def horizontal_flip(
input: features.BoundingBox) -> features.BoundingBox:
x, y, w, h = input.convert("xywh").to_parts()
x = input.image_size[1] - (x + w)
return features.BoundingBox.from_parts(x,
y,
w,
h,
like=input,
format="xywh")
def bounding_box(input: BoundingBox, *, size: Tuple[int, int], **_: Any) -> BoundingBox:
old_height, old_width = input.image_size
new_height, new_width = size
height_scale = new_height / old_height
width_scale = new_width / old_width
old_x1, old_y1, old_x2, old_y2 = input.convert("xyxy").to_parts()
new_x1 = old_x1 * width_scale
new_y1 = old_y1 * height_scale
new_x2 = old_x2 * width_scale
new_y2 = old_y2 * height_scale
return BoundingBox.from_parts(
new_x1, new_y1, new_x2, new_y2, like=input, format="xyxy", image_size=size
).convert(input.format)
def resize(input: features.BoundingBox,
size: torch.Tensor) -> features.BoundingBox:
old_height, old_width = input.image_size
new_height, new_width = size
height_scale = new_height / old_height
width_scale = new_width / old_width
old_x1, old_y1, old_x2, old_y2 = input.convert("xyxy").to_parts()
new_x1 = old_x1 * width_scale
new_y1 = old_y1 * height_scale
new_x2 = old_x2 * width_scale
new_y2 = old_y2 * height_scale
return features.BoundingBox.from_parts(new_x1,
new_y1,
new_x2,
new_y2,
like=input,
format="xyxy",
image_size=tuple(
size.tolist()))
def image(input: Image, *, crop_box: BoundingBox) -> Image:
# FIXME: pad input in case it is smaller than crop_box
x1, y1, x2, y2 = crop_box.convert("xyxy").to_parts()
return Image(input[..., y1 : y2 + 1, x1 : x2 + 1], like=input) # type: ignore[misc]
def __init__(self, crop_box: BoundingBox) -> None:
super().__init__()
self.crop_box = crop_box.convert("xyxy")
def bounding_box(input: BoundingBox) -> BoundingBox:
x, y, w, h = input.convert("xywh").to_parts()
x = input.image_size[1] - (x + w)
return BoundingBox.from_parts(x, y, w, h, like=input, format="xywh").convert(input.format)
