Fix _parallelogram_to_bounding_boxes

[AntoineSimoulin]

This PR adjust the behavior of _parallelogram_to_bounding_boxes. Instead of transforming a parallelogram into a rectangle based on the largest input diagonal, the function returns the minimum area rectangle covering the initial parallelogram. When applying transforms to input rotated bounding boxes, the output tend to be closer to the original boxes and therefore more consistent.

We illustrate below the impact when applying the transforms v2.RandomPerspective(distortion_scale=0.6, p=1.0) in the tutorial to transforms on Rotated Bounding Boxes.

Before fix:

After fix:

[pytorch-bot]

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[AntoineSimoulin]

Note: Add tests (illustrated below) to control that the grey parallelogram is transformed into the green rectangle (and not the red rectangle).

# Test the transformation of a simple parallelogram.
#              1
#    1-2      /   2
#   / /  ->  /   /
# 4-3       4   /
#              3
#
#          1
# 1-2       \ 2
#   \ \  ->  \  \
#    4-3       4 \
#                 3
parallelogram = torch.tensor(
    [[0, 4, 3, 1, 5, 1, 2, 4], [0, 1, 2, 1, 5, 4, 3, 4]],
    dtype=torch.float32,
)
expected = torch.tensor(
    [[0, 4, 4, 0, 5, 1, 1, 5], [0, 1, 1, 0, 5, 4, 4, 5]],
    dtype=torch.float32,
)
actual = _parallelogram_to_bounding_boxes(parallelogram)
torch.testing.assert_close(actual, expected)

[facebook-github-bot]

@AntoineSimoulin has imported this pull request. If you are a Meta employee, you can view this in D80916035.

[facebook-github-bot]

@AntoineSimoulin has imported this pull request. If you are a Meta employee, you can view this in D80916035.

[github-actions]

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