- nvidia.dali.fn.experimental.readers.video(*inputs, **kwargs)¶
Loads and decodes video files using FFmpeg.
The video streams can be in most of the container file formats. FFmpeg is used to parse video containers and returns a batch of sequences of
sequence_lengthframes with shape
(N, F, H, W, C), where
Nis the batch size, and
Fis the number of frames).
Containers which do not support indexing, like MPEG, require DALI to build the index.
DALI will go through the video and mark keyframes to be able to seek effectively, even in the variable frame rate scenario.
- Supported backends
- Keyword Arguments:
sequence_length (int) – Frames to load per sequence.
bytes_per_sample_hint (int or list of int, optional, default = ) –
Output size hint, in bytes per sample.
If specified, the operator’s outputs residing in GPU or page-locked host memory will be preallocated to accommodate a batch of samples of this size.
dont_use_mmap (bool, optional, default = False) –
If set to True, the Loader will use plain file I/O instead of trying to map the file in memory.
Mapping provides a small performance benefit when accessing a local file system, but most network file systems, do not provide optimum performance.
filenames (str or list of str, optional, default = ) – Absolute paths to the video files to load.
initial_fill (int, optional, default = 1024) –
Size of the buffer that is used for shuffling.
random_shuffleis False, this parameter is ignored.
labels (int or list of int, optional) – Labels associated with the files listed in
filenamesargument. If not provided, no labels will be yielded.
lazy_init (bool, optional, default = False) – Parse and prepare the dataset metadata only during the first run instead of in the constructor.
num_shards (int, optional, default = 1) –
Partitions the data into the specified number of parts (shards).
This is typically used for multi-GPU or multi-node training.
pad_last_batch (bool, optional, default = False) –
If set to True, pads the shard by repeating the last sample.
If the number of batches differs across shards, this option can cause an entire batch of repeated samples to be added to the dataset.
prefetch_queue_depth (int, optional, default = 1) –
Specifies the number of batches to be prefetched by the internal Loader.
This value should be increased when the pipeline is CPU-stage bound, trading memory consumption for better interleaving with the Loader thread.
preserve (bool, optional, default = False) – Prevents the operator from being removed from the graph even if its outputs are not used.
random_shuffle (bool, optional, default = False) –
Determines whether to randomly shuffle data.
A prefetch buffer with a size equal to
initial_fillis used to read data sequentially, and then samples are selected randomly to form a batch.
read_ahead (bool, optional, default = False) –
Determines whether the accessed data should be read ahead.
For large files such as LMDB, RecordIO, or TFRecord, this argument slows down the first access but decreases the time of all of the following accesses.
seed (int, optional, default = -1) –
If not provided, it will be populated based on the global seed of the pipeline.
shard_id (int, optional, default = 0) – Index of the shard to read.
skip_cached_images (bool, optional, default = False) –
If set to True, the loading data will be skipped when the sample is in the decoder cache.
In this case, the output of the loader will be empty.
step (int, optional, default = -1) –
Frame interval between each sequence.
When the value is less than 0,
stepis set to
stick_to_shard (bool, optional, default = False) –
Determines whether the reader should stick to a data shard instead of going through the entire dataset.
If decoder caching is used, it significantly reduces the amount of data to be cached, but might affect accuracy of the training.
stride (int, optional, default = 1) – Distance between consecutive frames in the sequence.
tensor_init_bytes (int, optional, default = 1048576) – Hint for how much memory to allocate per image.