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name: image-processing description: "Choose and debug img2dataset resizing, encoding, filtering, and bounding-box blurring." disable-model-invocation: true metadata: disco-role: operating license: MIT

Image Processing

Use this sub-skill when the task is about how img2dataset changes image geometry or pixels, especially Resizer and BoundingBoxBlurrer.

Route here for

• Choosing a resize mode and predicting the output dimensions: no, border, keep_ratio, keep_ratio_largest, center_crop.
• Picking interpolation strings, codec settings, and blur behavior.
• Explaining skip_reencode, disable_all_reencoding, alpha matting, and validation filters.
• Debugging bbox blur input from bbox_col or direct BoundingBoxBlurrer usage.

Do not handle here

• Input tables, column mapping, metadata layout, or writer/file format choices: route to input-output-formats.
• URL downloading, retries, hashing, SSL, incremental runs, and command orchestration: route to core-download.
• Multiprocessing, PySpark, Ray, W&B, shard sizing, or throughput tuning: route to distributed-execution.

Operating workflow

1. Check image options for the exact mode, codec, and filter semantics.
2. Use troubleshooting to map errors to the relevant resize, encode, or bbox cause.
3. If you need a quick repro, run scripts/probe_resize_options.py on a tiny synthetic image.
4. For bbox blur cases, confirm the coordinates are normalized [x_min, y_min, x_max, y_max] values in [0, 1] and that the final dimensions still come from the chosen resize mode.

Bundled helper

• scripts/probe_resize_options.py: synthetic resize/encode/filter/bbox probe with optional JSON output.

Start with image options and troubleshooting when the user asks why a sample changed shape, codec, or blur coverage.