Four seasons, one place

Start with the right photo.

One landscape with recognizable landmarks and vegetation suitable for four seasonal panels.

What to expect

Create one clean two-by-two contact sheet showing the exact same scene and camera in spring, summer, autumn and winter, in that reading order.

Keep an eye on

Weather and lighting are fictional reconstructions. Check landmark consistency and reflection direction; no factual weather claim.

Make it yours, step by step.

1. Adjust the recipe to describe your subject and preferred background.
2. Copy the complete recipe, then open ChatGPT.
3. Upload your photo in ChatGPT and paste the recipe. The short code alone is not an official command.
4. Inspect identity, text and proportions. Ask for a targeted correction if needed.

Choose the change deliberately.

Use stable landmarks to connect the panels: horizon, tree positions and major building forms. Seasonal changes can alter vegetation and ground coverage without requiring a new composition each time.

Review and refine the result

Compare the panels for missing landmarks and inconsistent framing. If the scenes drift, narrow each season's changes before adding decorative details. This is a concept comparison, not a time-lapse record.

A related direction, and why

/CONTACTSHEET — A contact sheet supports other kinds of controlled visual variation without implying a seasonal sequence.

These are editing suggestions, not additional test observations. Read the practical guide or use the before/after checklist.

Where this effect helps — and its limits.

Create one clean two-by-two contact sheet showing the exact same scene and camera in spring, summer, autumn and winter, in that reading order. Weather and lighting are fictional reconstructions. Check landmark consistency and reflection direction; no factual weather claim.

Input advice and use cases are editorial guidance, not additional test results.

Notes from recorded tests.

These notes describe the named runs, which may use a different subject from the comparison above. They do not guarantee results on another input or a future model. See our testing method.