Removed GradCAM

app.py

@@ -22,7 +22,7 @@ data = "data.yaml"
 # Load model
 device = select_device('cpu')
 model = DetectMultiBackend(weights, device=device, dnn=False, data=data, fp16=False)
-target_layers = [model.model.model[-1]]
+#target_layers = [model.model.model[-1]]
 
 false_detection_data = glob(os.path.join("false_detection", '*.jpg'))
 false_detection_data = [x.replace('\\', '/') for x in false_detection_data]
@@ -113,11 +113,11 @@ def inference(input_img, conf_thres, iou_thres, is_false_detection_images=True,
     else:
         misclassified_images = None
 
-    cam = EigenCAM(model, target_layers)
-    grayscale_cam = cam(im)[0, :]
-    cam_image = show_cam_on_image(rgb_img, grayscale_cam, use_rgb=True)
+    # cam = EigenCAM(model, target_layers)
+    # grayscale_cam = cam(im)[0, :]
+    # cam_image = show_cam_on_image(rgb_img, grayscale_cam, use_rgb=True)
 
-    return im0, cam_image, misclassified_images
+    return im0, misclassified_images
 
 title = "YOLOv9 model to detect shirt/tshirt"
 description = "A simple Gradio interface to infer on YOLOv9 model and detect tshirt in image"
@@ -138,8 +138,7 @@ demo = gr.Interface(inference,
                               gr.Slider(0, 1, 0.45, label="IoU Thresold"),
                               gr.Checkbox(label="Show False Detection"),
                               gr.Slider(5, 35, value=10, step=5, label="Number of False Detection")],
-                    outputs= [gr.Image(width=640, height=640, label="Output"), 
-                              gr.Plot(label="GradCAM"),
+                    outputs= [gr.Image(width=640, height=640, label="Output"),
                               gr.Plot(label="False Detection")],
                     title=title,
                     description=description,