mirror of
https://github.com/huggingface/lerobot.git
synced 2026-06-29 22:27:14 +00:00
3dd19d043e
* feat(depth): add depth quantization helpers and tests
* feat(video): add ffv1 to supported codecs
* feat(depth): persist depth metadata
* feat(depth): extend quantization tools to better fit the encoding/decoding pipeline
* feat(depth): plumb DepthEncoderConfig through LeRobotDataset and DatasetWriter
* feat(depth): wire StreamingVideoEncoder + writer to depth encoder
* feat(depth): wire DatasetReader to decode_depth_frames
* feat(cameras/realsense): expose async depth in metric meters
* feat(features): route 2D camera shapes to observation.depth.<key>
* feat(robots/so_follower): emit + populate depth keys when use_depth
* feat(record): plumb DepthEncoderConfig through lerobot-record
* feat(viz): render depth observations as rr.DepthImage in Viridis
* feat(depth maps writer): adding support for raw depth maps recording with image writer
* chore(format): format code
* feat(depth shape): ensuring depth maps shape is always including the channel
* feat(is_depth): simplifying is_depth nested name + legacy support
* fix(stop_event): fixing stop_event race condition in camera classes
* fix(plumbing): fixing missing parts in the depth maps pipeline
* chore(typos): fixing typos
* test(fix): fixing exisiting tests to still work with latest features
* tests(depth): adding new tests for depth integration validation
* feat(pix_fmt channels): use PyAv to check get pixel formats number of channels
* feat(refactor): refactor DepthEncoderConfig quantization pipeline, so that the methods do not live in the config class. Add pixel format - channels validation.Move the default pixel format for depth in the config file.
* fix(pre-commit): fixing mutable defautl value
* fix(info): fixing info metadata update when is_depth_map was set
* tests(typos): fixing typos in tests
* fix(realsense): fixing typo in realsense serial number
* fix(normalization): restricting 255 normalization to non depth/uint8 images only
* fix(typo): fixing typo
* fix(TIFF): add missing quantization and cleanup for TIFF files
* feat(batched dequantization): optimizing dequantize_depth for torch based batched dequantization
* feat(tools): adding depth support in LeRobotDataset edition tools
* test(aggregate): extending aggregation tests to depth frames
* test(cleaning): cleaning up tests
* fix(from_video_info): fixing early validation issue in from_video_info
* fix(typo): fixing typo
* fix(is_depth): adding missing doctrings and is_depth arguments in video decoding functions
Co-authored-by: Wensi (Vince) Ai <59036629+wensi-ai@users.noreply.github.com>
* fix(depth units): fixing depth units output for the realsense cameras
* feat(output unit): adding support for output unit specification at dataset reading/training time
Co-authored-by: Wensi (Vince) Ai <59036629+wensi-ai@users.noreply.github.com>
* test(depth): cleaning up depth tests
* test(depth encoding): updating and cleaning video/depth encoding tests
* chore(format): formatting code
* docs(depth): improving depth maps docs
* test(fix): fixing depth tests
* test(dataset tools): adding missing tests for new dataset edition tools features
* chore(format): formatting code
* fix(pyav check): fixing PyAV option validation for integer codec options by normalizing
numeric values before calling `is_integer()`
Co-authored-by: Wensi (Vince) Ai <59036629+wensi-ai@users.noreply.github.com>
* docs(mermaid): fixing mermaid diagram
* fix(rebase): rebase follow up corrections
* feat(dataset tools): adding missing docstrings and features for depth fill support in dataset edition tools
* docs(docstring): updating docstrings
* docs(dataset tools): updating docs
* fix(save images): fixing image saving in dataset tools
* fix(update video info): fixing update video info logic to match the recording and editing use cases
* test(reencode): fixing reencoding monkeypatch
* fix(review): add Claude review
* chore(format): format code
* fix(update video info): ditching the differentiated approahces for video info update - video info are always updated unless for preserved keys.
* chore(rebase): fixing rebase merge conflicts
* test(visualization): fixing visualization tests
* feat(docstrings): adding explicit docstring for encoding parameters. Docstrigns will now show up as description in the CLI --help.
* feat(mm as default): adding a global DEFAULT_DEPTH_UNIT variable setting mm as default depth unit
* fix(RGB <-> camera): renaming camera_encoder to rgb_encoder for clarity
* chore(TODO): removing deprecated TODO
* doc(write_u16_plane): improving docstrings for write_u16_plane
* feat(units): adding constants for depth frames units (m and mm)
* fix(spam): replacing spamming warning but a debug log
* feat(leagcy metadata): adding automatic metadata update for legacy 'video.is_depth_map' feature
* fix(copy&reindex): fixing metadat reshaping for single channel frames
* fix(ImageNet): excluding dpeth frames from ImageNet stats
* fix(PyAV container seek): fixing initial PyAV container seek to be robust againsy codec choice
* feat(lerobot-dataset-viz): adding support for depth in lerobot-dataset-viz
* fix(compress): removing rerun compression for DepthImages
* fix(signle channel squeeze): fixing single channel squeezing
* chore(format): format code
* fix(streaming): adding support for dequantization in streaming_dataset.py
* refactor(read depth): factorizing depth reading methods for realsense camera and adding support for depth-only usage
* chore(renaming): fixing missed RGBEncoderConfig renamings
* docs(renaming): reflecting renamings in a clearer way in the docs
* chore(annotation): excluding depth from the annotation pipeline
* feat(robots): adding depth support in compatible follower robots
* feat(LeSadKiwi): excluding LeKiwi from depth support (for now)
* chore(fail): removing misplaced file
* chore(fail): removing misplaced file
* fix(remove ffv1): removing ffv1 as it does not support MP4
* docs(cheat sheet): adding depth and video encoding to the cheat sheet
* fix(lossless): tuning depth encoding parameters for lossless depth storage
* test(fix): fixing failing tests
* depth(ZMQ): excluding ZMQ from depth support
* Revert "depth(ZMQ): excluding ZMQ from depth support"
This reverts commit b95cf4e4c2.
* fix(image transforms): excluding depth frames from images transforms
* fix(typo): typo
* fix(stats): fixing stats computation for depth frames
* fix(TIFF vs. pytorch): adding an extra uint16 to float32 conversion for depth maps stored as raw TIFF images
* fix(typos): fixing typos
* test(dtype): fixing stats computation typing tests
---------
Signed-off-by: Steven Palma <imstevenpmwork@ieee.org>
Co-authored-by: Wensi (Vince) Ai <59036629+wensi-ai@users.noreply.github.com>
Co-authored-by: Steven Palma <imstevenpmwork@ieee.org>
Co-authored-by: Wensi Ai <wsai@stanford.edu>
393 lines
13 KiB
Python
393 lines
13 KiB
Python
# Copyright 2024 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 queue
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import time
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from multiprocessing import queues
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from unittest.mock import MagicMock, patch
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import numpy as np
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import pytest
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from PIL import Image
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pytest.importorskip("datasets", reason="datasets is required (install lerobot[dataset])")
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from lerobot.datasets.image_writer import (
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AsyncImageWriter,
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image_array_to_pil_image,
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safe_stop_image_writer,
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write_image,
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)
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from tests.fixtures.constants import DUMMY_HWC
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DUMMY_IMAGE = "test_image.png"
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def test_init_threading():
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writer = AsyncImageWriter(num_processes=0, num_threads=2)
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try:
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assert writer.num_processes == 0
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assert writer.num_threads == 2
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assert isinstance(writer.queue, queue.Queue)
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assert len(writer.threads) == 2
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assert len(writer.processes) == 0
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assert all(t.is_alive() for t in writer.threads)
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finally:
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writer.stop()
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def test_init_multiprocessing():
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writer = AsyncImageWriter(num_processes=2, num_threads=2)
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try:
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assert writer.num_processes == 2
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assert writer.num_threads == 2
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assert isinstance(writer.queue, queues.JoinableQueue)
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assert len(writer.threads) == 0
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assert len(writer.processes) == 2
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assert all(p.is_alive() for p in writer.processes)
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finally:
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writer.stop()
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def test_zero_threads():
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with pytest.raises(ValueError):
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AsyncImageWriter(num_processes=0, num_threads=0)
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def test_image_array_to_pil_image_float_array_wrong_range_0_255():
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image = np.random.rand(*DUMMY_HWC) * 255
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with pytest.raises(ValueError):
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image_array_to_pil_image(image)
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def test_image_array_to_pil_image_float_array_wrong_range_neg_1_1():
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image = np.random.rand(*DUMMY_HWC) * 2 - 1
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with pytest.raises(ValueError):
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image_array_to_pil_image(image)
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def test_image_array_to_pil_image_rgb(img_array_factory):
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img_array = img_array_factory(100, 100)
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result_image = image_array_to_pil_image(img_array)
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assert isinstance(result_image, Image.Image)
