import gradio as gr
from fastai.vision.all import load_learner

nlearn = load_learner('./Ey.pkl')

categories = ('Chennai', 'London')

def classify_img(img):
    pred, idx, prob = nlearn.predict(img)
    return dict(zip(categories, map(float, prob)))

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

# classify_img('/kaggle/input/help-me/Screenshot 2024-02-08 at 23.19.37.png')

image = gr.Image(height=192,width=192)
label = gr.Label()
desc = "This model classifies satellite image of a particular area into possible cities. right now this is trained with Chennai and London city images"
examples = ['./test_data/chennai_1.png', './test_data/chennai_2.png', './test_data/chennai_3.png', './test_data/london_1.png', './test_data/chennai_1.png']

intf = gr.Interface(fn=classify_img, inputs=image, outputs=label, examples=examples, description=desc)
intf.launch()

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