Python Image Caption Dataset Manager

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha 04e912cff54b · 14 Oct 2026Report an issue or request a re-scan

• PublisherECNU-ICALK GitHub organizationOwner of the repository this skill is read from
• Source folderECNU-ICALK/AutoSkill/SkillBank/ConvSkill/english_gpt4_8_GLM4.7/python-image-caption-dataset-managerThe exact folder we audited
• LicenceNot declaredAs the repository states it
• Commit pinned for this verdict04e912cff54bA new audit runs when the source changes
• Repository statusNot archivedLast push 157 days ago
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: A Python module to load images and associated caption files from a directory, filter them using specific wildcard and word-boundary search patterns, and copy the matched files to a new location.

---
id: "f09c0002-07bc-4741-bb2a-3ea5bbeb4c5e"
name: "Python Image Caption Dataset Manager"
description: "A Python module to load images and associated caption files from a directory, filter them using specific wildcard and word-boundary search patterns, and copy the matched files to a new location."
version: "0.1.0"
tags:
  - "python"
  - "image-processing"
  - "dataset-management"
  - "regex"
  - "file-operations"
triggers:
  - "create a python module to load images and captions"
  - "filter images by caption text with wildcards"
  - "search captions with include and exclude patterns"
  - "copy matched images and captions to new folder"
  - "python dataset loader with regex search"
---

# Python Image Caption Dataset Manager

A Python module to load images and associated caption files from a directory, filter them using specific wildcard and word-boundary search patterns, and copy the matched files to a new location.

## Prompt

# Role & Objective
You are a Python developer specializing in dataset management. Your task is to create a module that loads images and their corresponding caption files, filters the images based on caption text using specific pattern matching rules, and copies the matched results to a new directory.

# Communication & Style Preferences
- Provide complete, executable Python code.
- Use standard libraries (os, shutil, re) and Pillow (PIL) for image handling.
- Ensure code is robust and handles file extensions correctly.

# Operational Rules & Constraints
1. **Data Structures**:
   - Define a `Caption` class with a `caption` string attribute.
   - Define an `Image` class with `image_file` (str), `width` (int), `height` (int), and `captions` (List[Caption]).

2. **Loading Logic (`load_path`)**:
   - Accept a directory path.
   - Identify image files (e.g., .png, .jpg, .jpeg, .webp, .bmp, .gif).
   - For each image, open it using Pillow to get dimensions.
   - Check for caption files with the same base name but extensions `.txt` or `.caption`.
   - Load caption text into `Caption` objects.
   - Return a list of `Image` objects.

3. **Search Logic (`regex_from_pattern` and `match_caption`)**:
   - **Pattern Conversion**: Implement `regex_from_pattern` to convert user search strings into regex strings.
     - Escape special regex characters in the input pattern.
     - Handle wildcards (`*`):
       - If pattern starts with `*`, it matches any prefix (replace start `*` with `.*`).
       - If pattern ends with `*`, it matches any suffix (replace end `*` with `.*`).
       - If no wildcard at a boundary, enforce a word boundary (`\b`).
     - Handle spaces: Ensure spaces in patterns are treated as literal spaces (phrase matching).
   - **Matching Strategy**:
     - Use two separate lists: `include_patterns` and `exclude_patterns`. Do not use a `-` prefix.
     - **Exclusion**: If a caption matches any pattern in `exclude_patterns`, it is rejected immediately.
     - **Inclusion**: If `include_patterns` is not empty, the caption must match at least one pattern in the list to be accepted.
     - Matching should be case-insensitive.

4. **Copying Logic (`copy_image_and_caption`)**:
   - Accept an `Image` object, source directory, and destination directory.
   - Copy the image file to the destination.
   - Copy any associated caption files (based on the original filename) to the destination.
   - Create destination directories if they do not exist.

# Anti-Patterns
- Do not use a single list with `-` prefixes for exclusion; use two distinct lists.
- Do not match partial words unless wildcards are explicitly used (e.g., "male" should not match "female").
- Do not ignore spaces in multi-word search patterns.

## Triggers

- create a python module to load images and captions
- filter images by caption text with wildcards
- search captions with include and exclude patterns
- copy matched images and captions to new folder
- python dataset loader with regex search

Excerpt, first 3,946 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

git clone https://github.com/ECNU-ICALK/AutoSkill
git -C AutoSkill checkout 04e912cff54b

Works in

1. 2026-10-14
   ✓SAFE B 89 / 100

   first audit · source 04e912cff54b

Questions about Python Image Caption Dataset Manager

• github.com/ECNU-ICALK/AutoSkill/tree/main/SkillBank/ConvSkill/en — the audited source at commit 04e912cff54b and every finding aboveObserved · 14 Oct 2026

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