From 235021ebc8672d7ef8434d603349a00ae48a5bd3 Mon Sep 17 00:00:00 2001 From: Daniel Falk Date: Fri, 25 Feb 2022 19:00:32 +0100 Subject: [PATCH] Add a video dataset This commit adds a video dataset that can read and write video files. The dataset is backed by OpenCVs video reader and writer and different buffer protocols such as PIL.Image and numpy.ndarray. There is one class for iterables (e.g. list of frames) and one for generators. Since large videos might not fit in memory, this ability allows us to read one frame from the video file, transform the frame and write it to another video file. Thus there is only need for one frame at a time in memory. The different codecs that are supported depends on the codecs installed and how OpenCV was compiled. Signed-off-by: Daniel Falk --- RELEASE.md | 7 + kedro/extras/datasets/video/__init__.py | 5 + kedro/extras/datasets/video/video_dataset.py | 358 ++++++++++++++++++ pyproject.toml | 1 + setup.py | 5 + test_requirements.txt | 1 + tests/extras/datasets/video/conftest.py | 107 ++++++ .../datasets/video/data/color_video.mp4 | Bin 0 -> 17452 bytes tests/extras/datasets/video/data/video.mjpeg | Bin 0 -> 430080 bytes tests/extras/datasets/video/data/video.mkv | Bin 0 -> 55145 bytes tests/extras/datasets/video/data/video.mp4 | Bin 0 -> 55132 bytes .../datasets/video/test_sliced_video.py | 56 +++ .../datasets/video/test_video_dataset.py | 186 +++++++++ .../datasets/video/test_video_objects.py | 170 +++++++++ tests/extras/datasets/video/utils.py | 49 +++ 15 files changed, 945 insertions(+) create mode 100644 kedro/extras/datasets/video/__init__.py create mode 100644 kedro/extras/datasets/video/video_dataset.py create mode 100644 tests/extras/datasets/video/conftest.py create mode 100644 tests/extras/datasets/video/data/color_video.mp4 create mode 100644 tests/extras/datasets/video/data/video.mjpeg create mode 100644 tests/extras/datasets/video/data/video.mkv create mode 100644 tests/extras/datasets/video/data/video.mp4 create mode 100644 tests/extras/datasets/video/test_sliced_video.py create mode 100644 tests/extras/datasets/video/test_video_dataset.py create mode 100644 tests/extras/datasets/video/test_video_objects.py create mode 100644 tests/extras/datasets/video/utils.py diff --git a/RELEASE.md b/RELEASE.md index 9f274159b7..764bc93748 100644 --- a/RELEASE.md +++ b/RELEASE.md @@ -14,6 +14,13 @@ * Make Kedro instantiate datasets from `kedro_datasets` with higher priority than `kedro.extras.datasets`. `kedro_datasets` is the namespace for the new `kedro-datasets` python package. * The config loader objects now implement `UserDict` and the configuration is accessed through `conf_loader['catalog']`. * You can configure config file patterns through `settings.py` without creating a custom config loader. +* Added `VideoDataSet` to read and write video files and interact with their frames: + +| Type | Description | Location | +| ------------------------------------ | -------------------------------------------------------------------------- | ----------------------------- | +| `video.VideoDataSet` | Read and write video files from a filesystem | `kedro.extras.datasets.video` | +| `video.video_dataset.SequenceVideo` | Create a video object from an iterable sequence to use with `VideoDataSet` | `kedro.extras.datasets.video` | +| `video.video_dataset.GeneratorVideo` | Create a video object from a generator to use with `VideoDataSet` | `kedro.extras.datasets.video` | ## Bug fixes and other changes * Fixed `kedro micropkg pull` for packages on PyPI. diff --git a/kedro/extras/datasets/video/__init__.py b/kedro/extras/datasets/video/__init__.py new file mode 100644 index 0000000000..f5f7af9461 --- /dev/null +++ b/kedro/extras/datasets/video/__init__.py @@ -0,0 +1,5 @@ +"""Dataset implementation to load/save data from/to a video file.""" + +__all__ = ["VideoDataSet"] + +from kedro.extras.datasets.video.video_dataset import VideoDataSet diff --git a/kedro/extras/datasets/video/video_dataset.py b/kedro/extras/datasets/video/video_dataset.py new file mode 100644 index 0000000000..b610006e99 --- /dev/null +++ b/kedro/extras/datasets/video/video_dataset.py @@ -0,0 +1,358 @@ +"""``VideoDataSet`` loads/saves video data from an underlying +filesystem (e.g.: local, S3, GCS). It uses OpenCV VideoCapture to read +and decode videos and OpenCV VideoWriter to