Upload app.py

app.py

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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 FYP Model Demo", description="FYP Demo by FYP GROUP:- 20F-18 \n [Leader: Humza Ali \n | Members: Dilshad Hussain, Yasir Ali]")
+io.launch()