Timeline for What should the output sizing be for a class that returns multiple image arrays for a dataloader
Current License: CC BY-SA 4.0
7 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jun 11, 2021 at 9:38 | vote | accept | einsteinxx | ||
| Jun 4, 2021 at 14:05 | comment | added | Devashish Prasad | Do let me know if you are satisfied with the answer? If not I will try my best possible way to edit it. Please consider accepting the answer if it answers your question. | |
| Jun 3, 2021 at 6:08 | answer | added | Devashish Prasad | timeline score: 0 | |
| Jun 3, 2021 at 3:38 | comment | added | einsteinxx | Yes, I take in one image and create 4 (or more) transformed images and I'd like to use that 4 as a batch to the VGG model. I was able to engineer it so that I run VGG once per transformed file found (so one prediction per file), but I feel like there's some dataloader magic that I'm not taking advantage of. | |
| Jun 2, 2021 at 7:24 | comment | added | Devashish Prasad | Welcome to DatascienceSE, you don't want to randomly augment your images? You want to make batches according to a single image, i.e. for each image you want predictions on 4 augmented images from your model? | |
| Jun 1, 2021 at 23:34 | review | First posts | |||
| Jun 1, 2021 at 23:56 | |||||
| Jun 1, 2021 at 23:29 | history | asked | einsteinxx | CC BY-SA 4.0 |