encode and write video. +""" +import itertools +import tempfile +from collections import abc +from copy import deepcopy +from pathlib import Path, PurePosixPath +from typing import Any, Dict, Generator, Optional, Sequence, Tuple, Union + +import cv2 +import fsspec +import numpy as np +import PIL.Image + +from kedro.io.core import AbstractDataSet, get_protocol_and_path + + +class SlicedVideo: + """A representation of slices of other video types""" + + def __init__(self, video, slice_indexes): + self.video = video + self.indexes = range(*slice_indexes.indices(len(video))) + + def __getitem__(self, index: Union[int, slice]) -> PIL.Image.Image: + if isinstance(index, slice): + return SlicedVideo(self, index) + return self.video[self.indexes[index]] + + def __len__(self) -> int: + return len(self.indexes) + + def __getattr__(self, item): + return getattr(self.video, item) + + +class AbstractVideo(abc.Sequence): + """Base class for the underlying video data""" + + _n_frames = 0 + _index = 0 # Next available frame + + @property + def fourcc(self) -> str: + """Get the codec fourcc specification""" + raise NotImplementedError() + + @property + def fps(self) -> float: + """Get the video frame rate""" + raise NotImplementedError() + + @property + def size(self) -> Tuple[int, int]: + """Get the resolution of the video""" + raise NotImplementedError() + + def __len__(self) -> int: + return self._n_frames + + def __getitem__(self, index: Union[int, slice]): + """Get a frame from the video""" + raise NotImplementedError() + + +class FileVideo(AbstractVideo): + """A video object read from a file""" + + def __init__(self, filepath: str) -> None: + self._filepath = filepath + self._cap = cv2.VideoCapture(filepath) + self._n_frames = self._get_length() + + @property + def fourcc(self) -> str: + fourcc = self._cap.get(cv2.CAP_PROP_FOURCC) + return int(fourcc).to_bytes(4, "little").decode("ascii") + + @property + def fps(self) -> float: + return self._cap.get(cv2.CAP_PROP_FPS) + + @property + def size(self) -> Tuple[int, int]: + width = int(self._cap.get(cv2.CAP_PROP_FRAME_WIDTH)) + height = int(self._cap.get(cv2.CAP_PROP_FRAME_HEIGHT)) + return width, height + + def __getitem__(self, index: Union[int, slice]): + if isinstance(index, slice): + return SlicedVideo(self, index) + + if index < 0: + index += len(self) + if index >= len(self): + raise IndexError() + + if index != self._index: + self._cap.set(cv2.CAP_PROP_POS_FRAMES, index) + self._index = index + 1 # Next frame to decode after this + ret, frame_bgr = self._cap.read() + if not ret: + raise IndexError() + + height, width = frame_bgr.shape[:2] + return PIL.Image.frombuffer( # Convert to PIL image with RGB instead of BGR + "RGB", (width, height), frame_bgr, "raw", "BGR", 0, 0 + ) + + def _get_length(self) -> int: + # OpenCV's frame count might be an approximation depending on what + # headers are available in the video file + length = int(round(self._cap.get(cv2.CAP_PROP_FRAME_COUNT))) + if length >= 0: + return length + + # Getting the frame count with OpenCV can fail on some video files, + # counting the frames would be too slow so it is better to raise an exception. + raise ValueError( + "Failed to load video since number of frames can't be inferred" + ) + + +class SequenceVideo(AbstractVideo): + """A video object read from an indexable sequence of frames""" + + def __init__( + self, frames: Sequence[PIL.Image.Image], fps: float, fourcc: str = "mp4v" + ) -> None: + self._n_frames = len(frames) + self._frames = frames + self._fourcc = fourcc + self._size = frames[0].size + self._fps = fps + + @property + def fourcc(self) -> str: + return self._fourcc + + @property + def fps(self) -> float: + return self._fps + + @property + def size(self) -> Tuple[int, int]: + return self._size + + def __getitem__(self, index: Union[int, slice]): + if isinstance(index, slice): + return SlicedVideo(self, index) + return self._frames[index] + + +class GeneratorVideo(AbstractVideo): + """A video object with frames yielded by a generator""" + + def __init__( + self, + frames: Generator[PIL.Image.Image, None, None], + length, + fps: float, + fourcc: str = "mp4v", + ) -> None: + self._n_frames = length + first = next(frames) + self._gen = itertools.chain([first], frames) + self._fourcc = fourcc + self._size = first.size + self._fps = fps + + @property + def