Update app.py

app.py

@@ -0,0 +1,35 @@
+import gradio as gr
+from tensorflow.keras.preprocessing import image
+from tensorflow.keras.models import load_model
+import numpy as np
+
+def predict(image_file):
+    width, height = 224, 224
+    img = image.img_to_array(image_file)
+    img = np.expand_dims(img, axis=0)
+    img = img / 255
+
+    model = load_model("/content/vgg16_model.h5")
+    result = model.predict(img)
+
+    if result[0][0] >= 0.5:
+        prediction = "Malignant"
+    else:
+        prediction = "Benign"
+
+    return prediction
+
+iface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(label="Upload Image"),
+    outputs=gr.Textbox(label="Predicted Results"),
+    title="Skin Cancer Prediction",
+    description="Upload an image containing skin lesion to predict if it is malignant or benign.",
+    theme="huggingface",
+    allow_flagging=False,
+    examples=[
+        ["example.jpg"],  # Replace "example.jpg" with actual example image file path
+    ]
+)
+
+iface.launch(share=True)