Update app.py

app.py

@@ -1,7 +1,30 @@
-import gradio as gr
-
-def greet(name):
-    return "Hello " + name + "!!"
-
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+import gradio as gr
+from PIL import Image
+import tensorflow as tf
+import numpy as np
+
+# Model load koro (example: EfficientNetB3)
+model = tf.keras.models.load_model("model.h5")  # model.h5 file upload koro
+
+# Class names (modify koro jodi dorkar hoy)
+class_names = ["Monkeypox", "Not Monkeypox"]
+
+def predict(image):
+    # Image resize & preprocess (modify koro jodi dorkar hoy)
+    img = image.resize((224, 224))
+    img = np.array(img) / 255.0
+    img = np.expand_dims(img, axis=0)
+    pred = model.predict(img)
+    label = class_names[np.argmax(pred)]
+    confidence = np.max(pred)
+    return f"{label} ({confidence*100:.2f}%)"
+
+iface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="Monkeypox Detection",
+    description="Upload a skin image to check for Monkeypox."
+)
+
+iface.launch()