fourcc(self) -> str: + return self._fourcc + + @property + def fps(self) -> float: + return self._fps + + @property + def size(self) -> Tuple[int, int]: + return self._size + + def __getitem__(self, index: Union[int, slice]): + raise NotImplementedError("Underlying video is a generator") + + def __next__(self): + return next(self._gen) + + def __iter__(self): + return self + + +class VideoDataSet(AbstractDataSet[AbstractVideo, AbstractVideo]): + """``VideoDataSet`` loads / save video data from a given filepath as sequence + of PIL.Image.Image using OpenCV. + + Example adding a catalog entry with + `YAML API + `_: + + .. code-block:: yaml + >>> cars: + >>> type: video.VideoDataSet + >>> filepath: data/01_raw/cars.mp4 + >>> + >>> cars: + >>> type: video.VideoDataSet + >>> filepath: data/01_raw/cars.mp4 + >>> filepath: s3://your_bucket/data/02_intermediate/company/motorbikes.mp4 + >>> credentials: dev_s3 + >>> + + + Example using Python API: + :: + + >>> from kedro.extras.datasets.video import VideoDataSet + >>> import numpy as np + >>> + >>> video = VideoDataSet(filepath='/video/file/path.mp4').load() + >>> frame = video[0] + >>> np.sum(np.asarray(frame)) + + + Example creating a video from numpy frames using Python API: + :: + + >>> from kedro.extras.datasets.video.video_dataset import VideoDataSet, SequenceVideo + >>> import numpy as np + >>> from PIL import Image + >>> + >>> frame = np.ones((640,480,3), dtype=np.uint8) * 255 + >>> imgs = [] + >>> for i in range(255): + >>> imgs.append(Image.fromarray(frame)) + >>> frame -= 1 + >>> + >>> video = VideoDataSet("my_video.mp4") + >>> video.save(SequenceVideo(imgs, fps=25)) + + + Example creating a video from numpy frames using a generator and Python API: + :: + + >>> from kedro.extras.datasets.video.video_dataset import VideoDataSet, GeneratorVideo + >>> import numpy as np + >>> from PIL import Image + >>> + >>> def gen(): + >>> frame = np.ones((640,480,3), dtype=np.uint8) * 255 + >>> for i in range(255): + >>> yield Image.fromarray(frame) + >>> frame -= 1 + >>> + >>> video = VideoDataSet("my_video.mp4") + >>> video.save(GeneratorVideo(gen(), fps=25, length=None)) + + """ + + # pylint: disable=too-many-arguments + def __init__( + self, + filepath: str, + fourcc: Optional[str] = "mp4v", + credentials: Dict[str, Any] = None, + fs_args: Dict[str, Any] = None, + ) -> None: + """Creates a new instance of VideoDataSet to load / save video data for given filepath. + + Args: + filepath: The location of the video file to load / save data. + fourcc: The codec to use when writing video, note that depending on how opencv is + installed there might be more or less codecs avaiable. If set to None, the + fourcc from the video object will be used. + credentials: Credentials required to get access to the underlying filesystem. + E.g. for ``GCSFileSystem`` it should look like `{"token": None}`. + fs_args: Extra arguments to pass into underlying filesystem class constructor + (e.g. `{"project": "my-project"}` for ``GCSFileSystem``). + """ + # parse the path and protocol (e.g. file, http, s3, etc.) + protocol, path = get_protocol_and_path(filepath) + self._protocol = protocol + self._filepath = PurePosixPath(path) + self._fourcc = fourcc + _fs_args = deepcopy(fs_args) or {} + _credentials = deepcopy(credentials) or {} + self._storage_options = {**_credentials, **_fs_args} + self._fs = fsspec.filesystem(self._protocol, **self._storage_options) + + def _load(self) -> AbstractVideo: + """Loads data from the video file. + + Returns: + Data from the video file as a AbstractVideo object + """ + with fsspec.open( + f"filecache::{self._protocol}://{self._filepath}", + mode="rb", + **{self._protocol: self._storage_options}, + ) as fs_file: + return FileVideo(fs_file.name) + + def _save(self, data: AbstractVideo) -> None: + """Saves video data to the specified filepath.""" + if self._protocol == "file": + # Write directly to the local file destination + self._write_to_filepath(data, str(self._filepath)) + else: + # VideoWriter can't write to an open file object, instead write to a + # local tmpfile and then copy that to the destination with fsspec. + # Note that the VideoWriter fails to write to the file on Windows if + # the file is already open, thus we can't use NamedTemporaryFile. + with tempfile.TemporaryDirectory() as tmp_dir: + tmp_file = Path(tmp_dir) / self._filepath.name + self._write_to_filepath(data, str(tmp_file)) + with fsspec.open( + f"{self._protocol}://{self._filepath}", + "wb", + **self._storage_options, + ) as f_target: + with tmp_file.open("r+b") as f_tmp: + f_target.write(f_tmp.read()) + + def _write_to_filepath(self, video: AbstractVideo, filepath: str) -> None: + # TODO: This uses the codec specified in the VideoDataSet if it is not None, this is due + # to compatibility issues since e.g. h264 coded is licensed and is thus not included in + # opencv if installed from a binary distribution. Since a h264 video can be read, but not + # written, it would be error prone to use the videos fourcc code. Further, an issue is + # that the video object does not know what container format will be used since that is + # selected by the suffix in the file name of the VideoDataSet. Some combinations of codec + # and container format might not work or will have bad support. + fourcc = self._fourcc or video.fourcc + + writer = cv2.VideoWriter( + filepath, cv2.VideoWriter_fourcc(*fourcc), video.fps, video.size + ) + if not writer.isOpened(): + raise ValueError( + "Failed to open video writer with params: " + + f"fourcc={fourcc} fps={video.fps} size={video.size[0]}x{video.size[1]} " + + f"path={filepath}" + ) + try: + for frame in iter(video): + writer.write( # PIL images are RGB, opencv expects BGR + np.asarray(frame)[:, :, ::-1] + ) + finally: + writer.release() + + def _describe(self) -> Dict[str, Any]: + return dict(filepath=self._filepath, protocol=self._protocol) + + def _exists(self) -> bool: + return self._fs.exists(self._filepath) diff --git a/pyproject.toml b/pyproject.toml index 9c3e01124a..9b17440f44 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -17,6 +17,7 @@ load-plugins = [ "pylint.extensions.docparams", "pylint.extensions.no_self_use" ] +extension-pkg-whitelist = "cv2" unsafe-load-any-extension = false [tool.pylint.messages_control] disable = [ diff --git a/setup.py b/setup.py index 37a3727081..45aa6887de 100644 --- a/setup.py +++ b/setup.py @@ -79,6 +79,9 @@ def _collect_requirements(requires): "pandas.GenericDataSet": [PANDAS], } pillow_require = {"pillow.ImageDataSet": ["Pillow~=9.0"]} +video_require = { + "video.VideoDataSet": ["opencv-python~=4.5.5.64"] +} plotly_require = { "plotly.PlotlyDataSet": [PANDAS, "plotly>=4.8.0, <6.0"], "plotly.JSONDataSet": ["plotly>=4.8.0, <6.0"], @@ -122,6 +125,7 @@ def _collect_requirements(requires): "networkx": _collect_requirements(networkx_require), "pandas": _collect_requirements(pandas_require), "pillow": _collect_requirements(pillow_require), + "video": _collect_requirements(video_require), "plotly": _collect_requirements(plotly_require), "redis": _collect_requirements(redis_require), "spark": _collect_requirements(spark_require), @@ -136,6 +140,7 @@ def _collect_requirements(requires): **networkx_require, **pandas_require, **pillow_require, + **video_require, **plotly_require, **spark_require, **tensorflow_required, diff --git a/test_requirements.txt b/test_requirements.txt index 52305e865a..5d10f0371d 100644 --- a/test_requirements.txt +++ b/test_requirements.txt @@ -30,6 +30,7 @@ memory_profiler>=0.50.0, <1.0 moto==1.3.7; python_version < '3.10' moto==3.0.4; python_version == '3.10' networkx~=2.4 +opencv-python~=4.5.5.64 openpyxl>=3.0.3, <4.0 pandas-gbq>=0.12.0, <1.0 pandas~=1.3 # 1.3 for read_xml/to_xml diff --git a/tests/extras/datasets/video/conftest.py b/tests/extras/datasets/video/conftest.py new file mode 100644 index 0000000000..ff084cdb5e --- /dev/null +++ b/tests/extras/datasets/video/conftest.py @@ -0,0 +1,107 @@ +from pathlib import Path + +import pytest +from PIL import Image +from utils import TEST_FPS, TEST_HEIGHT, TEST_WIDTH + +from kedro.extras.datasets.video.video_dataset import ( + FileVideo, + GeneratorVideo, + SequenceVideo, +) + + +@pytest.fixture(scope="module") +def red_frame(): + return Image.new("RGB", (TEST_WIDTH, TEST_HEIGHT), (255, 0, 0)) + + +@pytest.fixture(scope="module") +def green_frame(): + return Image.new("RGB", (TEST_WIDTH, TEST_HEIGHT), (0, 255, 0)) + + +@pytest.fixture(scope="module") +def blue_frame(): + return Image.new("RGB", (TEST_WIDTH, TEST_HEIGHT), (0, 0, 255)) + + +@pytest.fixture(scope="module") +def yellow_frame(): + return Image.new("RGB", (TEST_WIDTH, TEST_HEIGHT), (255, 255, 