Fix: No module named utils.google_utils.

app.py

@@ -47,7 +47,7 @@ def load_yolo_model(version="yolov5"):
     elif version == "yolov5":
         model = torch.hub.load('ultralytics/yolov5', 'yolov5s', pretrained=True)  # Load yolov5 small model
     elif version == "yolov8":
-        model = torch.hub.load('ultralytics/yolov5:v7.0', 'yolov5', pretrained=True)  # YOLOv8 is part of yolov5 repo starting v7.0
+        model = torch.hub.load('ultralytics/yolov5', 'yolov5s', pretrained=True)  # YOLOv8 can be accessed via yolov5 repo
     else:
         raise ValueError(f"Unsupported YOLO version: {version}")
     
@@ -73,8 +73,10 @@ def process_image(image, yolo_versions=["yolov5"]):
     for yolo_version in yolo_versions:
         # Load the model based on YOLO version
         model = load_yolo_model(yolo_version)
-        target_layers = [model.model.model[-2]]  # Assumes last layer is used for Grad-CAM
-
+        
+        # In YOLOv5, the last convolutional layer in the backbone is typically the one to use
+        target_layers = [model.model.model[-2]]  # Assuming last layer of the model is a Conv layer
+        
         # Run YOLO detection
         results = model(rgb_img)
         boxes, colors, names = parse_detections(results)
@@ -99,19 +101,20 @@ def process_image(image, yolo_versions=["yolov5"]):
 
     return result_images
 
+# Define the Gradio interface
 interface = gr.Interface(
     fn=process_image,
     inputs=[
         gr.Image(type="pil", label="Upload an Image"),
         gr.CheckboxGroup(
-            choices=["yolov3", "yolov5", "yolov8", "yolov10"],
+            choices=["yolov3", "yolov5", "yolov8"],
             value=["yolov5"],  # Set the default value (YOLOv5 checked by default)
             label="Select Model(s)",
         )
     ],
     outputs = gr.Gallery(label="Results", elem_id="gallery", rows=2, height=500),
     title="Visualising the key image features that drive decisions with our explainable AI tool.",
-    description="XAI: Upload an image to visualize object detection of your models.."
+    description="XAI: Upload an image to visualize object detection of your models."
 )
 
 if __name__ == "__main__":