Diagnose with plant.health
Integrate plant.health into your business and discover the world of AI-powered disease identification and plant care.
Plant care made easy
Plant.id API offers not only for plant identification but also disease diagnosis from images, utilizing hundreds of thousands expert-annotated data. It provides multilingual options for developers and R&D teams to craft innovative and user-centric solutions.
90 diseases classes
Common names, synonyms and taxonomy
Licence for representative images
Unlimited scalability
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Excellent precision
Recognizing the complexity of plant diseases, we employed top phytosanitary experts to annotate photos of diseased plants. This allowed us to go beyond mere symptoms and diagnose the actual disease, achieving unparalleled specificity and confidence.
Care for the future
We constantly improve the plant.health API. In 2024, we have an exciting update designed to elevate your experience.
October 2024: Symptom recognition: We will implement object detection methods to highlight diseased areas of a plant, taking the identification experience to a new level.
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Let's plant the next big success together!
Enhance your applications with our cutting-edge plant identification technology. Captivate your users and transform their experience with plant.id. Your journey starts now.
FAQs
Find answers to common questions about plant.health here. If you need further information, feel free to reach out.
Yes, we have an extra model is_healthy that can identify whether a plant is healthy or diseased. You can use the health = auto attribute to decide whether an image should undergo a health assessment automatically. If the model’s output exceeds a specific threshold, indicating the presence of a diseased plant, the image will be sent to the health assessment. If the plant is considered healthy, the cost is one credit. If the plant is considered diseased and a health assessment is requested, the cost is two credits.
If you want responses from both Species Identification and health assessment, you can set the parameter health = all. The total cost would be two credits.
The cost is one identification credit, the same as for plant identification. In case you want both the plant.id and plant.health results for a single plant, the cost is one credit for each product. The base price is €0.05 per credit. Discounts are available for bulk orders. Contact business@plant.id for details.
Diagnosing plant health is often a complex task. For example, if a plant is consistently overwatered, it is also unable to use nutrients effectively, so it will develop symptoms of both overwatering and nutrient deficiency. Therefore, when implementing this functionality, we recommend that you list more than one possible cause of disease in the result.
However, you can also improve the result by taking a photo of a diseased part of a plant for best results. Read our blog post for tips on using plant.health. Some diseases have less visible symptoms (e.g. small pests), and the detail is crucial for correct identification.
You can use the redundant attribute for discarding parent classes.
Discarding parent classes is useful when the difference between the probability of the parent class (higher in the hierarchy) and the child class (lower in the hierarchy) is insignificant. In this case, classes that can be discarded have a boolean attribute redundant in the response.
Specifically, this feature in the response activates when the probability of the child class is at least 80% of the probability of the parent class (or less than two percentages in absolute numbers that aim to assess cases with a probability of less than 10%). For example, when the probability of a parent class (e.g. water-related issue) is 95% and the probability of a child class (e.g. water deficiency) is at least 76%, then the attribute redundant=true will appear in the response.
Plant.health does not focus on a specific group of plants, although most annotations are for houseplants and ornamentals. Crop.health focuses on a broad range of diseases of selected food crops. You can read more about the differences in the crop.health FAQ section.