Description #

Video keyframe segmentation processor, supports intelligent segment splitting.

Key features #

• Multi-algorithm keyframe detection:
  • I_frame: Detection based on I-frame (recommended)
  • difference: Pixel difference detection
  • histogram: Histogram difference detection
• Supports segment binary output or TOS storage
• Provides timestamp positioning functionality

Format support #

• MP4 (.mp4)
• AVI (.avi)
• MOV (.mov)
• MKV (.mkv)
• Other common video formats

Operator parameters #

Input #

Output #

The processed struct fields include:

• segments: list[str], list of paths to video segments after splitting
• segments_binary: list[bytes], list of binary data for video segments after splitting
• video_format: list[str], list of formats for video segments after splitting

Parameters #

If a parameter does not have a default value, it is required

Examples #

The following code demonstrates how to use Daft (for distributed scenarios) to run the operator to split videos by keyframe.

from __future__ import annotations

import os

import daft
from daft import col
from daft.las.functions.udf import las_udf
from daft.las.functions.video import VideoSplitByKeyframes

if __name__ == "__main__":

    # After modification, the split videos will be saved to the specified TOS path. Therefore, you need to set environment variables to ensure write access to TOS, including: ACCESS_KEY, SECRET_KEY, TOS_ENDPOINT, TOS_REGION, TOS_TEST_DIR
    TOS_DIR = os.getenv("TOS_TEST_DIR", "tos_bucket")
    output_tos_dir = f"tos://{TOS_DIR}/video/video_split_by_keyframes"
    
    if os.getenv("DAFT_RUNNER", "native") == "ray":
        import logging

        import ray

        def configure_logging():
            logging.basicConfig(
                level=logging.INFO,
                format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
                datefmt="%Y-%m-%d %H:%M:%S.%s".format(),
            )
            logging.getLogger("tracing.span").setLevel(logging.WARNING)
            logging.getLogger("daft_io.stats").setLevel(logging.WARNING)
            logging.getLogger("DaftStatisticsManager").setLevel(logging.WARNING)
            logging.getLogger("DaftFlotillaScheduler").setLevel(logging.WARNING)
            logging.getLogger("DaftFlotillaDispatcher").setLevel(logging.WARNING)

        ray.init(dashboard_host="0.0.0.0", runtime_env={"worker_process_setup_hook": configure_logging})
        daft.set_runner_ray()
    daft.set_execution_config(actor_udf_ready_timeout=600)
    daft.set_execution_config(min_cpu_per_task=0)

    # Construct the URL using environment variables
    tos_dir_url = os.getenv("TOS_DIR_URL", "las-cn-beijing-public-online.tos-cn-beijing.volces.com")
    samples = {
        "video_path": [
            f"https://{tos_dir_url}/public/shared_video_dataset/sample.mp4"
        ]
    }

    ds = daft.from_pydict(samples)

    splitter = las_udf(
        VideoSplitByKeyframes,
        construct_args={
            "method": "I_frame",
            "keyframes_cnt": 2,
            "output_tos_dir": output_tos_dir,
        },
    )

    # Use Daft for distributed processing
    ds = ds.with_column("results", splitter(col("video_path")))

    ds.show()
    # ╭──────────────────────────────────────────┬──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
    # │ video_path                               ┆ results                                                                                                                          │
    # │ ---                                      ┆ ---                                                                                                                              │
    # │ Utf8                                     ┆ Struct[segments: List[Utf8], segments_binary: List[Binary], video_format: List[Utf8]]                                            │
    # ╞══════════════════════════════════════════╪══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╡
    # │ https://las-cn-beijing-publi-…           ┆ {segments: ["tos://tos_bucket/video/video_split_by_keyframes/sample/segment_1.mp4", "tos://tos_bucket/video/video_split_by_keyf… │
    # ╰──────────────────────────────────────────┴──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