json

[chuanchengh]

data = dict( samples_per_gpu=2, workers_per_gpu=2, train=dict( pipeline=train_pipeline, classes = classes, ann_file='path/of/annotations/json'), val=dict( classes = classes, ann_file='path/of/annotations/json'), test=dict( classes = classes, ann_file='path/of/annotations/json'))

Hello, I would like to ask how JSON needs to be configured,I changed to full Box 10shot Frisbee The error has been reported continuously since trainval.json, as follows：

`2023-10-29 15:52:05,608 - mmdet - INFO - load model from: pre/mae_pretrain_vit_base_full.pth 2023-10-29 15:52:05,954 - mmdet - WARNING - The model and loaded state dict do not match exactly

unexpected key in source state_dict: mask_token, decoder_pos_embed, norm.weight, norm.bias, decoder_embed.weight, decoder_embed.bias, decoder_blocks.0.norm1.weight, decoder_blocks.0.norm1.bias, decoder_blocks.0.attn.qkv.weight, decoder_blocks.0.attn.qkv.bias, decoder_blocks.0.attn.proj.weight, decoder_blocks.0.attn.proj.bias, decoder_blocks.0.norm2.weight, decoder_blocks.0.norm2.bias, decoder_blocks.0.mlp.fc1.weight, decoder_blocks.0.mlp.fc1.bias, decoder_blocks.0.mlp.fc2.weight, decoder_blocks.0.mlp.fc2.bias, decoder_blocks.1.norm1.weight, decoder_blocks.1.norm1.bias, decoder_blocks.1.attn.qkv.weight, decoder_blocks.1.attn.qkv.bias, decoder_blocks.1.attn.proj.weight, decoder_blocks.1.attn.proj.bias, decoder_blocks.1.norm2.weight, decoder_blocks.1.norm2.bias, decoder_blocks.1.mlp.fc1.weight, decoder_blocks.1.mlp.fc1.bias, decoder_blocks.1.mlp.fc2.weight, decoder_blocks.1.mlp.fc2.bias, decoder_blocks.2.norm1.weight, decoder_blocks.2.norm1.bias, decoder_blocks.2.attn.qkv.weight, decoder_blocks.2.attn.qkv.bias, decoder_blocks.2.attn.proj.weight, decoder_blocks.2.attn.proj.bias, decoder_blocks.2.norm2.weight, decoder_blocks.2.norm2.bias, decoder_blocks.2.mlp.fc1.weight, decoder_blocks.2.mlp.fc1.bias, decoder_blocks.2.mlp.fc2.weight, decoder_blocks.2.mlp.fc2.bias, decoder_blocks.3.norm1.weight, decoder_blocks.3.norm1.bias, decoder_blocks.3.attn.qkv.weight, decoder_blocks.3.attn.qkv.bias, decoder_blocks.3.attn.proj.weight, decoder_blocks.3.attn.proj.bias, decoder_blocks.3.norm2.weight, decoder_blocks.3.norm2.bias, decoder_blocks.3.mlp.fc1.weight, decoder_blocks.3.mlp.fc1.bias, decoder_blocks.3.mlp.fc2.weight, decoder_blocks.3.mlp.fc2.bias, decoder_blocks.4.norm1.weight, decoder_blocks.4.norm1.bias, decoder_blocks.4.attn.qkv.weight, decoder_blocks.4.attn.qkv.bias, decoder_blocks.4.attn.proj.weight, decoder_blocks.4.attn.proj.bias, decoder_blocks.4.norm2.weight, decoder_blocks.4.norm2.bias, decoder_blocks.4.mlp.fc1.weight, decoder_blocks.4.mlp.fc1.bias, decoder_blocks.4.mlp.fc2.weight, decoder_blocks.4.mlp.fc2.bias, decoder_blocks.5.norm1.weight, decoder_blocks.5.norm1.bias, decoder_blocks.5.attn.qkv.weight, decoder_blocks.5.attn.qkv.bias, decoder_blocks.5.attn.proj.weight, decoder_blocks.5.attn.proj.bias, decoder_blocks.5.norm2.weight, decoder_blocks.5.norm2.bias, decoder_blocks.5.mlp.fc1.weight, decoder_blocks.5.mlp.fc1.bias, decoder_blocks.5.mlp.fc2.weight, decoder_blocks.5.mlp.fc2.bias, decoder_blocks.6.norm1.weight, decoder_blocks.6.norm1.bias, decoder_blocks.6.attn.qkv.weight, decoder_blocks.6.attn.qkv.bias, decoder_blocks.6.attn.proj.weight, decoder_blocks.6.attn.proj.bias, decoder_blocks.6.norm2.weight, decoder_blocks.6.norm2.bias, decoder_blocks.6.mlp.fc1.weight, decoder_blocks.6.mlp.fc1.bias, decoder_blocks.6.mlp.fc2.weight, decoder_blocks.6.mlp.fc2.bias, decoder_blocks.7.norm1.weight, decoder_blocks.7.norm1.bias, decoder_blocks.7.attn.qkv.weight, decoder_blocks.7.attn.qkv.bias, decoder_blocks.7.attn.proj.weight, decoder_blocks.7.attn.proj.bias, decoder_blocks.7.norm2.weight, decoder_blocks.7.norm2.bias, decoder_blocks.7.mlp.fc1.weight, decoder_blocks.7.mlp.fc1.bias, decoder_blocks.7.mlp.fc2.weight, decoder_blocks.7.mlp.fc2.bias, decoder_norm.weight, decoder_norm.bias, decoder_pred.weight, decoder_pred.bias

