Generation Mode error

[MiguelAngeloMartinsRibeiro]

@joheras Hi, first of all thank you for your time

I'm getting an error on the collar notebook. When I change the generation mode from linear to sequential it gives me an error

PROBLEM = "instance_segmentation"
ANNOTATION_MODE = "coco"
INPUT_PATH = "Images_for_thesisCOCO"
GENERATION_MODE = "sequential"
OUTPUT_MODE = "coco"
OUTPUT_PATH= "output/"
!mkdir output

augmentor = createAugmentor(PROBLEM,ANNOTATION_MODE,OUTPUT_MODE,GENERATION_MODE,INPUT_PATH,{"outputPath":OUTPUT_PATH})

---

KeyError Traceback (most recent call last)
in ()
----> 1 augmentor = createAugmentor(PROBLEM,ANNOTATION_MODE,OUTPUT_MODE,GENERATION_MODE,INPUT_PATH,{"outputPath":OUTPUT_PATH})

/usr/local/lib/python3.7/dist-packages/clodsa/augmentors/augmentorFactory.py in createAugmentor(problem, annotationmode, outputmode, generationmode, inputPath, parameters)
3
4 def createAugmentor(problem,annotationmode,outputmode,generationmode,inputPath,parameters):
----> 5 Augmentor = Augmentors[problem][annotationmode][outputmode][generationmode]
6 if Augmentor is None:
7 raise ValueError("These parameters are not currently supported")

KeyError: 'sequential'

[joheras]

Thanks for the report. I have uploaded a new version of Clodsa that fixes the problem. Let me know if you have any further issues. Best, Jónathan El vie, 8 oct 2021 a las 1:00, MiguelAngeloMartinsRibeiro (< ***@***.***>) escribió:

…

@joheras <https://github.com/joheras> Hi, first of all thank you for your time I'm getting an error on the collar notebook. When I change the generation mode from linear to sequential it gives me an error PROBLEM = "instance_segmentation" ANNOTATION_MODE = "coco" INPUT_PATH = "Images_for_thesisCOCO" GENERATION_MODE = "sequential" OUTPUT_MODE = "coco" OUTPUT_PATH= "output/" !mkdir output augmentor = createAugmentor(PROBLEM,ANNOTATION_MODE,OUTPUT_MODE,GENERATION_MODE,INPUT_PATH,{"outputPath":OUTPUT_PATH}) ------------------------------ KeyError Traceback (most recent call last) in () ----> 1 augmentor = createAugmentor(PROBLEM,ANNOTATION_MODE,OUTPUT_MODE,GENERATION_MODE,INPUT_PATH,{"outputPath":OUTPUT_PATH}) /usr/local/lib/python3.7/dist-packages/clodsa/augmentors/augmentorFactory.py in createAugmentor(problem, annotationmode, outputmode, generationmode, inputPath, parameters) 3 4 def createAugmentor(problem,annotationmode,outputmode,generationmode,inputPath,parameters): ----> 5 Augmentor = Augmentors[problem][annotationmode][outputmode][generationmode] 6 if Augmentor is None: 7 raise ValueError("These parameters are not currently supported") KeyError: 'sequential' — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#48>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ABJRAG66XSXNHJCR2QYGPH3UFYQ7HANCNFSM5FSK7C5Q> . Triage notifications on the go with GitHub Mobile for iOS <https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675> or Android <https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub>.

[MiguelAngeloMartinsRibeiro]

@joheras Thank you for your reply
Sequential applies all the augmentations to one image, do you think it's worth it? My dataset is very similar. Is it a lot of trouble if I ask for you to make another mode?
My idea was: imagine a dataset of 25 images and 7 augmentations
Augmentation 1 is applied to image 1
Augmentation 2 is applied to image 2
Augmentation 3 is applied to image 3
Augmentation 4 is applied to image 4
Augmentation 5 is applied to image 5
Augmentation 6 is applied to image 6
Augmentation 7 is applied to image 7
Augmentation 1 is applied to image 8
Augmentation 2 is applied to image 9

and so on

And thanks for your excellent work, I'll cite you on my master thesis

[joheras]

I will try to implement that mode, but it will take me some time. I will let you know when it is ready. Best, Jónathan El vie, 10 dic 2021 a las 15:36, MiguelAngeloMartinsRibeiro (< ***@***.***>) escribió:

…

@joheras <https://github.com/joheras> Thank you for your reply Sequential applies all the augmentations to one image, do you think it's worth it? My dataset is very similar. Is it a lot of trouble if I ask for you to make another mode? My idea was: imagine a dataset of 25 images and 7 augmentations Augmentation 1 is applied to image 1 Augmentation 2 is applied to image 2 Augmentation 3 is applied to image 3 Augmentation 4 is applied to image 4 Augmentation 5 is applied to image 5 Augmentation 6 is applied to image 6 Augmentation 7 is applied to image 7 Augmentation 1 is applied to image 8 Augmentation 2 is applied to image 9 and so on And thanks for your excellent work, I'll cite you on my master thesis — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#48 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ABJRAG7B45HXA4ROBTMSM53UQIF6HANCNFSM5FSK7C5Q> . Triage notifications on the go with GitHub Mobile for iOS <https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675> or Android <https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub>.

[MiguelAngeloMartinsRibeiro]

Thank you @joheras I really appreciate it

Let me know when it's ready