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# Python script, Unicode text, UTF-8 text executable, with CRLF line terminators
import requests
import json
from pprint import pprint
import gradio as gr
import os
API_KEY = os.environ.get('PLANT_API_KEY') # Your API_KEY from https://my.plantnet.org/account/settings
PROJECT = "all"; # try specific floras: "weurope", "canada"
api_endpoint = f"https://my-api.plantnet.org/v2/identify/{PROJECT}?api-key={API_KEY}&lang=zh"
def identify_plant(image_paths, organs):
files = []
for image_path in image_paths:
image_data = open(image_path, 'rb')
files.append(('images', (image_path, image_data)))
data = {'organs': organs}
req = requests.Request('POST', url=api_endpoint, files=files, data=data)
prepared = req.prepare()
s = requests.Session()
response = s.send(prepared)
json_result = json.loads(response.text)
# Close the opened files
for _, (_, image_data) in files:
image_data.close()
return response.status_code, json_result
def gradio_interface(image_path, organs):
image_paths = [image_path]
print(image_paths)
status_code, json_result = identify_plant(image_paths, organs)
return json_result.get("bestMatch",None), json_result
with gr.Blocks(title="Clay&Tree PlantyAI") as demo:
image = gr.Image(type="filepath", label = "Plant Image")
identify_btn = gr.Button("Identify")
organs_input = gr.CheckboxGroup(choices=["flower", "leaf", "fruit", "bark", "habit"],label="Organs", info="What are the organs?")
best_match_text = gr.Textbox(label="Scientific Name")
json_text = gr.JSON(label="Raw Json String")
identify_btn.click(gradio_interface, inputs=[image,organs_input], outputs = [best_match_text,json_text])
demo.launch()
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