Comments (3)
Hi Gautam, thanks for solving this issue so quickly.
You are right I had serveral model files and probably confused them.
Thanks again for the great work you have done!
from teachablemachine-community.
After reading https://github.com/googlecreativelab/teachablemachine-community/issues/3 I tried to normalize between -1 and 1, which improves the classification accuracy but it does not fix the problem entirely. The classfier is still wrong on half of the samples of the "bad" class.
Changed line of code:
normalized_image_array = (image_array.astype(np.float32) / 127.0) -1
from teachablemachine-community.
Hi! I went through your Colab, and noticed the same classification performance issue.
However, I trained a new model in teachable machine with images in the training folder you provided, re-exported to keras, and tried the test samples again with the corrected normalization between -1 and 1. The performance was accurate. I suspect the keras model loaded into the Colab isn't the most up to date with the one trained in TM.
I've modified the drive link in a copy of the Colab with my newly exported keras model here:
My TM model is here:
The normalization is updated in the snippet: #58
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