Open markkdev opened 4 years ago
I also get this error anytime I run attr predict with roi
python3 ./demo/test_predictor.py --input demo/attr_pred_demo1.jpg
Traceback (most recent call last):
File "./demo/test_predictor.py", line 57, in
For my experience,I remove the mmfashion package by pip uninstall mmfashion and indicate the path of mmfashion by adding the following code at test_predictor.py
import sys
sys.path.append("/home/Source/mmfashion")
still fails at
mmfashion/models/predictor/base.py", line 29, in forward_test return self.simple_test(img[0], landmark[0]) TypeError: 'NoneType' object is not subscriptable
Thanks for the suggestion though
Based on your error information, it seems the model uses "roi-pooling" instead of "global pooling", because of "landmark[0]". Would you plz check which config file you used when testing?
In
Based on your error information, it seems the model uses "roi-pooling" instead of "global pooling", because of "landmark[0]". Would you plz check which config file you used when testing?
Do you mean it does not support roi resnet in test_predictor.py?
maybe it need a input landmark instead of None, but i dont't know how to generate the landmark of single image
@veralauee When I use checkpoint: 'checkpoint/Predict/resnet/roi/latest.pth' config: 'configs/attribute_predict/roi_predictor_resnet_attr.py' Thats when I got the NoneType error.
When I use checkpoint: 'checkpoint/Predict/resnet/global/latest.pth' config: 'configs/attribute_predict/global_predictor_resnet_attr.py' I get the same predictions for any images.
Did you resolve this issue?
@markkdev How did you resolve it? I encountered the same. Firstly, I use vgg16 for global and get similar results regardless of images. Then I switch to ROI for landmark and get same error thrown.
Never found a solution to this issue.
Thanks for the feedback. We will update the attribute prediction model soon.
Yeah, same issue. Would be great to know if there is a timeline for the prediction model to be updated
also getting the (same) wrong predictions on my own held out images.
https://github.com/open-mmlab/mmfashion/issues/32#issuecomment-582954019
I got the same problems. @markkdev did you find any solutions?
Same issues, getting the same results for all external images, is there any transform that needs to be applied to the image perhaps?
wrong predictions all the time :(
We just updated the attribute-prediction tasks. Please use
python test tools/test_cate_attr_predictor.py \ --config configs/category_attribute_predict/roi_predictor_vgg.py \ --checkpoint checkpoint/CateAttrPredict/vgg/roi/latest.pth
Since the prior dataset just implements the coarse labeling, that leads to the wrong prediction. We relabeled a more compact and accurate dataset for attribute prediction.
Hi,
I followed the process of setup, downloaded checkpoints for vgg16.pth, latest.pth for global attr.
Anytime I run the demo I get the same output no matter the image.
[ Top3 Prediction ] print lace knit [ Top5 Prediction ] print lace knit sleeve maxi [ Top10 Prediction ] print lace knit sleeve maxi shirt denim chiffon floral striped
Looking for a guide on what I could be doing wrong?
Appreciate it and thanks for you work.