Comments (6)
UPDATE:
I have changed the pretrained field in model settings in configs/top_down/hrnet/coco/hrnet_w48_coco_384x288.py using the URL "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/hrnetv2_w48-d2186c55.pth", but the error still occurs.
I debugged the function checkpoint.py/load_state_dict, and the list missing_keys is now empty, but the unexpected_keys is still not empty.
Could you please help me explain this problem? Should I revert to an old version of the repos to get compatibility?
from mmpose.
We did not expect the user to load a COCO trained model as pretrained
. Currently, it only supports using imagenet-pretrained model.
We will fix this part today.
from mmpose.
First, did you modify the model structure?
Second, in the second line of configs/top_down/hrnet/coco/hrnet_w48_coco_384x288.py, you may use load_from = hrnet_w48_coco_384x288-314c8528_20200708.pth
and set pretrained=None
in line 42
from mmpose.
UPDATE:
I have changed the pretrained field in model settings in configs/top_down/hrnet/coco/hrnet_w48_coco_384x288.py using the URL "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/hrnetv2_w48-d2186c55.pth", but the error still occurs.
I debugged the function checkpoint.py/load_state_dict, and the list missing_keys is now empty, but the unexpected_keys is still not empty.
Could you please help me explain this problem? Should I revert to an old version of the repos to get compatibility?
Don't worry, it is normal to have unexpected_keys
for HRNet. Please just ignore it.
from mmpose.
Fantastic!
Thank you very much for your support.
When I set pretrained to None, and set load_from to point to "hrnet_w48_coco_384x288-314c8528_20200708.pth". The pre-trained model is smoothly. missing_keys and unexpected_keys are empty now.
I hope that you add pre-training from COCO soon. It would be tremendously helpful if we can fine-tune from pre-trained model on COCO.
Again, thank you for your valuable works. The code is very well-organized and clean, the supported models are diverse, the model zoo is awesome. This is the best pose open-source project I have came across.
Best.
from mmpose.
PS. I don't change the model architecture. Just the path in the data-settings, and data_cfg.use_gt_bbox to True because PoseTrack doesn't have bb detections.
from mmpose.
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