app.py

# import gradio as gr

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

# iface = gr.Interface(fn=greet, inputs="text", outputs="text")
# iface.launch()
from fastai.vision.all import *
import gradio as gr

learn = load_learner("model_lec2.pkl")

brd_category = (
    "Black Woodpecker", 
    "Eurasian Three-Toed Woodpecker",
    "Great Spotted Woodpecker",
    "Green Woodpecker",
    "Grey-Headed Woodpecker",
    "Lesser Spotted Woodpecker",
    "Middle Spotted Woodpecker",
    "White-Backed Woodpecker",
    )

def classify_image(img):
    pred,idx,probs = learn.predict(img)
    return dict(zip(brd_category, map(float,probs)))

image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
examples = [
    "blk_woodpeck.jpg",
    "grt_spot_woodpeck.jpg",
    "eur_woodpeck.jpg",
    ]

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