Operator ID: daft.las.functions.image.image_compress.ImageCompress

Description #

Image compression processor that supports multiple interpolation algorithms and various input and output formats.

Key features #

• Input formats:
  • URL address (image_url)
  • Base64 encoding (image_base64)
  • Binary stream (image_binary)
• Compression and scaling:
  • Quality compression (quality parameter)
  • Size scaling (target_size or keep original size)
  • Multiple interpolation algorithms: nearest / bilinear / bicubic / lanczos
• Output modes:
  • Returns the Base64-encoded string of the compressed image
  • Optionally save the image to TOS
  • Optionally save the image to a local directory
• Format adaptation:
  • JPEG: quality compression + RGBA to RGB conversion
  • PNG: lossless compression (compress_level) + preserve alpha channel
  • WebP: quality/lossless compression + preserve alpha channel

Operator parameters #

Input #

Output #

An array of dictionaries containing processing results. Each element includes:

• base64: Base64-encoded string of the compressed image;
• image_path: Local/TOS storage path (valid when 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 compression.

from __future__ import annotations

import os

import daft
from daft import col
from daft.las.functions.image.image_compress import ImageCompress
from daft.las.functions.udf import las_udf

if __name__ == "__main__":
    # Content will be saved to the specified TOS path. Therefore, environment variables must be set to ensure write permissions 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}/image/image_compress"

    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.png"],
        "image_name": ["cat_ip_adapter"],
    }
    image_suffix = ".jpg"
    image_src_type = "image_url"
    target_size = [200, 200]
    quality = 85
    method = "lanczos"
    local_dir = ""
    ds = daft.from_pydict(samples)
    ds = ds.with_column(
        "image_compress",
        las_udf(
            ImageCompress,
            construct_args={
                "image_suffix": image_suffix,
                "output_dir": output_tos_dir,
                "image_src_type": image_src_type,
                "target_size": target_size,
                "quality": quality,
                "method": method,
            },
            batch_size=1,
        )(col("image"), col("image_name")),
    )
    ds.show()
# ╭────────────────────────────────┬────────────────┬────────────────────────────────────────────╮
# │ image                          ┆ image_name     ┆ image_compress                             │
# │ ---                            ┆ ---            ┆ ---                                        │
# │ String                         ┆ String         ┆ Struct[base64: String, image_path: String] │
# ╞════════════════════════════════╪════════════════╪════════════════════════════════════════════╡
# │ https://las-ai-qa-online.tos-… ┆ cat_ip_adapter ┆ {base64: /9j/4AAQSkZJRgABAQAA…             │
# ╰────────────────────────────────┴────────────────┴────────────────────────────────────────────╯