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assert result_image.size == (100, 100)
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assert result_image.mode == "RGB"
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def test_image_array_to_pil_image_pytorch_format(img_array_factory):
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img_array = img_array_factory(100, 100).transpose(2, 0, 1)
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result_image = image_array_to_pil_image(img_array)
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assert isinstance(result_image, Image.Image)
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assert result_image.size == (100, 100)
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assert result_image.mode == "RGB"
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def test_image_array_to_pil_image_single_channel(img_array_factory):
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img_array = img_array_factory(channels=1)
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with pytest.raises(ValueError, match="Unsupported single-channel image dtype"):
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image_array_to_pil_image(img_array)
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def test_image_array_to_pil_image_4_channels(img_array_factory):
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img_array = img_array_factory(channels=4)
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with pytest.raises(NotImplementedError):
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image_array_to_pil_image(img_array)
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def test_image_array_to_pil_image_float_array(img_array_factory):
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img_array = img_array_factory(dtype=np.float32)
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result_image = image_array_to_pil_image(img_array)
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assert isinstance(result_image, Image.Image)
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assert result_image.size == (100, 100)
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assert result_image.mode == "RGB"
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assert np.array(result_image).dtype == np.uint8
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def test_image_array_to_pil_image_uint8_array(img_array_factory):
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img_array = img_array_factory(dtype=np.float32)
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result_image = image_array_to_pil_image(img_array)
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assert isinstance(result_image, Image.Image)
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assert result_image.size == (100, 100)
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assert result_image.mode == "RGB"
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assert np.array(result_image).dtype == np.uint8
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def test_write_image_numpy(tmp_path, img_array_factory):
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image_array = img_array_factory()
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fpath = tmp_path / DUMMY_IMAGE
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write_image(image_array, fpath)
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assert fpath.exists()
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saved_image = np.array(Image.open(fpath))
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assert np.array_equal(image_array, saved_image)
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def test_write_image_image(tmp_path, img_factory):
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image_pil = img_factory()
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fpath = tmp_path / DUMMY_IMAGE
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write_image(image_pil, fpath)
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assert fpath.exists()
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saved_image = Image.open(fpath)
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assert list(saved_image.getdata()) == list(image_pil.getdata())
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assert np.array_equal(image_pil, saved_image)
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def test_write_image_exception(tmp_path):
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image_array = "invalid data"
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fpath = tmp_path / DUMMY_IMAGE
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with patch("lerobot.datasets.image_writer.logger") as mock_logger:
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write_image(image_array, fpath)
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mock_logger.error.assert_called()
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assert not fpath.exists()
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def test_save_image_numpy(tmp_path, img_array_factory):
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writer = AsyncImageWriter()
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try:
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image_array = img_array_factory()
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fpath = tmp_path / DUMMY_IMAGE
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fpath.parent.mkdir(parents=True, exist_ok=True)
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writer.save_image(image_array, fpath)
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writer.wait_until_done()
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assert fpath.exists()
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saved_image = np.array(Image.open(fpath))
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assert np.array_equal(image_array, saved_image)
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finally:
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writer.stop()
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def test_save_image_numpy_multiprocessing(tmp_path, img_array_factory):
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writer = AsyncImageWriter(num_processes=2, num_threads=2)
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try:
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image_array = img_array_factory()
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fpath = tmp_path / DUMMY_IMAGE
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writer.save_image(image_array, fpath)
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writer.wait_until_done()
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assert fpath.exists()
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saved_image = np.array(Image.open(fpath))
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assert np.array_equal(image_array, saved_image)
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finally:
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writer.stop()
