| # Conventions | |
| Please check the following conventions if you would like to modify MMYOLO as your own project. | |
| ## About the order of image shape | |
| In OpenMMLab 2.0, to be consistent with the input argument of OpenCV, the argument about image shape in the data transformation pipeline is always in the `(width, height)` order. On the contrary, for computation convenience, the order of the field going through the data pipeline and the model is `(height, width)`. Specifically, in the results processed by each data transform pipeline, the fields and their value meaning is as below: | |
| - img_shape: (height, width) | |
| - ori_shape: (height, width) | |
| - pad_shape: (height, width) | |
| - batch_input_shape: (height, width) | |
| As an example, the initialization arguments of `Mosaic` are as below: | |
| ```python | |
| @TRANSFORMS.register_module() | |
| class Mosaic(BaseTransform): | |
| def __init__(self, | |
| img_scale: Tuple[int, int] = (640, 640), | |
| center_ratio_range: Tuple[float, float] = (0.5, 1.5), | |
| bbox_clip_border: bool = True, | |
| pad_val: float = 114.0, | |
| prob: float = 1.0) -> None: | |
| ... | |
| # img_scale order should be (width, height) | |
| self.img_scale = img_scale | |
| def transform(self, results: dict) -> dict: | |
| ... | |
| results['img'] = mosaic_img | |
| # (height, width) | |
| results['img_shape'] = mosaic_img.shape[:2] | |
| ``` | |