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https://github.com/huggingface/lerobot.git
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CarolinePascal
53 lines
1.7 KiB
Python
53 lines
1.7 KiB
Python
#!/usr/bin/env python
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# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import pytest
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import torch
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# The script imports ``lerobot.datasets`` (via the annotation frame provider),
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# which only ships under the ``dataset`` extra.
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pytest.importorskip("datasets", reason="datasets is required (install lerobot[dataset])")
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from lerobot.scripts.lerobot_curate_cameras import _to_uint8_frame, _uniform_indices # noqa: E402
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@pytest.mark.parametrize(
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"n,k,expected",
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[
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(0, 4, []),
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(5, 0, []),
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(3, 5, [0, 1, 2]), # k >= n -> all frames
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(1, 4, [0]),
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(10, 1, [0]),
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(10, 4, [0, 3, 6, 9]), # evenly spaced, endpoints included
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],
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)
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def test_uniform_indices(n, k, expected):
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assert _uniform_indices(n, k) == expected
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def test_to_uint8_frame_scales_floats():
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frame = torch.ones(3, 4, 4, dtype=torch.float32) # [0,1] float
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out = _to_uint8_frame(frame)
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assert out.dtype == torch.uint8
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assert int(out.max()) == 255
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def test_to_uint8_frame_passthrough_uint8():
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frame = torch.zeros(3, 4, 4, dtype=torch.uint8)
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out = _to_uint8_frame(frame)
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assert out is frame # uint8 passes through untouched
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