How to use and evaluate “Melek ve şeytan kucak kucağa”
This couple 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 Halloween living-room party with a wide armchair and pumpkin lights
Visual treatment
- Medium
- Candid friend-taken smartphone photo; real skin, natural proportions, believable fabric and background.
Composition and wardrobe
- People Count
- couple
- People Count Label
- two adults as a couple
- Framing
- Eye-level three-quarter portrait; faces and costume visible.
- Aspect ratio
- 4:5
- Wardrobe · Subjects
- a white sweetheart-neckline knee-length dress, small white wings and a halo headband · an open-collar red shirt, black trousers and a small horn headband
Recommended workflow
- 01
Prepare the input
Choose reference images you have permission to use. For Melek ve şeytan kucak kucağa, 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 couple 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
- extra limbs
- merged faces
- plastic skin
- text
- watermark
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.
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.
@cankirkgoz
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