0)) + + +@pytest.fixture(scope="module") +def purple_frame(): + return Image.new("RGB", (TEST_WIDTH, TEST_HEIGHT), (255, 0, 255)) + + +@pytest.fixture +def color_video(red_frame, green_frame, blue_frame, yellow_frame, purple_frame): + return SequenceVideo( + [red_frame, green_frame, blue_frame, yellow_frame, purple_frame], + fps=TEST_FPS, + ) + + +@pytest.fixture +def color_video_generator( + red_frame, green_frame, blue_frame, yellow_frame, purple_frame +): + sequence = [red_frame, green_frame, blue_frame, yellow_frame, purple_frame] + + def generator(): + yield from sequence + + return GeneratorVideo( + generator(), + length=len(sequence), + fps=TEST_FPS, + ) + + +@pytest.fixture +def filepath_mp4(): + """This is a real video converted to mp4/h264 with ffmpeg command""" + return str(Path(__file__).parent / "data/video.mp4") + + +@pytest.fixture +def filepath_mkv(): + """This a a real video recoreded with an Axis network camera""" + return str(Path(__file__).parent / "data/video.mkv") + + +@pytest.fixture +def filepath_mjpeg(): + """This is a real video recorded with an Axis network camera""" + return str(Path(__file__).parent / "data/video.mjpeg") + + +@pytest.fixture +def filepath_color_mp4(): + """This is a video created with the OpenCV VideoWriter + + it contains 5 frames which each is a single color: red, green, blue, yellow, purple + """ + return str(Path(__file__).parent / "data/color_video.mp4") + + +@pytest.fixture +def mp4_object(filepath_mp4): + return 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red = np.array(slice_red_green[0]) + assert red.shape == (TEST_HEIGHT, TEST_WIDTH, 3) + assert np.all(red[:, :, 0] == 255) + assert np.all(red[:, :, 1] == 0) + assert np.all(red[:, :, 2] == 0) + + def test_slice_sequence_video_last_as_index(self, color_video): + """Test slicing and then indexing a SequenceVideo""" + slice_blue_yellow_purple = color_video[2:5] + purple = np.array(slice_blue_yellow_purple[2]) + assert purple.shape == (TEST_HEIGHT, TEST_WIDTH, 3) + assert np.all(purple[:, :, 0] == 255) + assert np.all(purple[:, :, 1] == 0) + assert np.all(purple[:, :, 2] == 255) + + def test_slice_sequence_video_last_as_end(self, color_video): + """Test slicing and then indexing a SequenceVideo""" + slice_blue_yellow_purple = color_video[2:] + purple = np.array(slice_blue_yellow_purple[-1]) + assert purple.shape == (TEST_HEIGHT, TEST_WIDTH, 3) + assert np.all(purple[:, :, 0] == 255) + assert np.all(purple[:, :, 1] == 0) + assert np.all(purple[:, :, 2] == 255) + + def test_slice_sequence_attribute(self, color_video): + """Test that attributes from the base class are reachable from sliced views""" + slice_red_green = color_video[:2] + assert slice_red_green.fps == color_video.fps + + def test_slice_sliced_video(self, color_video): + """Test slicing and then indexing a SlicedVideo""" + slice_green_blue_yellow = color_video[1:4] + slice_green_blue = slice_green_blue_yellow[:-1] + blue = np.array(slice_green_blue[1]) + assert blue.shape == (TEST_HEIGHT, TEST_WIDTH, 3) + assert np.all(blue[:, :, 0] == 0) + assert np.all(blue[:, :, 1] == 0) + assert np.all(blue[:, :, 2] == 255) + + def test_slice_file_video_first(self, mp4_object): + """Test slicing and then indexing a FileVideo""" + sliced_video = mp4_object[:2] + assert np.all(np.array(sliced_video[0]) == np.array(mp4_object[0])) + + def test_slice_file_video_last(self, mp4_object): + """Test slicing and then indexing a FileVideo""" + sliced_video = mp4_object[-2:] + assert np.all(np.array(sliced_video[-1]) == np.array(mp4_object[-1])) diff --git a/tests/extras/datasets/video/test_video_dataset.py b/tests/extras/datasets/video/test_video_dataset.py new file mode 100644 index 0000000000..81c1952513 --- /dev/null +++ b/tests/extras/datasets/video/test_video_dataset.py @@ -0,0 +1,186 @@ +import boto3 +import pytest +from moto import mock_s3 +from utils import TEST_FPS, assert_videos_equal + +from kedro.extras.datasets.video import VideoDataSet +from kedro.extras.datasets.video.video_dataset import FileVideo, SequenceVideo +from kedro.io import DataSetError + +S3_BUCKET_NAME = "test_bucket" +S3_KEY_PATH = "video" +S3_FULL_PATH = f"s3://{S3_BUCKET_NAME}/{S3_KEY_PATH}/" +AWS_CREDENTIALS = {"key": "FAKE_ACCESS_KEY", "secret": "FAKE_SECRET_KEY"} + + +@pytest.fixture +def tmp_filepath_mp4(tmp_path): + return (tmp_path / "test.mp4").as_posix() + + +@pytest.fixture +def tmp_filepath_avi(tmp_path): + return (tmp_path / "test.mjpeg").as_posix() + + +@pytest.fixture +def empty_dataset_mp4(tmp_filepath_mp4): + return VideoDataSet(filepath=tmp_filepath_mp4) + + +@pytest.fixture +def empty_dataset_avi(tmp_filepath_avi): + return VideoDataSet(filepath=tmp_filepath_avi) + + +@pytest.fixture +def mocked_s3_bucket(): + """Create a bucket for testing using moto.""" + with mock_s3(): + conn = boto3.client( + "s3", + region_name="us-east-1", + aws_access_key_id=AWS_CREDENTIALS["key"], + aws_secret_access_key=AWS_CREDENTIALS["secret"], + ) + conn.create_bucket(Bucket=S3_BUCKET_NAME) + yield conn + + +class TestVideoDataSet: + def test_load_mp4(self, filepath_mp4, mp4_object): + """Loading a mp4 dataset should create a FileVideo""" + ds = VideoDataSet(filepath_mp4) + loaded_video = ds.load() + assert_videos_equal(loaded_video, mp4_object) + + def test_save_and_load_mp4(self, empty_dataset_mp4, mp4_object): + """Test saving and reloading the data set.""" + empty_dataset_mp4.save(mp4_object) + reloaded_video = empty_dataset_mp4.load() + assert_videos_equal(mp4_object, reloaded_video) + assert reloaded_video.fourcc == empty_dataset_mp4._fourcc + + @pytest.mark.skip( + reason="Only one available codec that is typically installed when testing" + ) + def test_save_with_other_codec(self, tmp_filepath_mp4, mp4_object): + """Test saving the video with another codec than default.""" + save_fourcc = "xvid" + ds = VideoDataSet(filepath=tmp_filepath_mp4, fourcc=save_fourcc) + ds.save(mp4_object) + reloaded_video = ds.load() + assert reloaded_video.fourcc == save_fourcc + + def test_save_with_derived_codec(self, tmp_filepath_mp4, color_video): + """Test saving video by the codec specified in the video object""" + ds = VideoDataSet(filepath=tmp_filepath_mp4, fourcc=None) + ds.save(color_video) + reloaded_video = ds.load() + assert reloaded_video.fourcc == color_video.fourcc + + def test_saved_fps(self, empty_dataset_mp4, color_video): + """Verify that a saved video has the same framerate as specified in the video object""" + empty_dataset_mp4.save(color_video) + reloaded_video = empty_dataset_mp4.load() + assert reloaded_video.fps == TEST_FPS + + def test_save_sequence_video(self, color_video, empty_dataset_mp4): + """Test save (and load) a SequenceVideo object""" + empty_dataset_mp4.save(color_video) + reloaded_video = empty_dataset_mp4.load() + assert_videos_equal(color_video, reloaded_video) + + def test_save_generator_video( + self, color_video_generator, empty_dataset_mp4, color_video + ): + """Test save (and load) a GeneratorVideo object + + Since the GeneratorVideo is exhaused after saving the video to file we use + the SequenceVideo (color_video) which has the same frames to compare the + loaded video to. + """ + empty_dataset_mp4.save(color_video_generator) + reloaded_video = empty_dataset_mp4.load() + assert_videos_equal(color_video, reloaded_video) + + def test_exists(self, empty_dataset_mp4, mp4_object): + """Test `exists` method invocation for both existing and + nonexistent data set.""" + assert not empty_dataset_mp4.exists() + empty_dataset_mp4.save(mp4_object) + assert empty_dataset_mp4.exists() + + @pytest.mark.skip(reason="Can't deal with videos with missing time info") + def test_convert_video(self, empty_dataset_mp4, mjpeg_object): + """Load a file video in mjpeg format and save in mp4v""" + empty_dataset_mp4.save(mjpeg_object) + reloaded_video = empty_dataset_mp4.load() + assert_videos_equal(mjpeg_object, reloaded_video) + + def test_load_missing_file(self, empty_dataset_mp4): + """Check the error when trying to load missing file.""" + pattern = r"Failed while loading data from data set VideoDataSet\(.