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import gradio as gr
import numpy as np
import onnxruntime as ort
import json
from cryptography.fernet import Fernet
import os
# Model load
key = os.getenv("ARTER_MODEL_KEY")
cipher = Fernet(key)
with open("model.bin", "rb") as f:
encrypted = f.read()
decrypted = cipher.decrypt(encrypted)
ort_session = ort.InferenceSession(decrypted)
# Initialize ONNX session
input_name = ort_session.get_inputs()[0].name
def softmax(x):
return np.exp(x) / np.sum(np.exp(x), axis=1)
# Load mappings
with open("species_to_idx.json", "r") as f:
species_to_idx = json.load(f)
with open("idx_to_target.json", "r") as f:
idx_to_target = json.load(f)
target_list = list(idx_to_target.keys())
def predict(species):
if not species:
return {}, {}, {}
input = [species_to_idx[s] for s in species]
input_np = np.array(input, dtype=np.int64).reshape(1, -1)
output = ort_session.run([], {input_name: input_np})
output = {target: softmax(output[i]) for i, target in enumerate(target_list)}
format_output = []
for target in target_list:
probs = output[target][0]
classes = idx_to_target[target]
format_output.append({classes[str(i)]: float(p) for i, p in enumerate(probs)})
return format_output
# Gradio interface
with gr.Blocks() as demo:
gr.Markdown("## Naturtype og §3 klassifikation baseret på artsfund")
gr.Markdown("Dette værktøj analyserer artsregistreringer for at bestemme et områdes hovednaturtype, naturtilstand og om området er omfattet af Naturbeskyttelseslovens paragraf 3.")
with gr.Row():
choices = sorted(species_to_idx.keys())
species_dropdown = gr.Dropdown(
choices=choices,
multiselect=True,
label="Vælg arter",
)
with gr.Row():
naturtype = gr.Label("", label="Hovednaturtype")
p3 = gr.Label("", label="§3 område")
tilstand = gr.Label("", label="Naturtilstand")
gr.Markdown("App og model af Kenneth Thorø Martinsen (kenneth2810@gmail.com).")
species_dropdown.change(
predict,
inputs=[species_dropdown],
outputs=[naturtype, p3, tilstand]
)
if __name__ == "__main__":
demo.launch()
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