FAQ for Plant.id API
Most frequent questions and answers
- How to increase identification accuracy?
- How to increase identification speed?
- What kind of plants can you actually identify?
- What is the pricing?
- What does the “similar images” feature do?
- I can’t see any similar_images in the get_identification_result response
- What is the difference between the plant_name and the plant_details.scientific_name?
How to increase identification accuracy?
- Include multiple photos of a single plant to the plant identification request.
- Include GPS coordinates.
- There is a list of parameters (see
modifiersin /identify or /enqueue_identification endpoints), which enable you to trade off the accuracy for identification speed. However, it is not allowed by default; contact us if you need help.
- The default model is very general. However, we can create a specific model explicitly focused on your use case – for example, Mediterranean crops, Canadian weeds, or European trees. We can even use your own datasets to improve the model, for example, with satellite images. We can also train a customized new model, focused, for example, for estimation of the plant’s health.
How to increase identification speed?
In the administration, you can see an identification time (guaranteed by the SLA) per each request. This time value, however, does not account for image preprocessing (downscaling the resolution). That is the reason why the measured response time is higher than the identification time.
You can mitigate this delay by resizing the image on your side. To get the fastest response, set the photos’ size so that the longer side has 800 px. You can also use an /identify endpoint to get the identification directly into the response to your request to gain a second or two.
In special cases, it might be worth to ask us on email@example.com for a dedicated ML model (we might be able to go under 1 second).
What kind of plants can you actually identify?
Our machine learning model is mainly based on photos we have gathered running FlowerChecker in the past six years. The data contain photos of wild-growing, garden, and indoor plants.
We can currently identify more than 9963 plant species of various life forms, including trees, shrubs, and succulents. Besides, our database consists of the most common mushrooms, lichens, and mosses.
Regarding native plants, the countries marked by a green color are best covered by the database.
What is the pricing?
The base pricing is €0.05 per identification. There are discounts for bulk orders. The final price also depends on the identification speed and accuracy. Please contact us on firstname.lastname@example.org to discuss these issues.
What does the “similar images” feature do?
This is actually our smartest feature!
You see – name of the plant is not the only piece of information you will get from the API. We also provide representative images of a suggested taxon (species or genus).
The representative images are not static; they are selected based on the similarity with photos uploaded by your customer to achieve user satisfaction. Let us illustrate:
There are three different identifications of three different photos of a dandelion. The first one shows a puffy ball with seeds, the second one a leaf rosette, and the third one a plant in full bloom. As you can see, the Plant.id provides representative images of a dandelion based on the user’s picture. You are welcome to use our images in your app. What a great tool to improve user’s satisfaction with your service!
I can’t see any similar_images in the get_identification_result response
What is the difference between different plant names?
Plant.id API results give you four types of records related to plant names for a single taxon suggestion (taxon is the basic unit in the taxonomy hierarchy)
- plant_name Is a string which conclusively indicates the result of the identification. It is basically an ID which we are striving to keep unchanged across all Plant.id versions. Therefore, you can use it as a key for linking other in-app content.
Example: “Taraxacum officinale”
- plant_details.scientific_name stands for a scientific name (in Latin). It is the taxon name currently accepted by botanists.
Example: “Taraxacum campylodes G.E.Haglund”
- plant_details.synonyms lists other scientific names for the same species if there are any. They are considered also correct, but usually outdated because of nomenclature changes. See the explanation on Wikipedia
Example: [“Taraxacum vulgare var. vulgare”,”Taraxacum vulgare (Lam.) Schrank”, …].
TLDR botanical authorities change scientific names sometimes. The plant_details.scientific_name reflects the present taxonomy consensus. To keep the system stable, we use the plant_name which also mitigates necessary changes because of improving our service.