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Example client's code for work with identification API in various languages
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python 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.

What you'll get

For each identification requests, the API reponse a multiple species suggestions like this:

  "id": 3010636,
  "plant": {
    "name": "Buddleja davidii",
    "url": "",
    "common_name": "Butterfly-Bush"
  "probability": 0.9277143686644568,
  "confidence": 0.9798141922207031,
  "similar_images": [
      "id": "605775c7cb05e8463f7f8463b0fd915c",
      "similarity": 0.9318117206281141,
      "url": " davidii/605775c7cb05e8463f7f8463b0fd915c.jpg",
      "url_small": " davidii/605775c7cb05e8463f7f8463b0fd915c.small.jpg"
      "id": "890cf5e5b94a255ea4e517d785f53481",
      "similarity": 0.9316171609752804,
      "url": " davidii/890cf5e5b94a255ea4e517d785f53481.jpg",
      "url_small": " davidii/890cf5e5b94a255ea4e517d785f53481.small.jpg"
  "confirmed": false

Those "similar images" are representative images of the identified species carefuly selected by the model so it resembles the the input image.

API reference

Result of the identification is a list of records showing possible plant species (taxons). Each records contains: scientific name of the plant, probability (certainty level), representative images of the suggested taxon, common name and/or url.

See for full reference.

Python example

See python file

Android/java example

See android directory

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