FULL_COLOR_MAP = label_to_color_image(FULL_LABEL_MAP) def main_test(filepath): # 加载模型 modelname = "./datasets/quekou/export/frozen_inference_graph-22981.pb" MODEL = DeepLabModel(modelname) print("model loaded successfully!") filelist = os.listdir(filepath) for item in filelist: pr...
. TensorFlow的接口 在可视化下贴上caffemodel定义可以查看网络结构、以下是vgg16前几层的参考 层数越往上激活的图片就约简单、所以更容易被共享;拿用image Net训练好1000分类的网络参数可以认为前几层几乎都是训练好的、替换最后面fc层、换成目标的分类的个数 假如我们识别的是猫狗、那么fc就两个分类、最后一层需...
parser=argparse.ArgumentParser()#训练数据目录parser.add_argument('--train_dir', default='train')#测试目录parser.add_argument('--val_dir', default='val')#初始网络参数parser.add_argument('--model_path', default='vgg_16.ckpt', type=str) parser.add_argument('--batch_size', default=32, ty...
Finally, the feature map of the last layer is pooled by global average pooling to form a feature point. These feature points constitute the final feature vector, which is calculated in SoftMax [24]. The DenseNet model mainly realizes feature reuse through feature connection on the channel. ...
A pre-trained VGG-16 model [44] was employed, which resulted in an improved accuracy. As this was an anti-spoofing liveness detection issue with two classes (real and fake), the output of the final fully connected layer was adjusted from 2622 to 2, where 2622 was the number of facial...