Update app.py

app.py

@@ -8,6 +8,7 @@ import pandas as pd
 import warnings
 import math
 import numpy as np
+from tensorflow.keras.models import load_model
 
 # Suppress warnings
 warnings.filterwarnings("ignore", category=UserWarning, message="Using a slow image processor as `use_fast` is unset")
@@ -35,6 +36,7 @@ model_3 = AutoModelForImageClassification.from_pretrained(models[0]).to(device)
 feature_extractor_4 = AutoFeatureExtractor.from_pretrained(models[1])
 model_4 = AutoModelForImageClassification.from_pretrained(models[1]).to(device)
 
+model_5 = load_model("large_model_3lakh_v1.h5")
 # Define class names for all models
 class_names_1 = ['artificial', 'real']
 class_names_2 = ['AI Image', 'Real Image']
@@ -155,13 +157,20 @@ def predict_image(img, confidence_threshold):
             label_4 = "Uncertain Classification"
     except Exception as e:
         label_4 = f"Error: {str(e)}"
-    
+
+    try:
+        pred = model.predict(np.expand_dims(img_pil / 255, 0))
+        result_5 = {
+            'AI': pred[0],
+            'Real': pred[1]
+        }
     # Combine results
     combined_results = {
         "SwinV2": label_1,
         "AI-vs-Real-Image-Detection": label_2,
         "Organika/sdxl-detector": label_3,
-        "cmckinle/sdxl-flux-detector": label_4
+        "cmckinle/sdxl-flux-detector": label_4,
+        "ALSv": label_5
     }
     
     return combined_results