Vector image search

curl --request POST \
  --url https://api.managem.co.uk/search/vector \
  --header 'Content-Type: application/json' \
  --data '
{
  "limit": 3,
  "vectors": [
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  ]
}
'

{
  "count": 2,
  "matches": [
    {
      "score": 0.9987,
      "urn": "urn:managem:pokemon:set/151/card/25",
      "game": "Pokemon",
      "title": "151: Pikachu",
      "number": "25",
      "image": "https://images.managem.co.uk/urn:managem:pokemon:set/151/card/25/image/0"
    },
    {
      "score": 0.9921,
      "urn": "urn:managem:pokemon:set/base-set/card/58",
      "game": "Pokemon",
      "title": "Base Set: Pikachu",
      "number": "58",
      "image": "https://images.managem.co.uk/urn:managem:pokemon:set/base-set/card/58/image/0"
    }
  ]
}

Cards & sealed products

Vector image search

Find visually similar trading cards using a precomputed image embedding.

Use this endpoint for:

image-based card recognition flows
camera upload search
similarity search from a cropped card artwork image

Preparation requirements:

Generate a single image embedding from one card image at a time.
Use CLIP ViT-B/32-compatible image preprocessing so the model input is prepared as float32 pixel values with shape [1, 3, 224, 224].
Use the model embedding output with shape [1, 512].
L2-normalize the 512-dimensional vector before sending it to this API.
Send only the normalized numeric vector in vectors. Do not send raw pixels, base64 image data, or wrapped model response objects.

Behavior:

Accepts exactly one 512-dimensional embedding per request.
Accepts an optional limit between 1 and 10. If omitted, the API returns up to 5 matches.
Returns visually similar card matches, ordered by similarity score.
Each match includes the scored card identifier fields needed to resolve the card and display a primary image preview.

Good to know:

This route is designed for image embeddings only. It does not generate embeddings from uploaded files.
Invalid vectors are rejected before any similarity search is performed.

POST

vector

Vector image search

curl --request POST \
  --url https://api.managem.co.uk/search/vector \
  --header 'Content-Type: application/json' \
  --data '
{
  "limit": 3,
  "vectors": [
    1,
    0,
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    0,
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  ]
}
'

{
  "count": 2,
  "matches": [
    {
      "score": 0.9987,
      "urn": "urn:managem:pokemon:set/151/card/25",
      "game": "Pokemon",
      "title": "151: Pikachu",
      "number": "25",
      "image": "https://images.managem.co.uk/urn:managem:pokemon:set/151/card/25/image/0"
    },
    {
      "score": 0.9921,
      "urn": "urn:managem:pokemon:set/base-set/card/58",
      "game": "Pokemon",
      "title": "Base Set: Pikachu",
      "number": "58",
      "image": "https://images.managem.co.uk/urn:managem:pokemon:set/base-set/card/58/image/0"
    }
  ]
}

Body

application/json

Request payload for similarity search using a precomputed trading card image embedding.

vectors

number[]

required

A 512-dimensional image embedding prepared from a single trading card image.

limit

integer

Maximum number of matches to return. Must be between 1 and 10. Defaults to 5.

Required range: 1 <= x <= 10

Example:

3

Response

Scored vector matches for the submitted image embedding

Similarity search results for a single trading card image embedding.

count

integer

required

Number of matches returned for the submitted vector.

Required range: x >= 0

matches

object[]

required

Scored vector matches sorted from most similar to least similar.

Show child attributes

Lookup items by URN Search users