chibohe
commented
3 years ago RuntimeError: Error(s) in loading state_dict for DAN: Missing key(s) in state_dict: "feature_extractor.conv1.weight", "feature_extractor.bn1.weight", "
DAN设置如下： TrainReader: dataloader: dataset,BatchBalancedDataset select_data: '/' batch_ratio: '1.0' total_data_usage_ratio: 1.0 padding: True augment: False batch_size: 64 shuffle: True num_workers: 0 lmdb_sets_dir: train_set###百度网盘下载的训练文件夹
EvalReader: dataloader: dataset,evaldataloader select_data: '/' batch_size: 2 padding: True shuffle: True num_workers: 0 lmdb_sets_dir: test_set ###百度网盘下载的测试文件夹
TestReader: dataloader: dataset,evaldataloader select_data: '/' batch_size: 64 padding: True shuffle: True num_workers: 0 lmdb_sets_dir:
Global: algorithm: DAN use_gpu: True gpu_num: '0' device: cuda:0 num_iters: 800000 highest_acc_save_type: False data_filtering_off: False resumed_optimizer: False batch_max_length: 50 print_batch_step: 10 save_model_dir: output/DAN eval_batch_step: 2000 image_shape: [1, 32, 256] character_type: ch loss_type: attn use_space_char: false character_dict_path: keys.txt seed: 1234 pretrain_weights: models/DAN.pth ####百度下载的模型文件 save_inference_dir: results infer_img: test_pic ###存放测试图片的文件夹
Architecture: function: networks.DAN,DAN compress_layer: False layers: [3, 4, 6, 6, 3]
CAM: depth: 8 num_channel: 512
Loss: function: loss,AttnLoss blank_idx: 0
Optimizer: function: adam base_lr: 0.001 momentum: 0.9 weight_decay: 1.0e-4 lr_decay_epoch: 10 max_epoch: 1000
pytorch版本1.3 python3.7
抱歉才看到，等我定位到问题回复你。
RuntimeError: Error(s) in loading state_dict for DAN: Missing key(s) in state_dict: "feature_extractor.conv1.weight", "feature_extractor.bn1.weight", "
DAN设置如下： TrainReader: dataloader: dataset,BatchBalancedDataset select_data: '/' batch_ratio: '1.0' total_data_usage_ratio: 1.0 padding: True augment: False batch_size: 64 shuffle: True num_workers: 0 lmdb_sets_dir: train_set###百度网盘下载的训练文件夹
EvalReader: dataloader: dataset,evaldataloader select_data: '/' batch_size: 2 padding: True shuffle: True num_workers: 0 lmdb_sets_dir: test_set ###百度网盘下载的测试文件夹
TestReader: dataloader: dataset,evaldataloader select_data: '/' batch_size: 64 padding: True shuffle: True num_workers: 0 lmdb_sets_dir:
Global: algorithm: DAN use_gpu: True gpu_num: '0' device: cuda:0 num_iters: 800000 highest_acc_save_type: False data_filtering_off: False resumed_optimizer: False batch_max_length: 50 print_batch_step: 10 save_model_dir: output/DAN eval_batch_step: 2000 image_shape: [1, 32, 256] character_type: ch loss_type: attn use_space_char: false character_dict_path: keys.txt seed: 1234 pretrain_weights: models/DAN.pth ####百度下载的模型文件 save_inference_dir: results infer_img: test_pic ###存放测试图片的文件夹
Architecture: function: networks.DAN,DAN compress_layer: False layers: [3, 4, 6, 6, 3]
CAM: depth: 8 num_channel: 512
Loss: function: loss,AttnLoss blank_idx: 0
Optimizer: function: adam base_lr: 0.001 momentum: 0.9 weight_decay: 1.0e-4 lr_decay_epoch: 10 max_epoch: 1000
pytorch版本1.3 python3.7