Preparing Two Photos for Cat Clapping: Inputs, Costs and Result Checks

A cat clapping clip starts with three inputs: a person photograph, a cat photograph and a fixed motion reference. On Catclapping.net, you supply the two photographs. The workspace supplies the reference and requests a silent, 10-second vertical video. This guide explains the decisions you can actually control, and what to inspect after generation.

These are instructions for the current product, not the results of a comparative model benchmark. A completed task does not guarantee a perfect likeness or natural paw movement.

Choose photos for the parts that will move

The person and cat are separate inputs. Do not combine them into a collage before uploading. Use JPEG, PNG or WebP files, with each file no larger than 10 MB.

For the person, look at the photograph at thumbnail size. Can you still distinguish the eyes and mouth? A face that becomes a dark patch when reduced is a poor appearance reference. Try a sharper image with even light. Remove sunglasses and choose an unobstructed face rather than relying on the model to reconstruct hidden features.

For the cat, inspect the front legs and paws as carefully as the face. A tight headshot gives the model little information about the anatomy involved in a clap. Choose a single cat with space around its body. If the cat is dark, a background with a similar tone can obscure its outline; choose a different photograph instead of applying a heavy filter.

You can review a manual photo checklist on the homepage. It records your own checks; it does not perform automated face detection or predict a quality score.

Understand the fixed reference

The template comes from the original cat clapping Reel. It guides the sequence of actions and camera changes. The uploaded photographs guide appearance. You cannot replace that reference or write a different scene prompt through the public workspace.

The reference shown on the page is an input, not proof of what the service will generate for your photographs. The illustrated input pair also has no public result attached yet. Do not use that empty sample area to judge output quality.

Budget attempts before buying a pack

The credit charge depends on the active Seedance model and output quality. Review the current amount in the generator before submitting. Resolution changes the requested output size. It is not a promise that the higher setting will reproduce a face more accurately or fix an obscured paw.

Multiply the displayed credit charge by the number of attempts you plan to make. The pricing comparison shows the video count and remaining balance for each pack at the currently configured model. These are credit calculations, not predictions of how many attempts you will need.

Use the session estimator and credit packs before purchasing. Packs are one-time purchases with a 365-day credit validity period. Each new generation is another paid attempt, including a retry after a completed result you did not like.

Work from submission to preview

1. Open the generation workspace and sign in.
2. Select a person file and a cat file. Inspect the two previews before continuing.
3. Choose the output quality and confirm that you have permission to use the inputs.
4. Submit once, then follow the task status in the preview panel. Processing time varies with the provider queue.
5. When the MP4 is ready, play it all the way through and pause on the frames that matter.

You can return through Generation history using the same account. A waiting task is not a reason to submit a second copy: that second request may become a separate paid generation.

Review the result as a moving sequence

A single attractive frame can hide problems elsewhere in the clip. Check these points before downloading a version to publish:

| Check | What to inspect | What you can try on a later attempt | | --------------- | -------------------------------------------------------------- | ------------------------------------------------------- | | Person identity | Facial features across close-ups, not just the opening frame | A sharper portrait with fewer obstructions | | Cat identity | Coat pattern, face shape and silhouette through camera changes | A clearer cat image with a distinct outline | | Paw movement | Fused paws, extra limbs, or shapes changing during the clap | An input with both front paws and space around the legs | | Framing | Ears or paws disappearing beyond the vertical frame | A less tightly cropped source image |

These are troubleshooting suggestions, not guaranteed fixes. Repeating the exact same input can still produce a different result; it can also repeat the same defect.

Separate a task failure from a visual imperfection

A task marked failed restores its generation credits automatically. This is a return of credits to the account, not a cash refund. A task that completes with an awkward expression or distorted paw is not automatically classified as failed. See the service terms for the applicable conditions.

If the task list does not load, use its retry button or return to Generation history before submitting again. A page loading error alone does not tell you whether the provider finished the job.

Publish with the right expectations

The output is a silent MP4 in a vertical 9:16 format. Audio present in a reference clip is not included in the generated file. Add music or sound you have permission to use in your publishing app.

Confirm permission to use recognizable people and the source images. Do not present the generated scene as a real event, and follow the destination platform’s AI disclosure requirements. The privacy policy describes how uploaded photos and generated media are handled.