How to use and evaluate “Group project coffee break”
This portrait prompt is designed as an editable starting point, not a guaranteed one-click result. The notes below translate its JSON into a readable visual plan, identify the controls that matter, and show how to diagnose a weak generation without simply adding more text.
Prompt-specific blueprint
Scene and atmosphere
- Location
- A small outdoor study table beside the Orta Bahce lawn at Yildiz Technical University Davutpasa campus, actual long two-storey stone Kisla building with red tiled roof and arched windows visible as in the campus reference; three adult design students with paper layouts, a laptop and coffee
- Location Reference
- https://yildiz.edu.tr/sites/default/files/styles/galeri_850x450/public/2022-02/ytu-davutpasa-kampusu-3_0_0.jpg?h=539524f1&itok=i8SPv-1O
- Location Reference Usage
- If an attached location photo is available, preserve its actual YTU campus architecture; use it for the place only, not the person or photographic style.
Visual treatment
- Medium
- Everyday Turkish student's unretouched phone photo. Natural skin, clothes, color and shadows; ordinary phone exposure, subtle grain in low light. No editorial polish.
Composition and wardrobe
- People Count
- three
- People Count Label
- three distinct adults
- Framing
- fourth classmate takes a deliberate wide rear-phone group portrait of three students beside outdoor table, everyone aware and ready, papers resting on table and real Kisla facade behind
- Aspect ratio
- 4:5
- Wardrobe · Description
- main person in muted red open cardigan over a fitted white cropped tank; classmates casual blue and gray shirts
Recommended workflow
- 01
Prepare the input
Choose reference images you have permission to use. For Group project coffee break, prioritize a clear subject and avoid unrelated people or private details in the frame.
- 02
Lock the visual plan
Confirm subject count, framing, scene, and lighting before adding finishing language. Resolve conflicts such as close-up versus full-body composition.
- 03
Adapt for one model
Start with ChatGPT Image. Keep a baseline generation and document the exact model version, references, aspect ratio, and visible settings.
- 04
Revise from evidence
Name the visible failure, change one instruction block, and compare it against the baseline. Keep only revisions that improve the intended criterion.
Model adaptation notes
ChatGPT Image
Keep the JSON structure, attach references in the same conversation, and use follow-up edits for one local correction at a time.
A compatibility label means the visual intent can be adapted; it does not promise identical output across providers, versions, or settings.
Prompt-specific quality checklist
- The output preserves the intended portrait subject and scene.
- Lighting direction, camera framing, and environmental details agree.
- The result can be compared against the prompt’s stated purpose.
Failures to check before publishing
- pasted face
- oversized head
- twisted neck
- head rotated 90 degrees
- plastic skin
- beauty filter
- CGI
Why the editable controls matter
Gender
Changes Prompt.Identity.Gender without requiring a full prompt rewrite.
People count
Changes Prompt.Composition.People Count Label without requiring a full prompt rewrite.
Photo format
Changes Prompt.Composition.Aspect Ratio without requiring a full prompt rewrite.
Identity or subject drift
Reduce competing style language, improve the reference, and separate stable traits from pose, gaze, and expression.
Composition breaks
Check whether crop, shot distance, aspect ratio, subject count, and required objects can all be satisfied in one frame.
Artificial lighting or texture
Name a motivated light source and believable material behavior before adding grain, grading, sharpness, or resolution terms.







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