Sneaker care products vision model

What it covers

The product types the model is trained on. Anything outside this list is handled by a neighbouring model.

In scope

Shoe cleaners and shampoosProtector spraysSuede brushes and erasersSneaker wipesShoe trees and crease protectors

Not covered

The footwear itself such as sneakersBootsDress-shoesStandalone lacesLaundry detergents

What it reads

The model reads sneaker care products through a structured taxonomy. Below are its top-level feature families. Each one breaks down into detailed parts, attributes and possible values, and some of our taxonomies go beyond 200 labels. The full taxonomy is shared during a pilot.

01Container or tool form
02Cap and applicator
03Brush or cloth type
04Panel layout and labelling
05Material and finish
+Detailed parts, attributes and values within each family

Output format

Once live, the model returns the same record as every Klaimed model: the design similarity, a score for each feature, and the evidence image.

POST /v1/detect/sneaker-carePreview

{
  "model": "detect-sneaker-care",
  "listing": "site_a/8812-4410",
  "similarity": 0.94,
  "attributes": {
    "container_or_tool_form": 0.97,
    "cap_and_applicator": 0.86,
    "brush_or_cloth_type": 0.87,
    "panel_layout_and_labelling": 0.88,
    "material_and_finish": 0.41
  },
  "evidence": "ev_9f3a.png"
}

How teams use it

IP firmsMonitor sneaker care products copies for your clients, under your brand Design search firmsSearch sneaker care products designs across brand websites and registries Brand-protection platformsAdd sneaker care products recognition to your pipeline by API

Capabilities

Fine-grained attribute understanding: Reads sneaker care products the way a category expert would: overall shape and proportion, the geometry of each component, material and surface character, and the specific construction features that define one design against another.
Design-level similarity retrieval: Given a reference product, returns the closest matches from a monitored set, ranked by design similarity rather than by colour, scene or filename.
Feature-by-feature match explanation: Every match comes with its reasoning: which features agree between the reference and the candidate, which diverge, and how confident each comparison is.
Stable across how the product was photographed: The same design retrieves consistently whether it was shot as a studio packshot, a seller's phone photo or an in-use image, and holds up under changes of angle, lighting, background and partial occlusion.

Questions

Can the sneaker care products model find counterfeits without a logo or brand name?

Yes. It reads sneaker care products by design, through features such as container or tool form, cap and applicator and brush or cloth type. A listing with no logo, no brand name and a different photo still matches its reference when the design is the same.

Which product types does the sneaker care products model cover?

In scope: Shoe cleaners and shampoos, Protector sprays, Suede brushes and erasers, Sneaker wipes and Shoe trees and crease protectors. Not covered: The footwear itself such as sneakers, Boots, Dress-shoes, Standalone laces and Laundry detergents.

When will it be available?

It is in development. Early-access partners help shape the model on their own products. Tell us the product type and your volume and we'll share the timeline.

What images does it accept?

Studio packshots, seller phone photos and in-use images. Results stay consistent across angle, lighting, background and partial occlusion.

Is the attribute taxonomy public?

No. The taxonomy and training data are proprietary. We walk you through it during a pilot, and can add features and retrain the model on request.

How do I access it?

Request early access. Once it is live, it runs through the same Klaimed API and interface as every other model.