Lunar New Year Photo AI From Your Own Photos
The reunion dinner is the one meal of the year everybody tries to be at and the one photograph that is hardest to take, because the table is full, the food is arriving and somebody is always in the kitchen. The Image Editor at /dashboard/images/edit/ builds the picture from photos you already have: upload the people, describe the scene, and the faces in the result come from your uploads rather than from a written description of a family.
Lunar New Year suits this particularly well because the visual language is unambiguous. Red and gold, lanterns, blossom branches, mandarins, a round table with dishes at the centre — a description of two or three of those reads instantly and unmistakably as the festival. What has to be real is who is at the table, and that is the part you supply as photographs.
What this tool does
- Lunar New Year photos are assembled on the Image Editor tab at /dashboard/images/edit/, which takes uploaded photos as references rather than generating people from a written description.
- The faces in the result come from the photos you upload, not from the text description of the scene.
- Several reference images can be used in one edit and are addressed by position in the instruction — "image 1", "image 2" — because upload order is the order the model reads them in.
- Reference-image limits depend on the model: 20 on Grok Imagine Pro, 14 on Nano Banana 2 and Seedream 5 Lite, 10 on Kling IMAGE O1 and GPT Image 2, 9 on WAN 2.7 and 4 on FLUX.2 [dev].
- Identity-preserving edit models such as Nano Banana Edit and Seedream 4.5 Edit are the ones built for keeping a face recognisable, and naming the constraint explicitly in the instruction reduces drift.
- New accounts start with free signup credits, one-time credit packs never expire, and subscriptions are also available for a monthly allowance.
The picture the reunion dinner never produces
Every large family has an almost-photograph: the table set and full, everyone momentarily in the same room, and nobody holding the camera because everyone is holding something else. Ten minutes later the plates are half empty and two people are on their phones. The window in which that picture could be taken is roughly the length of the first toast.
Assembling the image removes the window. Each person comes from a photo taken whenever it was taken, and the table, the lanterns and the light come from the description. The honest caveat is that a picture built from six different photos will not carry a single moment's light across every face — it reads as a family portrait rather than as a photograph of that dinner, which for a card or a framed print is usually exactly what was wanted.
Composing a group that was never in one place
Group edits succeed or fail on two decisions. The first is consistency of source: people photographed from roughly the same angle and distance combine into something believable, while a mix of a close-up and a wide shot produces a frame that looks assembled even when every face is right. The second is scale — decide how much of each person the picture shows and keep it uniform.
When someone drifts, change their source photo rather than the instruction. A tighter, better-lit picture of the person who came out wrong fixes more than any amount of rewriting, and rewriting risks the faces that were already correct. Save the version you like before you experiment, so you always have a good image to fall back to.
How it works
1.Collect one photo per person
Front-facing and evenly lit, face clearly visible. Ask for a fresh photo if the only one you have is years old — not because old photos do not work, but because people change, and the point of the picture is that it looks like the family as it is.
2.Upload them together
Open /dashboard/images/edit/ and add every photo in the same run so the instruction can address them by position. Upload order is the order the model reads them in, so keeping a consistent order makes the instruction far easier to write and adjust.
3.Describe the table, then lock the faces
One sentence for the scene — a round table with dishes at the centre, red and gold, lanterns above, blossom branches, the people from the uploads seated together — and one sentence for the constraint: keep each face, hair and identity exactly as in the source photos. Never skip the constraint.
4.Check every face, then the table
Look at each person individually before judging the picture as a whole. Then check the details that give an assembled image away: hands, chopsticks, the pattern on a plate, any Chinese characters in the frame. Characters are the riskiest element to ask for, so keep text out of the scene where you can.
Frequently asked questions
How do I make a Lunar New Year family photo from separate pictures?
Upload one photo per person to the Image Editor at /dashboard/images/edit/ and describe the scene you want, addressing the uploads by position. The faces come from your photos, so the result is your family rather than a generated one. It answers the reunion-dinner problem, where everyone is at the table but nobody is behind the camera.
Can I make the picture look like a reunion dinner?
Yes, and the description is what does it: a round table with dishes at the centre, red and gold, lanterns above, mandarins and blossom branches, the people from the uploads seated together. Two or three of those elements are enough — asking for the whole visual vocabulary at once produces a busy frame rather than a specific one.
Should I include Chinese characters or a greeting on the image?
Text is the least reliable element in any generated image, and characters from a writing system the model has seen less of are the riskiest of all. If the picture needs words, keep them out of the generated image and add them as a caption or in a separate text layer. It is one of the few places where doing it by hand is genuinely faster than generating it.
Will the people in the photo be recognisable?
The faces come from your uploads, and identity-preserving edit models such as Nano Banana Edit and Seedream 4.5 Edit are the ones built for that. Adding "keep the face, hair and identity exactly as in the original" reduces drift measurably. A family picture is unforgiving here — one wrong face spoils the whole image — so check each person at full size before you save it.
How many people can I put in one picture?
It depends on the model you choose: up to 20 reference images on Grok Imagine Pro, 14 on Nano Banana 2 and Seedream 5 Lite, 10 on Kling IMAGE O1 and GPT Image 2, 9 on WAN 2.7 and 4 on FLUX.2 [dev]. For a large extended family, build it in two passes — assemble several people, then add the next group to a version that already works.
Can I make a moving version instead of a still?
Yes. The video side of the site takes one photo and generates a short clip from it, with the scene coming from your description. For a New Year greeting that is often the better format, since it can be sent to a family group and watched on a phone without anyone opening a link. The still is usually made first and animated afterwards.
Do I need a subscription to make one photo?
No. The tools run on credits rather than a plan, and new accounts start with free signup credits, so a single New Year picture does not require subscribing to anything. One-time credit packs never expire, which fits an image or two a year; subscriptions exist for people using the tools regularly.
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Make a Lunar New Year photo