增加Grad-CAM++

Author: yizt

interpretability/grad_cam.py

@@ -78,3 +78,45 @@ def __call__(self, inputs, index):
         # resize to 224*224
         cam = cv2.resize(cam, (224, 224))
         return cam
+
+
+class GradCamPlusPlus(GradCAM):
+    def __init__(self, net, layer_name):
+        super(GradCamPlusPlus, self).__init__(net, layer_name)
+
+    def __call__(self, inputs, index):
+        """
+
+        :param inputs: [1,3,H,W]
+        :param index: class id
+        :return:
+        """
+        self.net.zero_grad()
+        output = self.net(inputs)  # [1,num_classes]
+        if index is None:
+            index = np.argmax(output.cpu().data.numpy())
+        target = output[0][index]
+        target.backward()
+
+        gradient = self.gradient[0].cpu().data.numpy()  # [C,H,W]
+        gradient = np.maximum(gradient, 0.)  # ReLU
+        indicate = np.where(gradient > 0, 1., 0.)  # 示性函数
+        norm_factor = np.sum(gradient, axis=(1, 2))  # [C]归一化
+        for i in range(len(norm_factor)):
+            norm_factor[i] = 1. / norm_factor[i] if norm_factor[i] > 0. else 0.  # 避免除零
+        alpha = indicate * norm_factor[:, np.newaxis, np.newaxis]  # [C,H,W]
+
+        weight = np.sum(gradient * alpha, axis=(1, 2))  # [C]  alpha*ReLU(gradient)
+
+        feature = self.feature[0].cpu().data.numpy()  # [C,H,W]
+
+        cam = feature * weight[:, np.newaxis, np.newaxis]  # [C,H,W]
+        cam = np.sum(cam, axis=0)  # [H,W]
+        # cam = np.maximum(cam, 0)  # ReLU
+
+        # 数值归一化
+        cam -= np.min(cam)
+        cam /= np.max(cam)
+        # resize to 224*224
+        cam = cv2.resize(cam, (224, 224))
+        return cam

main.py

@@ -16,7 +16,7 @@
 import argparse
 from skimage import io
 import cv2
-from interpretability.grad_cam import GradCAM
+from interpretability.grad_cam import GradCAM, GradCamPlusPlus
 from interpretability.guided_back_propagation import GuidedBackPropagation
 
 
@@ -150,6 +150,12 @@ def main(args):
     mask = grad_cam(inputs, args.class_id)  # cam mask
     image_dict['cam'], image_dict['heatmap'] = gen_cam(img, mask)
     grad_cam.remove_handlers()
+    # Grad-CAM++
+    grad_cam_plus_plus = GradCamPlusPlus(net, layer_name)
+    mask_plus_plus = grad_cam_plus_plus(inputs, args.class_id)  # cam mask
+    image_dict['cam++'], image_dict['heatmap++'] = gen_cam(img, mask_plus_plus)
+    grad_cam_plus_plus.remove_handlers()
+
     # GuidedBackPropagation
     gbp = GuidedBackPropagation(net)
     inputs.grad.zero_()  # 梯度置零