Comments (5)
@mdbloice i did not forget you, i am at home in quarantene and will be back on monday to test it.
from augmentor.
Hi @tanzerlana yes that's a current limitation, patches need to be >0.1 and <1.0...
How small would you need your patches to be?
from augmentor.
Hello! thanks for your kind answer..
for my application I would need them to be between 0.01 and 0.1 as I am adding multiple labels it fills up too much and does not simulate our real world scenario
Thank you!
from augmentor.
Hi again @tanzerlana - if you update Augmentor using pip you should be able to now use values between 0.01 and 1.
Let me know if it's now working as you'd expect!
from augmentor.
from augmentor.
Related Issues (20)
- moudle 'Augmentor' has no attribute 'Pipeline'
- int() argument must be a string, a bytes-like object or a number, not 'Image' HOT 4
- why random_erasing sometimes cause error, but sometimes not. HOT 1
- OSError: cannot write mode RGBA as JPEG HOT 2
- What augments should you use?
- label interpolate issue
- p.ground_truth not work for p.add_operation HOT 3
- Not cropping skewed image to original image size HOT 1
- Question - Does it updated the labels too? HOT 3
- Use for Semantic Segmentation HOT 4
- Output dataset format Labelme JSON
- ValueError: image has wrong mode HOT 1
- ZeroDivisionError: float division by zero while performing augmentor.sample(num_samples)
- DataPipeline使用sample的时候会报错
- Incompatible with numpy >= 1.20 due to use of type aliases. HOT 1
- Rotation degrees are opposite. HOT 3
- Project dependencies may have API risk issues
- fail to build augmentor 0.2.11 due to a minor typo HOT 1
- Where is the auto-generated documentation?
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from augmentor.