Activity

1. xuv commented on Jul 19, 2019

   

   xuv

   on Jul 19, 2019

   Member

   More actions

   @octopousprime Thanks for reaching out and submitting this. It sounds related to #33.

   Will see what we can do about this, but it sounds like a bug.
2. octopousprime commented on Jul 24, 2019

   

   octopousprime

   on Jul 24, 2019

   Author

   More actions

   Thanks! I appreciate if you can inform me when would you expect to investigate and resolve this bug; as I have an ongoing research that depends on the accuracy of the results.
3. microcosm commented on Feb 20, 2020

   

   microcosm

   on Feb 20, 2020

   Contributor

   More actions

   This doesn't look so similar to issue #33, because that issue describes inaccurate results. @octopousprime's issue describes a completely wrong result - 100%

   However, this issue has been stale a while. I'm going to close it for now as we are trying to get a handle on the most crucial issues. @octopousprime please can you re-open this if you are still having a problem and we'll find someone to take a look at it - thanks
4. microcosm

   closed this as completedon Feb 20, 2020
5. gri1 commented on Mar 28, 2020

   

   gri1

   on Mar 28, 2020

   Last edited by gri1

   More actions

   I'm having the same issue, @microcosm. If I just change fermodel_example.py to use all 7 emotions:

   target_emotions = ['calm', 'anger', 'happiness', 'surprise', 'disgust', 'fear', 'sadness']
   

   Then I get the following output:

   Predicting on happy image...
   anger: 100.0%
   disgust: 0.0%
   fear: 0.0%
   happiness: 0.0%
   sadness: 0.0%
   surprise: 0.0%
   calm: 0.0%
   Predicting on disgust image...
   anger: 100.0%
   disgust: 0.0%
   fear: 0.0%
   happiness: 0.0%
   sadness: 0.0%
   surprise: 0.0%
   calm: 0.0%
   Predicting on anger image...
   anger: 98.3%
   disgust: 0.0%
   fear: 1.0%
   happiness: 0.7%
   sadness: 0.0%
   surprise: 0.0%
   calm: 0.0%
   

   Therefore it seems this model can only predict anger.
6. microcosm

   reopened this on Mar 30, 2020
7. Richardng12 commented on Aug 29, 2020

   

   Richardng12

   on Aug 29, 2020

   More actions

   Leaving a comment to say I have the same problem.

   Trained a model on FERPlus dataset using Conv_dropout_model.
   Relevant model plus emotion_map was exported using the methods in neuralnets

   When predicting using fer_model_example, all images return 100% on one of the emotions. E.g anger -100%
   Either the model trained is incorrect, or the method used to predict is incorrect - not quite sure which one