Try resizing the shortest edge to a certain number while avoiding the longest edge to exceed max_size.
| 27 | |
| 28 | |
| 29 | class CustomResize(ImageAugmentor): |
| 30 | """ |
| 31 | Try resizing the shortest edge to a certain number |
| 32 | while avoiding the longest edge to exceed max_size. |
| 33 | """ |
| 34 | |
| 35 | def __init__(self, short_edge_length, max_size, interp=cv2.INTER_LINEAR): |
| 36 | """ |
| 37 | Args: |
| 38 | short_edge_length ([int, int]): a [min, max] interval from which to sample the |
| 39 | shortest edge length. |
| 40 | max_size (int): maximum allowed longest edge length. |
| 41 | """ |
| 42 | super(CustomResize, self).__init__() |
| 43 | if isinstance(short_edge_length, int): |
| 44 | short_edge_length = (short_edge_length, short_edge_length) |
| 45 | self._init(locals()) |
| 46 | |
| 47 | def get_transform(self, img): |
| 48 | h, w = img.shape[:2] |
| 49 | size = self.rng.randint( |
| 50 | self.short_edge_length[0], self.short_edge_length[1] + 1) |
| 51 | scale = size * 1.0 / min(h, w) |
| 52 | if h < w: |
| 53 | newh, neww = size, scale * w |
| 54 | else: |
| 55 | newh, neww = scale * h, size |
| 56 | if max(newh, neww) > self.max_size: |
| 57 | scale = self.max_size * 1.0 / max(newh, neww) |
| 58 | newh = newh * scale |
| 59 | neww = neww * scale |
| 60 | neww = int(neww + 0.5) |
| 61 | newh = int(newh + 0.5) |
| 62 | return ResizeTransform(h, w, newh, neww, self.interp) |
| 63 | |
| 64 | |
| 65 | def box_to_point4(boxes): |
no outgoing calls
no test coverage detected