v0.2.0

What's Changed

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• Update README.md by @thibo73800 in #156

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• Fix model none on BaseTRTExporter by @thibo73800 in #158

BaseTRTExporter can now be create from a None model. This is usefull if one want to only export from an onnx file.

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• add depth absolute/relative encoding by @Data-Iab in #159

Two methods added to Depth:

encode_inverse : invert depth with given scale and shift.
encode_absolute : undo encode_inverse changes.
One method added to AugTensor:

to_squeezed_numpy: as its name indicates, converts to squeezed numpy.

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• fixe project run_id default by @thibo73800 in #161

Fixe when using load_training without loading the common argparse, the no_run_id was used in load_training. I now use a default value if the value is not set into the args.

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• fix: resize intrinsic matrix by @anhtu293 in #164

Ratio of width and height are not exact in the resize method of matrix intrinsic.

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• add batch(dim) and temporal(dim) by @thibo73800 in #162

In this merge request:

It is now possible to do

tensor.temporal(dim=1) # where dim can be 0 or 1

and

tensor.batch(dim=1) # where dim can be 0 or 1

TODO: Check back unit test to check that everything is correct.

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• Noisy aug, pose update, depth abs, render, batch_list by @jsalotti in #165

Add a mergeable pose label to the Frame object.

It can be used as such

P = aloscene.Pose(cam_pos)

Pose directly inherit from CameraExtrinsic but usually refer to the global world coordinates/

Fix noisy pos to propagate the normalization and to use the device properly.

Add aloscene.render()

You can now directly render a list of view using aloscene.render()

aloscene.render(views)

Here is a example to add views and to record a video

views = []
# Run DFM on side cameras

for frames in data_loader:

    # Build a list of view
    for frames_side in frames:
        output = model.inference(model(frames))
        views.append(output.get_view())
    
    # render the list
    aloscene.render(views, record_file="model_outputs.mp4")

# Save the final video
aloscene.save_renderer()

batch list from aloscene

Instead of doing

SpatialAugmentedTensor.batch_list(tensors)

or

tensors[0].batch_list(tensors)

You can now do:

aloscene.batch_list(tensors)

Compute translation between two pose/extrinsic

ref.pose.translation_with(src.pose)

New Contributors

• @Data-Iab made their first contribution in #159

Full Changelog: v0.1.0...v0.2.0