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def test_save_image_torch(tmp_path, img_tensor_factory):
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writer = AsyncImageWriter()
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try:
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image_tensor = img_tensor_factory()
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fpath = tmp_path / DUMMY_IMAGE
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fpath.parent.mkdir(parents=True, exist_ok=True)
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writer.save_image(image_tensor, fpath)
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writer.wait_until_done()
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assert fpath.exists()
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saved_image = np.array(Image.open(fpath))
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expected_image = (image_tensor.permute(1, 2, 0).cpu().numpy() * 255).astype(np.uint8)
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assert np.array_equal(expected_image, saved_image)
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finally:
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writer.stop()
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def test_save_image_torch_multiprocessing(tmp_path, img_tensor_factory):
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writer = AsyncImageWriter(num_processes=2, num_threads=2)
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try:
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image_tensor = img_tensor_factory()
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fpath = tmp_path / DUMMY_IMAGE
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writer.save_image(image_tensor, fpath)
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writer.wait_until_done()
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assert fpath.exists()
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saved_image = np.array(Image.open(fpath))
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expected_image = (image_tensor.permute(1, 2, 0).cpu().numpy() * 255).astype(np.uint8)
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assert np.array_equal(expected_image, saved_image)
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finally:
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writer.stop()
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def test_save_image_pil(tmp_path, img_factory):
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writer = AsyncImageWriter()
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try:
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image_pil = img_factory()
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fpath = tmp_path / DUMMY_IMAGE
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fpath.parent.mkdir(parents=True, exist_ok=True)
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writer.save_image(image_pil, fpath)
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writer.wait_until_done()
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assert fpath.exists()
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saved_image = Image.open(fpath)
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assert list(saved_image.getdata()) == list(image_pil.getdata())
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finally:
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writer.stop()
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def test_save_image_pil_multiprocessing(tmp_path, img_factory):
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writer = AsyncImageWriter(num_processes=2, num_threads=2)
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try:
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image_pil = img_factory()
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fpath = tmp_path / DUMMY_IMAGE
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writer.save_image(image_pil, fpath)
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writer.wait_until_done()
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assert fpath.exists()
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saved_image = Image.open(fpath)
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assert list(saved_image.getdata()) == list(image_pil.getdata())
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finally:
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writer.stop()
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def test_save_image_invalid_data(tmp_path):
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writer = AsyncImageWriter()
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try:
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image_array = "invalid data"
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fpath = tmp_path / DUMMY_IMAGE
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fpath.parent.mkdir(parents=True, exist_ok=True)
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with patch("lerobot.datasets.image_writer.logger") as mock_logger:
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writer.save_image(image_array, fpath)
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writer.wait_until_done()
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mock_logger.error.assert_called()
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assert not fpath.exists()
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finally:
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writer.stop()
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def test_save_image_after_stop(tmp_path, img_array_factory):
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writer = AsyncImageWriter()
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writer.stop()
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image_array = img_array_factory()
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fpath = tmp_path / DUMMY_IMAGE
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writer.save_image(image_array, fpath)
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time.sleep(1)
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assert not fpath.exists()
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def test_stop():
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writer = AsyncImageWriter(num_processes=0, num_threads=2)
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writer.stop()
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assert not any(t.is_alive() for t in writer.threads)
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def test_stop_multiprocessing():
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writer = AsyncImageWriter(num_processes=2, num_threads=2)
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writer.stop()
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assert not any(p.is_alive() for p in writer.processes)
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def test_multiple_stops():
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writer = AsyncImageWriter()
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writer.stop()
