Building a privacy-first PNG checker for Tesla digital wraps

A convincing car render and a usable digital wrap are different deliverables. One is a picture of a vehicle; the other is a flat texture that must map onto particular body panels.

While building Tesla Wrap AI, that distinction became one of the most useful constraints in the workflow. This post explains a small browser-based companion tool: a local PNG preflight check, plus a prompt builder that makes panel placement explicit.

Disclosure: I build Tesla Wrap AI. The companion tools are free; AI generation on the main website uses credits. This article was prepared with AI assistance and checked against the companion implementation.

Start with the actual deliverable

Digital Paint Shop wraps change a vehicle visualization, not the physical paint or vinyl. A preview screenshot cannot substitute for the underlying wrap PNG.

A sensible workflow has three separate checks:

1. File checks: can the browser decode the image, and does the file satisfy basic format constraints?
2. Template checks: does the image use the correct UV layout for the exact vehicle generation and variant?
3. Visual checks: are the hood motif, door graphics and lettering where the designer intended?

Passing the first check says nothing definitive about the other two. Two square images can have identical dimensions and completely different panel maps.

Read the signature, not just the extension

An input with accept="image/png" helps people choose a file. It does not prove that the selected bytes represent a PNG. The companion checks the eight-byte PNG signature before attempting to decode the image:

async function hasPngSignature(file) {
  const bytes = new Uint8Array(
    await file.slice(0, 8).arrayBuffer()
  );
  const signature = [137, 80, 78, 71, 13, 10, 26, 10];
  return signature.every((value, index) => bytes[index] === value);
}

This is a format preflight, not a comprehensive security validator. A matching signature does not establish that every chunk is valid. The browser still needs to decode the file, and a server receiving uploads needs its own validation.

The checker also reports dimensions, file size and the filename separately. That makes a failure actionable: “dimensions do not match” is more helpful than a single unexplained “invalid file.” The current constraints are linked to Tesla's published custom-wrap requirements, rather than treated as permanent assumptions.

Keep the image local

For this task, a server upload adds no value. A File object already exposes the file size and lets JavaScript read a small byte range. An object URL lets the browser decode and preview the selected image without sending its contents anywhere.

There are two easy lifecycle mistakes:

• Leaking object URLs: revoke the previous URL when replacing or removing a file.
• Displaying stale results: if someone chooses a second image while the first is decoding, the first callback can arrive late. Use a monotonically increasing selection counter and ignore callbacks from earlier selections.

The companion limits local decoding to a bounded file size, clears old validation rows when a new selection starts, and provides a visible remove action. It does not read the image's metadata to infer a vehicle model; that would create false confidence.

Give generation the right constraints

The prompt builder is deliberately simple. It combines the selected vehicle version, a visual direction and symmetry preference with a few layout instructions:

Center the hood motif. Keep key artwork within panels, clear of seams; simplify small panels. Preserve the UV layout and canvas proportions.

It also asks for requested lettering to remain readable and never mirrored. These instructions are a starting point, not a guarantee. The real generation workflow still needs the correct template and visual inspection afterward. A text prompt alone cannot establish UV compatibility.

The generated prompt stays within the main editor's input limit. The Space does not run an image-generation model or silently consume credits; it links to the matching editor and asks the user to paste the prompt into the AI panel.

Try the companion

The Hugging Face Space contains the prompt builder and local PNG checker, with its static implementation visible in the Files tab. No personal image needs to leave the browser to run the checker.

For the full workflow, the digital-wrap gallery offers designs to inspect before opening a copy in the editor. Choose the exact model, inspect the flat texture and available 3D preview, then save the actual PNG.

The broader lesson applies beyond cars: validate the file, validate its coordinate system, and validate the rendered result as separate steps. Which part of that workflow would you want to automate next?