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import gradio as gr
from fastai.vision.all import *
import skimage
learn = load_learner('jha2ee/riffusion-model-v1')
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 = "StableDiffusion_SoundFX"
description = "Generate sound FX"
article = "<p style='text-align: center'><a href='https://huggingface.co/riffusion/riffusion-model-v1' " \
"target='_blank'>Blog post</a></p> "
examples = ['sample.jpeg']
interpretation = 'default'
enable_queue = True
gr.Interface(
fn=predict,
inputs=gr.inputs.Image(shape=(512, 512)),
outputs=gr.outputs.Label(num_top_classes=3),
title=title,
description=description,
article=article,
examples=examples,
interpretation=interpretation,
enable_queue=enable_queue
).launch()
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