missing keys in source state_dict: fpn1.0.weight, fpn1.0.bias, fpn1.1.weight, fpn1.1.bias, fpn1.1.running_mean, fpn1.1.running_var, fpn1.3.weight, fpn1.3.bias, fpn2.0.weight, fpn2.0.bias

2023-10-29 15:52:05,979 - mmdet - INFO - loading checkpoint for <class 'mmdet.models.roi_heads.bbox_heads.mae_bbox_head.MAEBBoxHead'> Use load_from_local loader 2023-10-29 15:52:06,150 - mmdet - WARNING - The model and loaded state dict do not match exactly

unexpected key in source state_dict: cls_token, mask_token, decoder_norm.weight, decoder_norm.bias, decoder_pred.weight, decoder_pred.bias

missing keys in source state_dict: fc_cls.weight, fc_cls.bias, fc_reg.weight, fc_reg.bias, decoder_box_norm.weight, decoder_box_norm.bias

Use load_from_local loader Traceback (most recent call last): File "./tools/test.py", line 220, in main() File "./tools/test.py", line 177, in main checkpoint = load_checkpoint(model, args.checkpoint, map_location='cpu') File "/root/miniconda3/envs/open-mmlab/lib/python3.7/site-packages/mmcv/runner/checkpoint.py", line 513, in load_checkpoint checkpoint = _load_checkpoint(filename, map_location, logger) File "/root/miniconda3/envs/open-mmlab/lib/python3.7/site-packages/mmcv/runner/checkpoint.py", line 451, in _load_checkpoint return CheckpointLoader.load_checkpoint(filename, map_location, logger) File "/root/miniconda3/envs/open-mmlab/lib/python3.7/site-packages/mmcv/runner/checkpoint.py", line 244, in load_checkpoint return checkpoint_loader(filename, map_location) File "/root/miniconda3/envs/open-mmlab/lib/python3.7/site-packages/mmcv/runner/checkpoint.py", line 261, in load_from_local checkpoint = torch.load(filename, map_location=map_location) File "/root/miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/serialization.py", line 585, in load return _legacy_load(opened_file, map_location, pickle_module, pickle_load_args) File "/root/miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/serialization.py", line 755, in _legacy_load magic_number = pickle_module.load(f, pickle_load_args) _pickle.UnpicklingError: invalid load key, '\xe2'. Traceback (most recent call last): File "/root/miniconda3/envs/open-mmlab/lib/python3.7/runpy.py", line 193, in _run_module_as_main "main", mod_spec) File "/root/miniconda3/envs/open-mmlab/lib/python3.7/runpy.py", line 85, in _run_code exec(code, run_globals) File "/root/miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/distributed/launch.py", line 261, in main() File "/root/miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/distributed/launch.py", line 257, in main cmd=cmd) subprocess.CalledProcessError: Command '['/root/miniconda3/envs/open-mmlab/bin/python', '-u', './tools/test.py', '--local_rank=0', 'configs/imted/few_shot/imted_faster_rcnn_vit_base_2x_finetuning_10shot_coco.py', 'work_dirs/imted_faster_rcnn_vit_base_2x_finetuning_10shot_coco/mae_vit_small_800e.pth', '--launcher', 'pytorch', '--eval', 'bbox']' returned non-zero exit status 1.`

[LiewFeng]

Hi. Sorry for the late reply. It seems you use the wrong checkpoint. You can use this checkpoint for evaluation. For the data preparation, please refer to this