Comments (2)
Do you mean that the network predicts every image in the test set as neutral?
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I do have the same problem, I replace the FER 2013 emotion label with the mostly marked label in FER+, then trained that dataset with MobileNet. I get the model test accuracy with ~80% .
Then I randomly choose multi web downloaded images to run the forward progress. I get most results of neutral while some of the images should be happiness or sad
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Related Issues (16)
- License: commercial use?
- Distorting the image on new images to predict HOT 3
- Can we use cntk-gpu instead of cntk package?
- Can every one share your results?
- Test accuracy on Multi-label
- errors in the new csv file? HOT 1
- What's the meaning of "NF","unknown" HOT 1
- This repo is missing important files HOT 1
- Size of images HOT 1
- Same number of votes on two emotions HOT 1
- How to match the file fer2013new.csv and fer2013 HOT 1
- Where can download FER dataset?
- There are some error in rect_util.py
- the loss function for multi label learning
- the environment of code
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