kedro_datasets_experimental.video.VideoDataset¶
- class kedro_datasets_experimental.video.VideoDataset(*, filepath, fourcc='mp4v', credentials=None, fs_args=None, metadata=None)[source]¶
VideoDatasetloads / save video data from a given filepath as sequence of PIL.Image.Image using OpenCV.Example usage for the YAML API:
cars: type: video.VideoDataset filepath: data/01_raw/cars.mp4 motorbikes: type: video.VideoDataset filepath: s3://your_bucket/data/02_intermediate/company/motorbikes.mp4 credentials: dev_s3
Example usage for the Python API:
from kedro_datasets.video import VideoDataset import numpy as np video = VideoDataset( ... filepath="https://storage.googleapis.com/gtv-videos-bucket/sample/ForBiggerBlazes.mp4" ... ).load() frame = video[0]
Example creating a video from numpy frames using Python API:
from kedro_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(filepath=tmp_path / "my_video.mp4") video.save(SequenceVideo(imgs, fps=25))
Example creating a video from numpy frames using a generator and the Python API:
from kedro_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(filepath=tmp_path / "my_video.mp4") video.save(GeneratorVideo(gen(), fps=25, length=None))
Methods
exists()Checks whether a dataset's output already exists by calling the provided _exists() method.
from_config(name, config[, load_version, ...])Create a dataset instance using the configuration provided.
load()Loads data from the video file.
release()Release any cached data.
save(data)Saves video data to the specified filepath.
- __init__(*, filepath, fourcc='mp4v', credentials=None, fs_args=None, metadata=None)[source]¶
Creates a new instance of VideoDataset to load / save video data for given filepath.
- Parameters:
filepath (
str) – The location of the video file to load / save data.fourcc (
Optional[str]) – 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 (
Optional[dict[str,Any]]) – Credentials required to get access to the underlying filesystem. E.g. forGCSFileSystemit should look like {“token”: None}.fs_args (
Optional[dict[str,Any]]) – Extra arguments to pass into underlying filesystem class constructor (e.g. {“project”: “my-project”} forGCSFileSystem).metadata (
Optional[dict[str,Any]]) – Any arbitrary metadata. This is ignored by Kedro, but may be consumed by users or external plugins.
- exists()¶
Checks whether a dataset’s output already exists by calling the provided _exists() method.
- Return type:
- Returns:
Flag indicating whether the output already exists.
- Raises:
DatasetError – when underlying exists method raises error.
- classmethod from_config(name, config, load_version=None, save_version=None)¶
Create a dataset instance using the configuration provided.
- Parameters:
name (
str) – Data set name.load_version (
Optional[str]) – Version string to be used forloadoperation if the dataset is versioned. Has no effect on the dataset if versioning was not enabled.save_version (
Optional[str]) – Version string to be used forsaveoperation if the dataset is versioned. Has no effect on the dataset if versioning was not enabled.
- Return type:
- Returns:
An instance of an
AbstractDatasetsubclass.- Raises:
DatasetError – When the function fails to create the dataset from its config.
- load()[source]¶
Loads data from the video file.
- Return type:
AbstractVideo- Returns:
Data from the video file as a AbstractVideo object
- release()¶
Release any cached data.
- Raises:
DatasetError – when underlying release method raises error.
- Return type: