训练后的模型使用报错

[wy353208214]

1. 模型配置

{
  "lr": 0.1,
  "milestones": [10, 15, 22],
  "gamma": 0.1,
  "epochs": 25,
  "momentum": 0.9,
  "batch_size": 1024,
  "num_classes": 3,
  "input_channel": 3,
  "embedding_size": 128,
  "train_root_path": "./datasets/rgb_image",
  "snapshot_dir_path": "./saved_logs/snapshot",
  "log_path": "./saved_logs/jobs/Anti_Spoofing_2.7_80x80/Oct18_11-21-58 ",
  "board_loss_every": 10,
  "save_every": 30,
  "devices": [0],
  "patch_info": "2.7_80x80",
  "input_size": [80, 80],
  "kernel_size": [5, 5],
  "device": "cpu",
  "ft_height": 10,
  "ft_width": 10,
  "model_path": "./saved_logs/snapshot/Anti_Spoofing_2.7_80x80",
  "job_name": "Anti_Spoofing_2.7_80x80"
}

生成的模型文件：

2. 这里的模型需要改文件名吗，替换之后报如下错误：

Traceback (most recent call last):
  File "/Users/steven/Dev_Project/Python/Silent-Face-Anti-Spoofing/test.py", line 111, in <module>
    test(args.image_name, args.model_dir, args.device_id)
  File "/Users/steven/Dev_Project/Python/Silent-Face-Anti-Spoofing/test.py", line 61, in test
    prediction += model_test.predict(img, os.path.join(model_dir, model_name))
  File "/Users/steven/Dev_Project/Python/Silent-Face-Anti-Spoofing/src/anti_spoof_predict.py", line 88, in predict
    self._load_model(model_path)
  File "/Users/steven/Dev_Project/Python/Silent-Face-Anti-Spoofing/src/anti_spoof_predict.py", line 77, in _load_model
    self.model.load_state_dict(new_state_dict)
  File "/usr/local/lib/python3.9/site-packages/torch/nn/modules/module.py", line 2041, in load_state_dict
    raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for MiniFASNet:
        Missing key(s) in state_dict: "conv1.conv.weight", "conv1.bn.weight", "conv1.bn.bias", "conv1.bn.running_mean", "conv1.bn.running_var", "conv1.prelu.weight", "conv2_dw.conv.weight", "conv2_dw.bn.weight", "conv2_dw.bn.bias", "conv2_dw.bn.running_mean", "conv2_dw.bn.running_var", "conv2_dw.prelu.weight", "conv_23.conv.conv.weight", "conv_23.conv.bn.weight", "conv_23.conv.bn.bias", "conv_23.conv.bn.running_mean", "conv_23.conv.bn.running_var", "conv_23.conv.prelu.weight", "conv_23.conv_dw.conv.weight", "conv_23.conv_dw.bn.weight", "conv_23.conv_dw.bn.bias", "conv_23.conv_dw.bn.running_mean", "conv_23.conv_dw.bn.running_var", "conv_23.conv_dw.prelu.weight", "conv_23.project.conv.weight", "conv_23.project.bn.weight", "conv_23.project.bn.bias", "conv_23.project.bn.running_mean", "conv_23.project.bn.running_var", "conv_3.model.0.conv.conv.weight", "conv_3.model.0.conv.bn.weight", "conv_3.model.0.conv.bn.bias", "conv_3.model.0.conv.bn.running_mean", "conv_3.model.0.conv.bn.running_var", "conv_3.model.0.conv.prelu.weight", "conv_3.model.0.conv_dw.conv.weight", "conv_3.model.0.conv_dw.bn.weight", "conv_3.model.0.conv_dw.bn.bias", "conv_3.model.0.conv_dw.bn.running_mean", "conv_3.model.0.conv_dw.bn.running_var", "conv_3.model.0.conv_dw.prelu.weight",

[wy353208214]

参考这里
#43

[wy353208214]

训练后，生成的多个model，选用哪个？