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| import gradio as gr | |
| from transformers import pipeline | |
| from datasets import load_dataset | |
| import requests | |
| from bs4 import BeautifulSoup | |
| classifier = pipeline("text-classification", model="CesarLeblanc/test_model") | |
| dataset = load_dataset("CesarLeblanc/text_classification_dataset") | |
| def text_classification(text): | |
| result = classifier(text) | |
| habitat_label = result[0]['label'] | |
| habitat_label = dataset['train'].features['label'].names[int(habitat_label.split('_')[1])] | |
| habitat_score = result[0]['score'] | |
| formatted_output = f"This vegetation plot belongs to the habitat {habitat_label} with the probability {habitat_score*100:.2f}%" | |
| floraveg_url = f"https://floraveg.eu/habitat/overview/{habitat_label}" | |
| response = requests.get(url) | |
| if response.status_code == 200: | |
| soup = BeautifulSoup(response.text, 'html.parser') | |
| img_tag = soup.find('img', src=lambda x: x and x.startswith("https://files.ibot.cas.cz/cevs/images/syntaxa/thumbs/")) | |
| if img_tag: | |
| image_url = img_tag['src'] | |
| else: | |
| image_url = 'https://www.salonlfc.com/wp-content/uploads/2018/01/image-not-found-scaled-1150x647.png' | |
| else: | |
| image_url = 'https://www.salonlfc.com/wp-content/uploads/2018/01/image-not-found-scaled-1150x647.png' | |
| image_output = gr.Image(value=image_url) | |
| return formatted_output, image_output | |
| examples=["sparganium erectum, calystegia sepium, persicaria amphibia", "thinopyrum junceum, cakile maritima"] | |
| io = gr.Interface(fn=text_classification, | |
| inputs= gr.Textbox(lines=2, label="List of comma-separated binomial names of species (see examples)", placeholder="Enter species here..."), | |
| outputs=[gr.Textbox(lines=2, label="Vegetation Plot Classification Result"), "image"], | |
| title="Pl@ntBERT", | |
| description="Vegetation Plot Classification: enter the species found in a vegetation plot and see its EUNIS habitat!", | |
| examples=examples) | |
| io.launch() |