Description #

The image format conversion processor supports conversion between multiple input and output formats and allows adjustment of output quality.

Key features #

• Support for multiple image formats:
  • Input: URL address, Base64 encoding, binary stream
  • Output: PNG, JPEG/JPG, WebP
• Quality adjustment:
  • Supports adjusting the output quality of lossy compression formats (JPEG, WebP)
  • The quality range can be set from -1 to 100; -1 indicates using the default value
• Intelligent format processing:
  • Automatically handles transparency channels (JPEG does not support transparency channels)
  • Automatically handles color mode conversion (such as CMYK to RGB)
• Dual output modes:
  • Direct output as Base64 encoding
  • TOS/local persistent storage

Operator parameters #

Input #

Output #

An array of dictionaries containing processing results; each element includes:

• base64: Base64 encoding of the converted image;
• image_path: Local/TOS storage path (valid when the output directory is configured)

Parameters #

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

Examples #

The following code demonstrates how to use daft to run the operator for image format conversion.

from __future__ import annotations

import os

import daft
from daft import col
from daft.las.functions.image.image_format_convert import ImageFormatConvert
from daft.las.functions.udf import las_udf

if __name__ == "__main__":
    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)


    tos_dir_url = os.getenv("TOS_DIR_URL", "las-cn-beijing-public-online.tos-cn-beijing.volces.com")
    samples = {
        "image": [
            f"https://{tos_dir_url}/public/shared_image_dataset/cat_ip_adapter.jpeg"
        ],
        "image_name": ["cat_ip_adapter"],
    }

    output_format = "png"
    image_suffix = ""
    tos_dir = ""
    local_dir = ""
    image_src_type = "image_url"
    quality = -1
    num_gpus = 0

    ds = daft.from_pydict(samples)
    ds = ds.with_column(
        "image_format_convert",
        las_udf(
            ImageFormatConvert,
            construct_args={
                "output_format": output_format,
                "image_suffix": image_suffix,
                "tos_dir": tos_dir,
                "local_dir": local_dir,
                "image_src_type": image_src_type,
                "quality": quality,
            },
            num_gpus=num_gpus,
            batch_size=1,
        )(col("image"), col("image_name")),
    )

    ds.show()

    # ╭────────────────────────────────┬────────────────┬────────────────────────────────────────╮
    # │ image                          ┆ image_name     ┆ image_format_convert                   │
    # │ ---                            ┆ ---            ┆ ---                                    │
    # │ Utf8                           ┆ Utf8           ┆ Struct[base64: Utf8, image_path: Utf8] │
    # ╞════════════════════════════════╪════════════════╪════════════════════════════════════════╡
    # │ https://las-cn-beijing-public… ┆ cat_ip_adapter ┆ {base64: iVBORw0KGgoAAAANSUhE…         │
    # ╰────────────────────────────────┴────────────────┴────────────────────────────────────────╯