Novel to Storyboard

The Challenge: Converting Text to Storyboard

In content creation for film or games, manually converting novels or screenplays into storyboard scripts is time-consuming and error-prone. Creators must analyze text sentence by sentence to identify visual details like shot types, camera movements, lighting, and color tones, while extracting character and scene features. This requires expertise in visual language and involves repetitive labor that can overlook key elements.

Core Capabilities and Workflow

This skill automates the process with the following core capabilities:

• Storyboard Generation: Automatically breaks down narratives and dialogues into structured shots, including fields like shot number, shot type (e.g., wide shot, close-up), content description, camera movement (e.g., push shot, tracking shot), lighting, color tone, and sound effects.
• Character Card Extraction: Extracts character name, appearance, personality, speaking lines, and generates AI drawing prompts from the text.
• Scene Card Generation: Identifies location type, time, atmosphere, color scheme, and infers visual styles for scenes.

The workflow proceeds as follows:

1. Input Handling: Supports direct text paste (for short content under 5000 characters) or uploading .txt/.md files. In file mode, command parameters like input specify the path, -o sets the output directory, and -f chooses the output format (markdown, json, or both).
2. AI Analysis: Uses keyword rules and AI models to automatically segment scenes (prioritizing headers like 第X场, INT., EXT.; defaulting to double line breaks if absent), recognize dialogues (relying on the Character: Dialogue format), and infer shot types (e.g., wide shots from environmental descriptions, close-ups from detail descriptions).
3. Output Generation: Produces complete storyboard scripts, character cards, and scene cards in Markdown or JSON formats, along with statistical summaries (e.g., total shots, scenes).

Applicability and Considerations

This skill is suitable for:

• Chinese script formats (e.g., Character: Dialogue) and English scripts (INT./EXT. format).
• Novel narrative formats, though structured text improves accuracy.

Key considerations include:

• Dialogue Recognition depends on standard formats; non-standard inputs may lead to missed dialogues.
• Scene Segmentation is based on headers or line breaks; complex structures might require manual adjustment.
• Feature Extraction is rule-based; complex or subtle descriptions may need AI supplementation.
• Long Text Processing is recommended in file mode to avoid dialogue limitations.