Comments (7)
Sorry, I just noticed that I should set polygon=True. Now, the training program starts running.
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Why is polygon
set to False
by default if the training code will fail? I just ran into this problem because I'm attempting to train the model on a custom dataset.
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@seangtkelley SSD and TextBoxes work with axis aligned bounding boxes (polygon=False
), but SegLink and TextBoxes++ work with oriented bounding boxes and require a different representation (polygon=True
). It is probably not the most elegant solution and it may depend on your interpretation of 'default'... An alternative could be to write a separate class for the polygon case.
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I run data_synthtext.py script and the error I got is:
TypeError: 'NoneType' object is not iterable
Do you meet this error and do you know how to fix?
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Have you placed the SynthText dataset at the right location? For instance ./data/SynthText/gt.mat
...
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@mvoelk Ohh I could not find the place to get SyntText dataset which is gt.mat or do I need to run another script to create that file? (If yes, what script plz?)
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I made it, thanks
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Related Issues (20)
- TBPP model arbitrary input shape HOT 1
- encode/decode error for tbpp
- DSOD Low mAP HOT 1
- Target length zero error
- about environment set (tf version?) HOT 2
- SL_end2end_predict.ipynb: Model dimensions don't match that in weights file. HOT 4
- Request to add .pkl files to repo HOT 4
- DSODSL Output tensor format HOT 1
- CRNN output format HOT 1
- How to convert to tflite?
- SL_end2end_predict.ipynb fails on converting to .py with necessary modifications. HOT 9
- Light architectures for object detection HOT 5
- fit_generator for ssd training & Check loss during training HOT 1
- training with own dataset resize issue HOT 1
- While training, got <UnknownError: AttributeError: 'NoneType' object has no attribute 'shape'> HOT 1
- links to download models not working HOT 2
- TypeError: map() got an unexpected keyword argument 'deterministic' error HOT 3
- How to modify the size of anchor? HOT 4
- Metrics issue ? HOT 4
- Problem during with Crowd Human dataset HOT 1
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