new: real images augmentation

[Data-Iab]

• New feature : 3 different implementations of focus blur augmentation

from alodataset.transforms import RandomFocusBlur, RandomFocusBlurV2, RandomFocusBlurV3

import aloscene
import torch

frame = aloscene.Frame(torch.rand((3, 300, 300)))
blured_frame1 = RandomFocusBlur()(frame)
blured_frame2 = RandomFocusBlurV2()(frame)
blured_frame3 = RandomFocusBlurV3()(frame)

• New feature : Motion blur augmentation from optical flow

## Motion blur from RAFT-flow
from alonet.raft.raft import RAFT

flow_model = RAFT(weights="raft-things")
flow_model = model.eval()

frame_t0_t1 = aloscene.Frame(torch.ones((2, 3, 300, 300)), names=tuple("TCHW"))
frame_t0 = frame_t0_t1[0]
frame_t1 = frame_t0_t1[1]

blured_t1 = RandomFlowMotionBlur(flow_model=flow_model)(frame_t1, p_frame=frame_t0)
blured_t1.get_view().render()

## Motion blur from ground truth optical flow
flow = aloscene.Flow(torch.ones((2, 300, 300)))
blured_t1 = RandomFlowMotionBlur()(frame_t1, flow=flow)
blured_t1.get_view().render()

• New feature : Random corner masking augmentation

from alodataset.transforms import RandomCornersMask
import aloscene
import torch

frame = aloscene.Frame(torch.ones((3, 300, 300)))
randomly_masked_frame = RandomCornersMask()(frame)

• Fix bug X : CameraIntrinsic initialization with a shape of 4x4 was not possible using __init__

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This pull request includes

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update