Update gradcam_utils.py

gradcam_utils.py

@@ -147,28 +147,32 @@
 
 
 
-from tf_explain.core.grad_cam import GradCAM
 import numpy as np
+from tf_explain.core.grad_cam import GradCAM
+import tensorflow as tf
+from tensorflow.keras.preprocessing.image import img_to_array
 from PIL import Image
 
-def generate_heatmap_tf_explain(image_pil, model, class_index, layer_name="block5_conv4"):
-    from tf_explain.core.grad_cam import GradCAM
-
-    # Preprocess image
-    img_array = np.array(image_pil.resize((224, 224))) / 255.0
+def generate_heatmap_tf_explain(image_pil, model, class_index):
+    # Convert to numpy and preprocess
+    img = image_pil.resize((224, 224))
+    img_array = img_to_array(img) / 255.0
     img_array = np.expand_dims(img_array, axis=0)
 
-    # Reconstruct model to include target layer
-    from tensorflow.keras.models import Model
-    model_for_explanation = Model(inputs=model.input, outputs=model.output)
+    # Prepare data
+    data = ([img_array], None)
 
+    # Run tf-explain GradCAM
     explainer = GradCAM()
     explanation = explainer.explain(
-        validation_data=(img_array, None),
-        model=model_for_explanation,
+        validation_data=data,
+        model=model,
         class_index=class_index,
-        layer_name=layer_name
+        layer_name=None  # will auto-detect final conv layer
     )
 
-    return Image.fromarray(explanation)
+    # Convert explanation (numpy) to PIL
+    heatmap_pil = Image.fromarray(explanation).resize((224, 224))
+    return heatmap_pil
+