image-outpainting-output · Open Skill 公開技能
image-outpainting-output
image-outpainting-output 是 Digen 上的公開 Open Skill。開啟後即可了解此工作流能製作什麼。
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# Image Outpainting Output Skill ## Purpose Use this skill when the user wants to expand an existing image into a new aspect ratio, create multiple campaign formats from one source, or prepare outpainted assets for ads, social media, banners, stories, thumbnails, product pages, or other layouts. The core objective is **not merely to generate a larger canvas**. The objective is to produce an output that is: 1. Technically valid. 2. Visually coherent. 3. Faithful to the important subject/product. 4. Useful for the intended layout. 5. Ready for downstream design or export. Treat every outpaint as a new visual composition that requires review. --- # 1. OUTPUT-FIRST PRINCIPLE Always optimize for the final deliverable. Do not report: > "Outpainting completed." Report whether the resulting asset is actually usable. The output decision must answer four separate questions: ### A. Technical validity - Did generation succeed? - Is the image readable? - Is the requested aspect ratio correct? - Are the decoded dimensions correct or acceptable? - Is the requested output format correct? ### B. Subject / product fidelity - Is the main subject still the same? - Are important shapes preserved? - Are brand marks, labels, packaging, logos, facial identity, or defining details intact? - Did the model add duplicate products or objects? - Did the model unintentionally redraw the original subject? ### C. Scene continuity - Does the generated area continue the original scene naturally? - Are perspective lines continuous? - Is lighting direction consistent? - Are shadows, reflections, textures, patterns, and gradients plausible? - Are seams visible at delivery size? ### D. Layout usefulness - Is there usable negative space? - Is the subject positioned well for the destination? - Is there room for headline, CTA, logo, UI overlays, or campaign graphics? - Does the output still work after the planned text/design layer is placed? A technically correct image can still fail the task. --- # 2. INPUT CONTRACT Before processing, identify: - Source image. - Source dimensions. - Source orientation. - Intended destination aspect ratio(s). - Intended use: ad, story, banner, poster, thumbnail, catalog, etc. - Main protected subject. - Important details that must not change. - Preferred output format. - Planned text / logo / CTA area. - Any destination safe-area requirements. Keep an untouched source master. Normalize orientation before measuring width and height. Record the working source dimensions. When practical, record a source revision identifier or checksum so later outputs can be traced to the exact input. --- # 3. DECIDE: CROP, CANVAS, OR OUTPAINT Do not use outpainting automatically. Choose the smallest transformation that achieves the destination. ### Use a crop when: - The source already contains enough context. - Important content remains intact. - No generated scenery is needed. ### Use a designed canvas when: - A flat background, gradient, color block, or graphic panel can solve the composition. - Precise text placement matters more than photographic continuation. ### Use outpainting when: - The destination requires more surrounding scene. - Natural continuation of the environment is important. - Cropping would remove commercially or narratively important content. - Stretching would distort the subject. Do not use AI-generated pixels where ordinary layout can solve the problem more reliably. --- # 4. DESTINATION BRIEF For every output, create a small destination brief before generation. Use: ```text OUTPUT NAME: INTENDED USE: TARGET ASPECT RATIO: TARGET / EXPECTED DIMENSIONS: MAIN SUBJECT: PROTECTED DETAILS: DESIRED SUBJECT SCALE: DESIRED SUBJECT POSITION: TEXT / LOGO ZONE: UI / SAFE AREA: BACKGROUND CONTINUATION: ACCEPTABLE VARIATIONS: REJECTION RULES: OUTPUT FORMAT: ``` The brief must include explicit rejection rules. Example: ```text Reject if: - product logo changes - product count changes - mug handle disa