delta.data.load_training_dataset_seg#
- delta.data.load_training_dataset_seg(dataset_path, target_size, *, crop, kw_data_aug, validation_split=0, test_split=0, seed=1, stack=False)[source]#
Create new segmentation datasets.
- Parameters
- dataset_pathPath
Path of the folder that contains img, seg and optionally wei.
- target_size(int, int)
Target size of the images (input size of the neural network).
- cropbool
If True, the images are cropped to the target size, if False, they are resized. Typically we resize mother machine images and crop 2D pad images.
- kw_data_augdict[str, Any]
Parameters for the data augmentation function (see data_augmentation).
- validation_splitfloat, optional
Proportion (between 0 and 1) of the input images used for the validation set. The default is 0.
- test_splitfloat, optional
Proportion (between 0 and 1) of the input images used for the test set. The default is 0.
- seedint, optional
Seed for the random number generator. The default is 1.
- stackbool, optional
Whether to stack the labels and weights. This is a technicality that should be removed soon. For now, specify True for cell segmentation and False for RoI segmentation (follow the example scripts).
- Returns
- train_dsSegmentationDataset,
- validation_dsSegmentationDataset, (optional)
- test_dsSegmentationDataset, (optional)