*\)" + with pytest.raises(DataSetError, match=pattern): + empty_dataset_mp4.load() + + def test_save_s3(self, mp4_object, mocked_s3_bucket, tmp_path): + """Test to save a VideoDataSet to S3 storage""" + video_name = "video.mp4" + + dataset = VideoDataSet( + filepath=S3_FULL_PATH + video_name, credentials=AWS_CREDENTIALS + ) + dataset.save(mp4_object) + + tmp_file = tmp_path / video_name + mocked_s3_bucket.download_file( + Bucket=S3_BUCKET_NAME, + Key=S3_KEY_PATH + "/" + video_name, + Filename=str(tmp_file), + ) + reloaded_video = FileVideo(str(tmp_file)) + assert_videos_equal(reloaded_video, mp4_object) + + @pytest.mark.xfail + @pytest.mark.parametrize( + "fourcc, suffix", + [ + ("mp4v", "mp4"), + ("mp4v", "mjpeg"), + ("mp4v", "avi"), + ("avc1", "mp4"), + ("avc1", "mjpeg"), + ("avc1", "avi"), + ("mjpg", "mp4"), + ("mjpg", "mjpeg"), + ("mjpg", "avi"), + ("xvid", "mp4"), + ("xvid", "mjpeg"), + ("xvid", "avi"), + ("x264", "mp4"), + ("x264", "mjpeg"), + ("x264", "avi"), + ("divx", "mp4"), + ("divx", "mjpeg"), + ("divx", "avi"), + ("fmp4", "mp4"), + ("fmp4", "mjpeg"), + ("fmp4", "avi"), + ], + ) + def test_video_codecs(self, fourcc, suffix, color_video): + """Test different codec and container combinations + + Some of these are expected to fail depending on what + codecs are installed on the machine. + """ + video_name = f"video.{suffix}" + video = SequenceVideo(color_video._frames, 25, fourcc) + ds = VideoDataSet(video_name, fourcc=None) + ds.save(video) + # We also need to verify that the correct codec was used + # since OpenCV silently (with a warning in the log) fall backs to + # another codec if one specified is not compatible with the container + reloaded_video = ds.load() + assert reloaded_video.fourcc == fourcc diff --git a/tests/extras/datasets/video/test_video_objects.py b/tests/extras/datasets/video/test_video_objects.py new file mode 100644 index 0000000000..66a284fa60 --- /dev/null +++ b/tests/extras/datasets/video/test_video_objects.py @@ -0,0 +1,170 @@ +import numpy as np +import pytest +from utils import ( + DEFAULT_FOURCC, + MJPEG_FOURCC, + MJPEG_FPS, + MJPEG_LEN, + MJPEG_SIZE, + MKV_FOURCC, + MKV_FPS, + MKV_LEN, + MKV_SIZE, + MP4_FOURCC, + MP4_FPS, + MP4_LEN, + MP4_SIZE, + TEST_FPS, + TEST_HEIGHT, + TEST_NUM_COLOR_FRAMES, + TEST_WIDTH, + assert_images_equal, +) + +from kedro.extras.datasets.video.video_dataset import ( + FileVideo, + GeneratorVideo, + SequenceVideo, +) + + +class TestSequenceVideo: + def test_sequence_video_indexing_first(self, color_video, red_frame): + """Test indexing a SequenceVideo""" + red = np.array(color_video[0]) + assert red.shape == (TEST_HEIGHT, TEST_WIDTH, 3) + assert np.all(red == red_frame) + + def test_sequence_video_indexing_last(self, color_video, purple_frame): + """Test indexing a SequenceVideo""" + purple = np.array(color_video[-1]) + assert purple.shape == (TEST_HEIGHT, TEST_WIDTH, 3) + assert np.all(purple == purple_frame) + + def test_sequence_video_iterable(self, color_video): + """Test iterating a SequenceVideo""" + for i, img in enumerate(map(np.array, color_video)): + assert np.all(img == np.array(color_video[i])) + assert i == TEST_NUM_COLOR_FRAMES - 1 + + def test_sequence_video_fps(self, color_video): + # Test the one set by the fixture + assert color_video.fps == TEST_FPS + + # Test creating with another fps + test_fps_new = 123 + color_video_new = SequenceVideo(color_video._frames, fps=test_fps_new) + assert color_video_new.fps == test_fps_new + + def test_sequence_video_len(self, color_video): + assert len(color_video) == TEST_NUM_COLOR_FRAMES + + def test_sequence_video_size(self, color_video): + assert color_video.size == (TEST_WIDTH, TEST_HEIGHT) + + def test_sequence_video_fourcc_default_value(self, color_video): + assert color_video.fourcc == DEFAULT_FOURCC + + def test_sequence_video_fourcc(self, color_video): + fourcc_new = "mjpg" + assert ( + DEFAULT_FOURCC != fourcc_new + ), "Test does not work if new test value is same as default" + color_video_new = SequenceVideo( + color_video._frames, fps=TEST_FPS, fourcc=fourcc_new + ) + assert color_video_new.fourcc == fourcc_new + + +class TestGeneratorVideo: + def test_generator_video_iterable(self, color_video_generator, color_video): + """Test iterating a GeneratorVideo + + The content of the mock GeneratorVideo should be the same as the SequenceVideo, + the content in the later is tested in other unit tests and can thus be trusted + """ + for i, img in enumerate(map(np.array, color_video_generator)): + assert np.all(img == np.array(color_video[i])) + assert i == TEST_NUM_COLOR_FRAMES - 1 + + def test_generator_video_fps(self, color_video_generator): + # Test the one set by the fixture + assert color_video_generator.fps == TEST_FPS + + # Test creating with another fps + test_fps_new = 123 + color_video_new = GeneratorVideo( + color_video_generator._gen, length=TEST_NUM_COLOR_FRAMES, fps=test_fps_new + ) + assert color_video_new.fps == test_fps_new + + def