|
|
|
import gradio as gr |
|
import os |
|
import torch |
|
from typing import Tuple, Dict |
|
from timeit import default_timer as timer |
|
|
|
|
|
from predictor import predictionMaker |
|
|
|
exampleList = [["examples/" + example] for example in os.listdir("examples")] |
|
|
|
title = "Detecting Retinal Diseases for Early Prevention" |
|
description = "An EfficientNetB2 feature extractor computer vision model to classify OCT images into Brain Tumor types: CNV, DME, Drusen and Normal" |
|
article = "Created by [Eternal Bliassard](https://github.com/EternalBlissard)." |
|
|
|
|
|
demo = gr.Interface(fn=predictionMaker, |
|
inputs=[gr.Image(type="pil")], |
|
outputs=[gr.Label(num_top_classes=2, label="Predictions"), |
|
gr.Number(label="Prediction time (s)")], |
|
examples=exampleList, |
|
title=title, |
|
description=description, |
|
article=article) |
|
|
|
|
|
demo.launch() |
|
|
|
|
|
|
|
|
|
|