Upload 3 files

app.py

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+import gradio as gr
+import tensorflow as tf
+from tensorflow.keras.preprocessing import image
+import numpy as np
+from PIL import Image
+
+# تحميل الموديل
+model = tf.keras.models.load_model("model.h5")
+
+# دالة التنبؤ
+def predict(img):
+    img = img.resize((228, 228))  # تأكد من نفس المقاس المستخدم في التدريب
+    img_array = image.img_to_array(img)
+    img_array = np.expand_dims(img_array, axis=0)
+    img_array = img_array / 255.0
+
+    prediction = model.predict(img_array)[0][0]
+    label = "Stroke" if prediction > 0.5 else "No Stroke"
+    confidence = round(float(prediction) * 100, 2) if prediction > 0.5 else round((1 - float(prediction)) * 100, 2)
+    return f"{label} ({confidence}%)"
+
+# إنشاء واجهة Gradio
+interface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="Brain Stroke Detection",
+    description="Upload a CT scan image to detect stroke probability."
+)
+
+interface.launch()

model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5e4c7de57bd900c1f9789b197efc682ff480ce25b761cf249bfa5506f04644f1
+size 86072208

requirements.txt

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+gradio
+tensorflow
+Pillow