Comments (4)
@wsh-nie We included pretrained model link in readme
from video-swin-transformer.
You can find the pretrained models in the column "model" for each dataset, under https://github.com/SwinTransformer/Video-Swin-Transformer.
E.g.
from video-swin-transformer.
The Baidu shows incorrect credentials for the code swim
.
from video-swin-transformer.
Hi, are there any mismatches occurring? I find that when I set it as below I can inference normally
config_file = '/home/haylee/Video-Swin-Transformer/mmaction2/tsn_imagenet-pretrained-r50_8xb32-1x1x8-100e_kinetics400-rgb.py'
checkpoint_file = '/home/haylee/Video-Swin-Transformer/mmaction2/tsn_imagenet-pretrained-r50_8xb32-1x1x8-100e_kinetics400-rgb_20220906-2692d16c.pth'
But setting it to the following reasoning reports an error
config_file = '/home/haylee/Video-Swin-Transformer/configs/recognition/tsn/tsn_r50_video_inference_1x1x3_100e_kinetics400_rgb.py'
checkpoint_file = '/home/haylee/Video-Swin-Transformer/checkpoints/tsn_r50_1x1x3_100e_kinetics400_rgb_20200614-e508be42.pth'
Error as below:
Exception has occurred: TypeError
class 'Normalize' in mmcv/transforms/processing.py: Normalize.__init__() got an unexpected keyword argument 'to_bgr'
TypeError: Normalize.__init__() got an unexpected keyword argument 'to_bgr'
During handling of the above exception, another exception occurred:
File "/home/haylee/Video-Swin-Transformer/mmaction2/mmaction/apis/inference.py", line 79, in inference_recognizer
test_pipeline = Compose(test_pipeline_cfg)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/haylee/Video-Swin-Transformer/demo/haylee_demo.py", line 12, in <module>
pred_result = inference_recognizer(model, video_file)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: class 'Normalize' in mmcv/transforms/processing.py: Normalize.__init__() got an unexpected keyword argument 'to_bgr'
from video-swin-transformer.
Related Issues (20)
- Embeddings
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- is there a priority between drop out and patch norm?
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- How much video memory does a single GPU need to run SSV2? I use the 16G ,then it prompt CUDA out of memory
- Pretraining for SSv2
- Code for duplicate the weights pretrained on Imagenet
- Welcome update to OpenMMLab 2.0
- Pretrained Swin-L on Kinects 600 dataset
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- Missing keys in source state_dict: backbone.patch_embed.proj.weight, backbone.patch_embed.proj.bias, and so on.
- size mismatch for cls_head.fc_cls.weight: copying a param with shape torch.Size([400, 1024]) from checkpoint, the shape in current model is torch.Size([101, 1024]).
- How to solve this: AttributeError: 'Recognizer2D' object has no attribute 'demo/label_map_k400'
- TypeError: 'str' object is not callable HOT 2
- IncompatibleKeys appear when I loaded the pretrained 2d model
- Steps to convert mmaction's video-swin-transformer to ONNX successfully HOT 4
- Model weights for Swin-L HOT 1
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from video-swin-transformer.