Spaces:
Sleeping
Sleeping
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## import gradio as gr
#
## def greet(name):
## return "Hello " + name + "!!"
#
## iface = gr.Interface(fn=greet, inputs="text", outputs="text")
## iface.launch()
import gradio as gr
from fastai.vision.all import *
import skimage
import pathlib
temp = pathlib.PosixPath
pathlib.PosixPath = pathlib.WindowsPath
pathlib.PosixPath = temp
learn = load_learner('model.pkl')
labels = learn.dls.vocab
def predict(img):
img = PILImage.create(img)
pred,pred_idx,probs = learn.predict(img)
return {labels[i]: float(probs[i]) for i in range(len(labels))}
title = "Female/Male Classifier"
description = "A Female/Male classifier trained on the duckduckgo search result with fastai. Created as a demo for Gradio and HuggingFace Spaces."
## article="<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Blog post</a></p>"
examples = ['femaleDefault.jpg', 'maleDefault.jpg',
'dragQueen1.jpg', 'dragQueen2.jpg',
'femaleAngry1.jpg', 'femaleAngry2.jpg',
'femaleMuscle1.jpg', 'femaleMuscle2.jpg',
'maleAsian.jpg', 'maleEurope.jpg',
'femaleAsian.jpg', 'femaleDefault.jpg',
'maleCrying2.jpg', 'maleCrying2No.jpg']
#interpretation='default'
enable_queue=True
#
## gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(),title=title,description=description,article=article,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()
#
inter = gr.Interface(
fn=predict,
inputs=gr.inputs.Image(shape=(512, 512)),
outputs=gr.outputs.Label(),
title=title,
description=description,
examples=examples,
cache_examples=True,
examples_per_page=2)
inter.queue()
inter.launch() |