Comments (4)
What exactly in the ReadMe points toward an incorrect implementation of rotation and shearing?
from dataaugmentationforobjectdetection.
The bounding boxes in your examples are simply wrong after shearing and rotation.
from dataaugmentationforobjectdetection.
@ogencoglu This can happen if you are using Python 2
In data_aug.py your scale factor should be float, but in Python 2 they will be treated as Integers
Just change the scale_factor code in data_aug.py as follows:'
Instead of
scale_factor_x = img.shape[1] / w
scale_factor_y = img.shape[0] / h
Do this
scale_factor_x = 1.0* img.shape[1] / w
scale_factor_y = 1.0*img.shape[0] / h
from dataaugmentationforobjectdetection.
I can also confirm that shear and rotation don't work properly on python 3. I think the problem is due to resize to fit the original image dimensions
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Related Issues (20)
- Crop Video frames HOT 1
- How To Contribute HOT 1
- Please provide licence details
- I encountered a problem about rgb HOT 1
- About black region left in rotation/translation
- Some transforms could cut boxes or even delete them
- Typo Error: 'Tranformed`, should be Transformed
- Difference between resizing and scaling? HOT 2
- will i get bounding box for each augmentation ?
- Convert txt to pkl HOT 2
- IndexError: index 0 is out of bounds for axis 0 with size 0 HOT 2
- Random copy-paste
- Rotation scaling difference HOT 1
- RandomHSV function
- Will there be a new version for polygon bounding boxes ?
- Numpy divide error in RandomRotate and RandomShear HOT 1
- Error while using sequence HOT 1
- Hope to add Crop or RandomCrop operation
- Bug in clip_box function HOT 1
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