# Python Image Dataset Loader and Caption Filter

> Python Image Dataset Loader and Caption Filter is an Agent Skill for documents published in the ECNU-ICALK/AutoSkill repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.

A Python module to load images and associated caption files from a directory, filter images based on caption text patterns with wildcards and exclusion rules, and copy the matched files to a new location.

- Skill name: `Python Image Dataset Loader and Caption Filter`
- Category: [Documents](https://www.openparable.com/skill/documents/1)
- Source: https://github.com/ECNU-ICALK/AutoSkill/blob/HEAD/SkillBank/ConvSkill/english_gpt4_8/python-image-dataset-loader-and-caption-filter/SKILL.md
- Repository: ECNU-ICALK/AutoSkill (518 GitHub stars when collected)

## SKILL.md

# Python Image Dataset Loader and Caption Filter

A Python module to load images and associated caption files from a directory, filter images based on caption text patterns with wildcards and exclusion rules, and copy the matched files to a new location.

## Prompt

# Role & Objective
You are a Python developer tasked with creating a dataset management module. The goal is to load images and their associated captions from a file system, filter the images based on specific caption text matching rules, and copy the 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 existence checks.

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

2. **Image Loading (`load_path`)**:
   - Accept a directory path.
   - Iterate through files to find images (support common extensions like .png, .jpg, .jpeg, .webp).
   - Use Pillow to open images and extract `width` and `height`.
   - For each image, check for caption files with the same base name but extensions `.txt` or `.caption`. Load the text content into `Caption` objects.
   - Return a list of `Image` objects.

3. **Caption Search Logic**:
   - Use two separate lists for filtering: `include_patterns` and `exclude_patterns`. Do NOT use a prefix (like '-') to denote exclusion; the list separation handles that.
   - Implement `regex_from_pattern(pattern)` to convert user search strings into valid regex strings:
     - Escape special regex characters.
     - Treat `*` as a wildcard matching any sequence of characters (equivalent to `.*` in regex).
     - If the pattern does not start with `*`, prepend a word boundary (`\b`).
     - If the pattern does not end with `*`, append a word boundary (`\b`).
     - Handle spaces within patterns to allow phrase matching (e.g., "comic book character").
   - Implement `match_caption(caption, include_patterns, exclude_patterns)`:
     - Perform case-insensitive matching.
     - If the caption matches any pattern in `exclude_patterns`, return `False` immediately.
     - If `include_patterns` is not empty, the caption must match at least one pattern in `include_patterns` to return `True`.
     - If `include_patterns` is empty and no exclude patterns matched, return `True`.

4. **File Copying**:
   - Implement a function to copy matched `Image` objects and their associated caption files to a specified destination directory.
   - Create the destination directory if it does not exist.
   - Maintain original filenames.

# Anti-Patterns
- Do not use a `-` prefix for exclusion patterns.
- Do not match substrings unless wildcards are explicitly used (respect word boundaries).
- Do not assume case sensitivity; matching should be case-insensitive.

## Triggers

- load images and captions from path
- filter images by caption text patterns
- search captions with wildcards and exclude lists
- copy matched images and captions to new folder
- python dataset image loader

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