Update app.py

app.py

@@ -20,6 +20,7 @@ import cv2
 from pytorch_grad_cam import EigenCAM
 from pytorch_grad_cam.utils.model_targets import FasterRCNNBoxScoreTarget
 from pytorch_grad_cam.utils.image import show_cam_on_image
+from pytorch_grad_cam.utils.image import show_cam_on_image, scale_cam_image
 
 
 # my files
@@ -145,12 +146,20 @@ with gr.Blocks() as demo:
         objs = [b[1] for b in nms_boxes_output[0]]
         bbox_coord = [b[2:] for b in nms_boxes_output[0]]
         targets = [FasterRCNNBoxScoreTarget(objs, bbox_coord)]
-
+        
         target_layers = [inference_model.model]
         cam = EigenCAM(inference_model, target_layers, use_cuda=False,reshape_transform=yolov3_reshape_transform)
         grayscale_cam = cam(input_tensor = input_img_tensor, targets= targets)
         grayscale_cam = grayscale_cam[0, :]
-        visualization = show_cam_on_image(input_img_copy, grayscale_cam, use_rgb=False, image_weight=gradcam_opa)
+        
+        renormalized_cam = np.zeros(grayscale_cam.shape, dtype=np.float32)
+        new_bboxes = [a[0] for a in sections]
+          
+        for x1, y1, x2, y2 in new_bboxes:
+            renormalized_cam[y1:y2, x1:x2] = scale_cam_image(grayscale_cam[y1:y2, x1:x2].copy())
+
+        renormalized_cam = scale_cam_image(renormalized_cam) 
+        visualization = show_cam_on_image(input_img_copy, renormalized_cam, use_rgb=False, image_weight=gradcam_opa)
 
         return (visualization,sections)
       else: