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


learn = load_learner('model.pkl')


labels = learn.dls.vocab

def greet(name): return f"Hello {name}!"
gr.Interface(fn=greet, inputs="text", outputs="text").launch()

# def predict(img):
#     img = Image.open(img)
#     pred,pred_idx,probs = learn.predict(img)
#     return {labels[i]: float(probs[i]) for i in range(len(labels))}

# title = "Shark vs Bird Classifier"
# description = "A Shark vs Bird classifier trained using Duck Duck Go search engine with fastai. Created as a demo for Gradio and HuggingFace Spaces."

# examples = ['shark.jpg', 'bird.jpg']
# interpretation='default'
# enable_queue=True

# gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()