from fast.ai.vision.all import *
import gradio as gr

# def greet(name):
#    return "Hello " + name + "!!"

# iface = gr.Interface(fn=greet, inputs="text", outputs="text")
# iface.launch()




# from:
#  https://course.fast.ai/Lessons/lesson2.html
#  https://github.com/fastai/fastbook/blob/master/02_production.ipynb


#learn_inf = load_learner(path/'export.pkl')
#learn_inf.predict('images/grizzly.jpg')
#learn_inf.dls.vocab


# model created from: https://www.kaggle.com/code/zachwormgoor/stock-photo-recognizer
learn = load_learner('model.pkl')

categories = ('stock', 'amateur')

def classify(img):
    pred,idx,probs = learn.predict(img)
    return dict(zip(categories, map(float,probs)))
    
    
image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ['stock.jpg', 'amateur.jpg', 'unsure.jpg']

intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False)