digilut
Entrypoint of Digilut's main CLI.
Usage:
$ digilut [OPTIONS] COMMAND [ARGS]...
Options:
--install-completion
: Install completion for the current shell.--show-completion
: Show completion for the current shell, to copy it or customize the installation.--help
: Show this message and exit.
Commands:
clean-bbox
: Remove obvious labelling mistakes from the...credits
: Print credits with style.pyfast
: Pyfast processing commands to patchify...tiles
: Commands for tiles.undersample
: Undersample patches to solve class imbalance
digilut clean-bbox
Remove obvious labelling mistakes from the input bounding box csv and save a new cleaned dataset csv.
Usage:
$ digilut clean-bbox [OPTIONS] CSV_BBOXES CSV_OUTPUT
Arguments:
CSV_BBOXES
: Bounding box csv to clean [required]CSV_OUTPUT
: Name of the cleaned csv [required]
Options:
--show-plots / --no-show-plots
: Plot figures [default: no-show-plots]--train / --no-train
: In train mode run some check on rows, disabled for validation. [default: train]--help
: Show this message and exit.
digilut credits
Print credits with style.
Usage:
$ digilut credits [OPTIONS]
Options:
--help
: Show this message and exit.
digilut pyfast
Pyfast processing commands to patchify .tif WSI images.
Usage:
$ digilut pyfast [OPTIONS] COMMAND [ARGS]...
Options:
--help
: Show this message and exit.
Commands:
labels
: Create labels for the tiles.patchify-dataset
: Extracts tiles from a dataset of slides.patchify-slide
: Exports the TIFF file into PNG tiles of...
digilut pyfast labels
Create labels for the tiles.
A tile is positive if it intersects at more that XX% with a bounding box.
Usage:
$ digilut pyfast labels [OPTIONS] CSV_BBOXES FOLDER_PATCHES CSV_LABELS
Arguments:
CSV_BBOXES
: [required]FOLDER_PATCHES
: [required]CSV_LABELS
: [required]
Options:
--threshold-iou FLOAT
: [default: 0.1]--help
: Show this message and exit.
digilut pyfast patchify-dataset
Extracts tiles from a dataset of slides. Calls patchify-slide over each slide in the folder.
Usage:
$ digilut pyfast patchify-dataset [OPTIONS] [CSV_PATH] [IMAGES_DIR] [OUTPUT_DIR]
Arguments:
[CSV_PATH]
: Path to the CSV file [default: data/train.csv][IMAGES_DIR]
: Folder containing the .tif slide images [default: data/images][OUTPUT_DIR]
: Output dir. Each slide will have a {outputdir}/{slide} [default: outputs]
Options:
--save-engine TEXT
: Engine to save image. 'cv2' (recommended) OR 'pillow' [default: cv2]--patch-size INTEGER
: Patch size (width and hieght) [default: 256]--level INTEGER
: Zoom level. 0 is the best resolution [default: 0]--overlap-percent FLOAT
: Percentage of overlap between patches [default: 0.0]-f, --img_format TEXT
: Image format. PNG is better (no artifact) but it x5 heavier. Values: 'jpg', 'png' [default: jpg]--help
: Show this message and exit.
digilut pyfast patchify-slide
Exports the TIFF file into PNG tiles of tissue.
Usage:
$ digilut pyfast patchify-slide [OPTIONS] TIFF_PATH OUTPUT_DIR
Arguments:
TIFF_PATH
: Path to the slide [required]OUTPUT_DIR
: Output folder where patches will be saved [required]
Options:
--save-engine TEXT
: Engine to save image. 'cv2' (recommended) OR 'pillow' [default: cv2]--patch-size INTEGER
: Patch size (width and hieght) [default: 256]--level INTEGER
: Zoom level. 0 is the best resolution [default: 0]--overlap-percent FLOAT
: Percentage of overlap between patches [default: 0.0]--img-format TEXT
: Image format. PNG is better (no artifact) but it x5 heavier. Values: 'jpg', 'png' [default: jpg]--help
: Show this message and exit.
digilut tiles
Commands for tiles.
Usage:
$ digilut tiles [OPTIONS] COMMAND [ARGS]...
Options:
--help
: Show this message and exit.
Commands:
extract-from-dataset
: Extract tiles a dataset of tiles.extract-from-image
: Extract tiles from the slide.generate-labels
: (Deprecated) Create the labels for the tiles.
digilut tiles extract-from-dataset
Extract tiles a dataset of tiles. Calls extract_from_image over a folder of slides.
Usage:
$ digilut tiles extract-from-dataset [OPTIONS] [CSV_PATH] [OUTPUT_DIR]
Arguments:
[CSV_PATH]
: Path to the CSV file [default: data/train.csv][OUTPUT_DIR]
: Outputdir [default: outputs]
Options:
--tile-size INTEGER
: Size of the tiles (height and width) [default: 1024]--parallel / --no-parallel
: Enable multiprocessing. [default: parallel]--help
: Show this message and exit.
digilut tiles extract-from-image
Extract tiles from the slide.
Usage:
$ digilut tiles extract-from-image [OPTIONS] PATH_TIFF OUTPUT_DIR
Arguments:
PATH_TIFF
: Path to the TIFF file [required]OUTPUT_DIR
: Output folder. The output will we saved in {outputdir}/{path_tiff.stem} [required]
Options:
--tile-size INTEGER
: Size of the tiles (height and width) [default: 1024]-p, --no-parallel
: Disable multiprocessing. [default: True]--help
: Show this message and exit.
digilut tiles generate-labels
Create the labels for the tiles. V1 Deprecated. Use digilut pyfast
Usage:
$ digilut tiles generate-labels [OPTIONS] CSV_BBOXES SLIDE_FOLDER
Arguments:
CSV_BBOXES
: Bounding box file. [required]SLIDE_FOLDER
: Slide folder, that contains aninfo
and atiles
subfolder. [required]
Options:
--iou-thres FLOAT
: Threshold Intersection over Union. If tile IOU > with a bounding box, the tile is labbeled positive. [default: 0.2]--help
: Show this message and exit.
digilut undersample
Undersample patches to solve class imbalance
Usage:
$ digilut undersample [OPTIONS] COMMAND [ARGS]...
Options:
--help
: Show this message and exit.
Commands:
run
: Takes as input the set of possible patches...
digilut undersample run
Takes as input the set of possible patches and returns a subset of them that will be used for building the training dataset.
For each slide folder, checks the patches metadata.csv Keep N positive and N negative patches.
Usage:
$ digilut undersample run [OPTIONS] CSV_PATCHES OUTPUT_BALANCED_PATCHES
Arguments:
CSV_PATCHES
: [required]OUTPUT_BALANCED_PATCHES
: [required]
Options:
--sampling-strategy FLOAT
--random-seed INTEGER
: [default: 1234]--help
: Show this message and exit.