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Siyeong-Lee/CAM_pytorch.py

Created November 15, 2019 07:17
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CAM_pytorch.py
params = list(net.parameters())
# get only weight from last layer(linear)
weight_softmax = np.squeeze(params[-2].cpu().data.numpy())
def returnCAM(feature_conv, weight_softmax, class_idx):
size_upsample = (128, 128)
bz, nc, h, w = feature_conv.shape
output_cam = []
for idx in class_idx:
cam = weight_softmax[class_idx].dot(feature_conv.reshape( (nc, h*w)))
cam = cam.reshape(h, w)
cam = cam - np.min(cam)
cam_img = cam/np.max(cam)
cam_img = np.uint8(255 * cam_img)
output_cam.append(cv2.resize(cam_img, size_upsample))
return output_cam
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