test_generator_video_len(self, color_video_generator): + assert len(color_video_generator) == TEST_NUM_COLOR_FRAMES + + def test_generator_video_size(self, color_video_generator): + assert color_video_generator.size == (TEST_WIDTH, TEST_HEIGHT) + + def test_generator_video_fourcc_default_value(self, color_video_generator): + assert color_video_generator.fourcc == DEFAULT_FOURCC + + def test_generator_video_fourcc(self, color_video_generator): + fourcc_new = "mjpg" + assert ( + DEFAULT_FOURCC != fourcc_new + ), "Test does not work if new test value is same as default" + color_video_new = GeneratorVideo( + color_video_generator._gen, + length=TEST_NUM_COLOR_FRAMES, + fps=TEST_FPS, + fourcc=fourcc_new, + ) + assert color_video_new.fourcc == fourcc_new + + +class TestFileVideo: + @pytest.mark.skip(reason="Can't deal with videos with missing time info") + def test_file_props_mjpeg(self, mjpeg_object): + assert mjpeg_object.fourcc == MJPEG_FOURCC + assert mjpeg_object.fps == MJPEG_FPS + assert mjpeg_object.size == MJPEG_SIZE + assert len(mjpeg_object) == MJPEG_LEN + + def test_file_props_mkv(self, mkv_object): + assert mkv_object.fourcc == MKV_FOURCC + assert mkv_object.fps == MKV_FPS + assert mkv_object.size == MKV_SIZE + assert len(mkv_object) == MKV_LEN + + def test_file_props_mp4(self, mp4_object): + assert mp4_object.fourcc == MP4_FOURCC + assert mp4_object.fps == MP4_FPS + assert mp4_object.size == MP4_SIZE + assert len(mp4_object) == MP4_LEN + + def test_file_index_first(self, color_video_object, red_frame): + assert_images_equal(color_video_object[0], red_frame) + + def test_file_index_last_by_index(self, color_video_object, purple_frame): + assert_images_equal(color_video_object[TEST_NUM_COLOR_FRAMES - 1], purple_frame) + + def test_file_index_last(self, color_video_object, purple_frame): + assert_images_equal(color_video_object[-1], purple_frame) + + def test_file_video_failed_capture(self, mocker): + """Validate good behavior on failed decode + + The best behavior in this case is not obvious, the len property of the + video object specifies more frames than is actually possible to decode. We + cannot know this in advance without spending loads of time to decode all frames + in order to count them.""" + mock_cv2 = mocker.patch("kedro.extras.datasets.video.video_dataset.cv2") + mock_cap = mock_cv2.VideoCapture.return_value = mocker.Mock() + mock_cap.get.return_value = 2 # Set the length of the video + ds = FileVideo("/a/b/c") + + mock_cap.read.return_value = True, np.zeros((1, 1)) + assert ds[0] + + mock_cap.read.return_value = False, None + with pytest.raises(IndexError): + ds[1] diff --git a/tests/extras/datasets/video/utils.py b/tests/extras/datasets/video/utils.py new file mode 100644 index 0000000000..6b675aed2f --- /dev/null +++ b/tests/extras/datasets/video/utils.py @@ -0,0 +1,49 @@ +import itertools + +import numpy as np +from PIL import ImageChops + +TEST_WIDTH = 640 # Arbitrary value for testing +TEST_HEIGHT = 480 # Arbitrary value for testing +TEST_FPS = 1 # Arbitrary value for testing + +TEST_NUM_COLOR_FRAMES = ( + 5 # This should be the same as number of frames in conftest videos +) +DEFAULT_FOURCC = "mp4v" # The expected default fourcc value + +# This is video data extracted from the video files with ffmpeg command +MKV_SIZE = (640, 360) +MKV_FPS = 50 +MKV_FOURCC = "h264" +MKV_LEN = 109 # from ffprobe + +MP4_SIZE = (640, 360) +MP4_FPS = 50 +MP4_FOURCC = "avc1" +MP4_LEN = 109 # from ffprobe + +MJPEG_SIZE = (640, 360) +MJPEG_FPS = 25 # From ffprobe, not reported by ffmpeg command +# I'm not sure that MJPE is the correct fourcc code for +# mjpeg video since I cannot find any official reference to +# that code. This is however what the openCV VideoCapture +# reports for the video, so we leave it like this for now.. +MJPEG_FOURCC = "mjpe" +MJPEG_LEN = 24 # from ffprobe + + +def assert_images_equal(image_1, image_2): + """Assert that two images are approximately equal, allow for some + compression artifacts""" + assert image_1.size == image_2.size + diff = np.asarray(ImageChops.difference(image_1, image_2)) + assert np.mean(diff) < 5 + assert np.mean(diff > 50) < 0.01 # Max 1% of pixels + + +def assert_videos_equal(video_1, video_2): + assert len(video_1) == len(video_2) + + for image_1, image_2 in itertools.zip_longest(video_1, video_2): + assert_images_equal(image_1, image_2)