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# import gradio as gr
# def greet(name):
# return "Hello " + name + "!! (welcome to testing)"
# iface = gr.Interface(
# fn = greet,
# inputs = "text",
# outputs = "text"
# )
# iface.launch(share = True)
from fastai.vision.all import *
import gradio as gr
def is_cat(x):
return x[0].isupper()
#|export
dog_path = 'aku.jpeg'
cat_path = 'munchkin.jpeg'
dunno_path = 'dunno.jpeg'
model_path = 'model.pkl'
learn = load_learner(model_path)
#|export
categories = ('Dog', 'Cat')
def classify_image(image):
predict, index, probabilities = learn.predict(image)
output = dict(zip(categories, map(float, probabilities)))
return output
image = gr.Image() # image = gr.inputs.Image(shape = (192, 192))
label = gr.Label() # label = gr.Label()
examples = [dog_path, cat_path, dunno_path] # examples = ['aku.jpeg', 'munchkin.jpeg', 'dunno.jpeg']
interface = gr.Interface(
fn = classify_image,
inputs = image,
outputs = label,
examples = examples
)
interface.launch(inline = False, share = True) |