import gradio as gr
from fastai.vision.all import *
import skimage


learn = load_learner('model.pkl')
#from huggingface_hub import from_pretrained_fastai
#learn = from_pretrained_fastai("devdatanalytics/commonbean")

labels = learn.dls.vocab
def predict(img):
    img = PILImage.create(img)
    pred,pred_idx,probs = learn.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

#title = "Common beans diseases classfier"
#description = "An app for Common beans diseases Classisfication"
#article="<p style='text-align: center'>The app identifies and classifies common beans diseases: Anthracnose and Bean rust.</p>"
# Create the Gradio interface
interface = gr.Interface(
    fn=predict,
    inputs=gr.Image(),
    outputs=gr.Label(num_top_classes=3)
)

# Enable the queue to handle POST requests
interface.queue(api_open=True)

# Launch the interface
interface.launch()