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writer.stop() # Should not raise an exception
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assert not any(t.is_alive() for t in writer.threads)
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def test_multiple_stops_multiprocessing():
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writer = AsyncImageWriter(num_processes=2, num_threads=2)
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writer.stop()
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writer.stop() # Should not raise an exception
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assert not any(t.is_alive() for t in writer.threads)
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def test_wait_until_done(tmp_path, img_array_factory):
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writer = AsyncImageWriter(num_processes=0, num_threads=4)
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try:
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num_images = 100
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image_arrays = [img_array_factory(height=500, width=500) for _ in range(num_images)]
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fpaths = [tmp_path / f"frame_{i:06d}.png" for i in range(num_images)]
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for image_array, fpath in zip(image_arrays, fpaths, strict=True):
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fpath.parent.mkdir(parents=True, exist_ok=True)
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writer.save_image(image_array, fpath)
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writer.wait_until_done()
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for i, fpath in enumerate(fpaths):
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assert fpath.exists()
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saved_image = np.array(Image.open(fpath))
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assert np.array_equal(saved_image, image_arrays[i])
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finally:
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writer.stop()
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def test_wait_until_done_multiprocessing(tmp_path, img_array_factory):
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writer = AsyncImageWriter(num_processes=2, num_threads=2)
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try:
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num_images = 100
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image_arrays = [img_array_factory() for _ in range(num_images)]
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fpaths = [tmp_path / f"frame_{i:06d}.png" for i in range(num_images)]
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for image_array, fpath in zip(image_arrays, fpaths, strict=True):
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fpath.parent.mkdir(parents=True, exist_ok=True)
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writer.save_image(image_array, fpath)
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writer.wait_until_done()
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for i, fpath in enumerate(fpaths):
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assert fpath.exists()
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saved_image = np.array(Image.open(fpath))
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assert np.array_equal(saved_image, image_arrays[i])
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finally:
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writer.stop()
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def test_exception_handling(tmp_path, img_array_factory):
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writer = AsyncImageWriter()
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try:
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image_array = img_array_factory()
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with (
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patch.object(writer.queue, "put", side_effect=queue.Full("Queue is full")),
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pytest.raises(queue.Full) as exc_info,
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):
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writer.save_image(image_array, tmp_path / "test.png")
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assert str(exc_info.value) == "Queue is full"
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finally:
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writer.stop()
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def test_with_different_image_formats(tmp_path, img_array_factory):
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writer = AsyncImageWriter()
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try:
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image_array = img_array_factory()
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formats = ["png", "tiff", "tif"]
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for fmt in formats:
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fpath = tmp_path / f"test_image.{fmt}"
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write_image(image_array, fpath)
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assert fpath.exists()
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finally:
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writer.stop()
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def test_safe_stop_image_writer_decorator():
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class MockWriter:
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def __init__(self):
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self.image_writer = MagicMock(spec=AsyncImageWriter)
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class MockDataset:
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def __init__(self):
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self.writer = MockWriter()
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@safe_stop_image_writer
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def function_that_raises_exception(dataset=None):
|
|
raise Exception("Test exception")
|
|
|
|
dataset = MockDataset()
|
|
|
|
with pytest.raises(Exception) as exc_info:
|
|
function_that_raises_exception(dataset=dataset)
|
|
|
|
assert str(exc_info.value) == "Test exception"
|
|
dataset.writer.image_writer.stop.assert_called_once()
|
|
|
|
|
|
def test_main_process_time(tmp_path, img_tensor_factory):
|
|
writer = AsyncImageWriter()
|
|
try:
|
|
image_tensor = img_tensor_factory()
|
|
fpath = tmp_path / DUMMY_IMAGE
|
|
start_time = time.perf_counter()
|
|
writer.save_image(image_tensor, fpath)
|
|
end_time = time.perf_counter()
|
|
time_spent = end_time - start_time
|
|
# Might need to adjust this threshold depending on hardware
|
|
assert time_spent < 0.01, f"Main process time exceeded threshold: {time_spent}s"
|
|
writer.wait_until_done()
|
|
assert fpath.exists()
|
|
finally:
|
|
writer.stop()
|