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.
Plant.id API v2
Identify your plant
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.
Request
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)
Response
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)
Try it yourself!
We prepared a simple code to demostrate, how the API works. See the Python example
Documentation
See our documentation for full reference.