Debug: parsing detections

requirements.txt

@@ -8,3 +8,4 @@ grad-cam==1.4.8
 gradio
 ultralytics
 torchcam
+YOLOv8-Explainer

yolov8.py

@@ -49,7 +49,7 @@ def generate_cam_image(model, target_layers, tensor, rgb_img, boxes):
     return cam_image, renormalized_cam_image
 
 
-def xai_yolov8n(image):
+def xai_yolov8nnnn(image):
     model = YOLO('yolov8n.pt')  # Load YOLOv8n pre-trained weights
     model.eval()
 
@@ -86,4 +86,31 @@ def xai_yolov8n(image):
 
     # Return final image and a caption
     caption = "Results using YOLOv8n"
-    return Image.fromarray(final_image), caption
+    return Image.fromarray(final_image), caption
+
+
+
+from YOLOv8_Explainer import yolov8_heatmap, display_images
+
+def xai_yolov8n(image):
+    model = yolov8_heatmap(
+        weight="yolov8n.pt", 
+            conf_threshold=0.4, 
+            device = "cpu", 
+            method = "EigenCAM", 
+            layer=[10, 12, 14, 16, 18, -3],
+            backward_type="all",
+            ratio=0.02,
+            show_box=True,
+            renormalize=False,
+    )
+
+    # Pass the NumPy array to the model
+    imagelist = model(image)  # Use the image array directly
+
+    # Display the resulting images
+    # Pass the NumPy array to the model
+    imagelist = model(image)  # Use the image array directly
+
+# Display the resulting images
+    print(imagelist)