Plant.id offers a plant identification service based on machine learning. Once you obtain the API key, you can use these client's code to speed-up the development of your implementation.
Send plant photos to our back end, wait for identification, and return the result. If the identification takes more than the identification_timeout
, return identification info without any suggestions.
Send POST request to: https://api.plant.id/v2/identify
and include following parameters:
api_key
- your API keyimages
- one ore more images of the plant you want to identify (string - base64 or a file)
Other optional parameters:
modifiers
- list of strings:"crops_simple"
/"crops_fast"
(default)/"crops_medium"
- specify the speed & accuracy of the identification"similar_images"
- allow displaying of similar images -> If you want to get similar images in the response, you must include itemsimilar_images
here.
plant_language
- language code (ISO 639-1) used forplant_details
(default"en"
)plant_details
- list of strings, which determines which information about the plant will be included in the response (if the data is available)"common_names"
- list of common names of the plant in the language specified inplant_language
"url"
- link to page with the plant profile (usually Wikipedia)"name_authority"
- scientific name of the plant"wiki_description"
- description of the plant from Wikipedia with source url and license"taxonomy"
- dictionary with the plant taxonomy
- and more (see the Documentation)
The result contains a list of suggestions of possible plant species (taxons). Each suggestion contains:
scientific_name
- the scientific name of the plantcommon_names
- list of common names of the plant (if available)url
- link to page with the plant profile (usually Wikipedia)wiki_description
- description of the plant from Wikipedia (if available)taxonomy
- taxonomy of the plant (if available)probability
- certainty level that suggested plant is the one from the photosimilar_images
- representative images of the identified species carefully selected by the model, so it resembles the input image (Similar images are included in the result only if you add the valuesimilar_image
in themodifiers
list of the request.)- and more (see the Documentation)
We prepared a simple code to demostrate, how the API works. See the Python example
See our documentation for full reference.