Closed TriDvaRas closed 2 years ago
Hi!
In order for training pipeline to work, you'll need 3 datasets:
Does this answer your question?
Yes, thank you!
hello,I have some questions about the dataset: are the training data clean photos? Are the validation photos the same as the training photos? Or are photos data with a mask? thank you !
Hi!
In order for training pipeline to work, you'll need 3 datasets:
* Training data. This is just a folder with jpg's, no extra action is needed. Masks are generated on the fly * Validation data. It is used to evaluate the model after each epoch - and to automatically choose the best one. The creation process is described in [Create your data](https://github.com/saic-mdal/lama#create-your-data) section. * "Visual test" data. It is just like validation, but small. It is useful to assess the generator performance by eye - the pipeline visualizes every sample from this dataset (unlike training and validation). You can put here the most interesting and difficult samples (image+mask pairs). Metrics like FID are not informative when calculated on a small data, so despite metrics are calculated for visual test as well, they are not worth paying attention to.
Does this answer your question?
@windj007 Hi,If I want to train a model in a single scene, such as a grassland, how many pictures should my training set have at least to achieve a better result?
Hi, i'm trying to run the train script on my custom data. I was following to 'Create your data' part of readme and it's a bit unclear what's the purpose of my_dataset/train folder. By this part of readme i assumed that this folder is auto-populated
I left it empty and the run fails with 'num_samples should be a positive integer value, but got num_samples=0' Looking at logs it seems like it's trying to find files there
Other folders seem to look fine in log
So I also tried putting some images in train folder with same structure as val but it still fails with the same error