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import gradio as gr | |
from predict import predict_gradio | |
title = "Mohammad Ali Food101 Classification🍔" | |
description = "This demo is a related to classification of 101 different foods." | |
with open('gradio_results.md') as f: | |
article = f.read() | |
interface_options = { | |
"article": article, | |
"layout": "horizontal", | |
"theme": "default", | |
} | |
demo = gr.Interface( | |
predict_gradio, | |
inputs = gr.Image(type="pil"), | |
outputs = [gr.Label(num_top_classes = 5 , label = "All Predictions in 5 most value predicted classes"), | |
gr.Label(num_top_classes = 1 , label = "Model Predicts Image as a")], | |
examples=['examples/3243342.jpg', 'examples/1652678.jpg', 'examples/1046933.jpg', 'examples/1840999.jpg', 'examples/168855.jpg'], | |
title = title, | |
description = description, | |
**interface_options | |
) | |
demo.launch() | |