Predict
Predict categories for a product
Predictions are performed using a neural model. As input, you can either provide:
- the
barcodeof a product: Robotoff will fetch the product from Product Opener and will use this data as inputs to predict categories. - expected inputs under a
productkey. The neural category model accepts the following fields as input:product_name,ingredients_tags,ocr,nutriments,image_embeddings. All fields are optional (but you should at least provide one).
barcodestring
The barcode of the product to categorize
Length
1 <= lengthserver_type?string
The server type (=project) to use, such as 'off' (Open Food Facts), 'obf' (Open Beauty Facts),... Only 'off' is currently supported for category prediction
Default
"off"Value in
"off" | "obf" | "opff" | "opf"deepest_only?boolean
If true, only return the deepest elements in the category taxonomy (don't return categories that are parents of other predicted categories)
threshold?number
The score above which we consider the category to be detected
Default
0.5productobject
product information used as model input. All fields are optional, but at least one field must be provided.
Properties
1 <= propertiesResponse Body
curl -X POST "https://robotoff.openfoodfacts.org/api/v1/predict/category" \
-H "Content-Type: application/json" \
-d '{
"barcode": "0748162621021"
}'{
"neural": [
{
"value_tag": "en:roast-chicken",
"confidence": 0.6
}
]
}