_center_crop: bool = True, |
| 22 | do_normalize: bool = True, |
| 23 | do_resize: bool = True, |
| 24 | image_mean: List[float] = [0.48145466, 0.4578275, 0.40821073], |
| 25 | image_std: List[float] = [0.26862954, 0.26130258, 0.27577711], |
| 26 | size: int = 224, |
| 27 | **kwargs |
| 28 | ) -> None: |
| 29 | self.crop_size = crop_size |
| 30 | self.do_center_crop = do_center_crop |
| 31 | self.do_normalize = do_normalize |
| 32 | self.do_resize = do_resize |
| 33 | self.image_mean = mx.array(image_mean) |
| 34 | self.image_std = mx.array(image_std) |
| 35 | self.size = size |
| 36 | |
| 37 | def __call__(self, images: List[Image]) -> mx.array: |
| 38 | return mx.concatenate( |
nothing calls this directly
no outgoing calls
no test coverage detected