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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+Best_Model_On_Partial.keras filter=lfs diff=lfs merge=lfs -text

Best_Model_On_Partial.keras

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3e168c670b5d153c0d8e128502f34c2330b337536636866ec43d7b973fcfe285
+size 283521382

app.py

@@ -0,0 +1,67 @@
+import gradio as gr
+import tensorflow as tf
+import numpy as np
+from PIL import Image
+
+# Load the trained model
+model = tf.keras.models.load_model("Best_Model_On_Partial.keras")
+
+# Class labels
+class_labels = ['Glioma', 'Meningioma', 'No Tumor', 'Pituitary']
+
+# Image preprocessing function
+def preprocess_image(image):
+    image = image.convert("RGB")
+    image = image.resize((224, 224))
+    image = np.array(image) / 255.0  # Normalize
+    image = np.expand_dims(image, axis=0)  # Add batch dimension
+    return image
+
+# Prediction function
+def predict(image):
+    processed_image = preprocess_image(image)
+    prediction = model.predict(processed_image)
+    predicted_class = np.argmax(prediction)
+    confidence = np.max(prediction) * 100
+    
+    return f"🧠 Prediction: {class_labels[predicted_class]} (Confidence: {confidence:.2f}%)"
+
+# Customizing Gradio UI
+custom_css = """
+    body {background-color: #1A1F3B; color: #E0E0E0; font-family: Arial, sans-serif;}
+    .gradio-container {max-width: 800px; margin: auto; text-align: center;}
+    .gr-button {background-color: #007BFF !important; color: white !important; border-radius: 8px;}
+    .gr-box {background-color: #2C3E50; padding: 10px; border-radius: 10px;}
+"""
+
+description = """
+🧠 **Brain Tumor Detector**  
+Upload an MRI scan to classify brain tumors using deep learning.  
+💡 **Supports:** Glioma | Meningioma | No Tumor | Pituitary  
+🚀 **Fast & Accurate AI Model**
+"""
+
+with gr.Blocks() as interface:
+    gr.HTML("<img src='Figure 2025-01-07 031757 (8).png' style='width:100px; position:absolute; top:10px; left:10px;'>")
+    gr.Markdown("## Brain Tumor Detection 🧠")
+    image = gr.Image(type="pil", label="Upload Brain MRI")
+    output = gr.Textbox(label="Prediction")
+    btn = gr.Button("Predict")
+    
+    btn.click(predict, inputs=image, outputs=output)
+    
+# UI Interface
+interface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil", label="Upload Brain MRI"),
+    outputs=gr.Textbox(label="Prediction"),
+    title="Brain Tumor Detection 🧠",
+    description="Upload an MRI scan to classify brain tumors using deep learning.",
+    theme="default",
+    css=custom_css,
+    examples=["/mnt/data/2.webp"]  # Use the uploaded image as an example
+)
+
+# Launch the app
+interface.launch()
+

requirements.txt

@@ -1,4 +1,4 @@
-gradio
 tensorflow
+gradio
 numpy
 pillow