Update app.py

app.py

@@ -1,40 +1,28 @@
-import gradio as gr
-import numpy as np
-from tensorflow.keras.models import load_model
-from PIL import Image
-import requests
-import h5py
-import os
-
-# Download model only if not already present
-model_path = "xception_model.h5"
-if not os.path.exists(model_path):
-    url = "https://huggingface.co/Zeyadd-Mostaffa/cv_GP/resolve/main/xception_model.h5"
-    with open(model_path, "wb") as f:
-        f.write(requests.get(url).content)
-
-# Load model
-model = load_model(model_path)
-
-# Preprocess function
-def preprocess_image(image):
-    image = image.resize((150, 150)).convert("RGB")
-    arr = np.array(image) / 255.0
-    return np.expand_dims(arr, axis=0)
-
-# Prediction function
-def predict(image):
-    img = preprocess_image(image)
-    prob = model.predict(img)[0][0]
-    label = "REAL" if prob >= 0.5 else "FAKE"
-    return {"REAL": 1 - prob, "FAKE": prob}, f"Prediction: {label}"
-
-# Gradio UI
-demo = gr.Interface(
-    fn=predict,
-    inputs=gr.Image(type="pil"),
-    outputs=[gr.Label(num_top_classes=2), gr.Text()],
-    title="Deepfake Detection (Xception Model)"
-)
-
-demo.launch()
+import gradio as gr
+import numpy as np
+from tensorflow.keras.models import load_model
+from PIL import Image
+
+# Load pre-uploaded model
+model = load_model("xception_model.h5")
+
+def preprocess_image(image):
+    image = image.resize((299, 299)).convert("RGB")  # ✅ Fix: match Xception input shape
+    img_array = np.array(image) / 255.0
+    return np.expand_dims(img_array, axis=0)
+
+def predict(image):
+    img = preprocess_image(image)
+    prob = model.predict(img)[0][0]
+    label = "REAL" if prob >= 0.5 else "FAKE"
+    return {"REAL": 1 - prob, "FAKE": prob}, f"Prediction: {label}"
+
+demo = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil"),
+    outputs=[gr.Label(num_top_classes=2), gr.Text()],
+    title="Deepfake Detection (Xception Model)"
+)
+
+demo.launch()
+