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from skimage import io | |
import base64 | |
from tensorflow.keras.models import load_model | |
import numpy as np | |
import gradio | |
import moleimages | |
model = load_model("mymodel-2.h5") | |
def predict(input): | |
mimg = moleimages.MoleImages() | |
X = mimg.load_image(input) | |
y_pred = model.predict(X) | |
return {"Benign": float(y_pred[0][0]), "Malignant": float(1-y_pred[0][0])} | |
io = gradio.Interface(fn=predict, inputs='image', outputs='label', analytics_enabled=True, | |
title="Skin Cancer Detection & Classification", description="") | |
io.launch() | |