Update app.py

app.py

@@ -5,7 +5,6 @@ from tensorflow.keras.preprocessing import image
 import numpy as np
 from PIL import Image
 import io
-import os
 
 app = FastAPI(title="OralScan Model API")
 
@@ -35,7 +34,7 @@ async def predict(file: UploadFile = File(...)):
         contents = await file.read()
         img = Image.open(io.BytesIO(contents)).convert("RGB")
         
-        # Resize to 224x224 (what MobileNetV2 expects)
+        # Resize to 224x224
         img = img.resize((224, 224))
         
         # Preprocess
@@ -48,8 +47,12 @@ async def predict(file: UploadFile = File(...)):
         predicted_class = int(np.argmax(predictions[0]))
         confidence = float(np.max(predictions[0]) * 100)
 
-        # Change these class names to match your actual 3 classes
-        class_names = ["Healthy", "Mild Condition", "Severe Condition"]
+        # Your actual class names
+        class_names = [
+            "Oral Homogenous Leukoplakia",
+            "Oral Non-Homogenous Leukoplakia",
+            "Other Oral White Lesions"
+        ]
 
         return {
             "predicted_class": predicted_class,