def process_annotation(args, slide, rule):
if args.method == "none":
annotation = wp.annotation("")
annotation.dot_to_bbox(args.dot_bbox_width, args.dot_bbox_height)
if args.minmax:
min_, max_ = map(int, args.minmax.split("-"))
annotation.make_masks(slide,
foreground="minmax",
min_=min_,
max_=max_)
else:
annotation.make_masks(slide, foreground="otsu")
else:
annotation = wp.annotation(args.annotation, slidename=slide.filename)
annotation.dot_to_bbox(args.dot_bbox_width, args.dot_bbox_height)
if hasattr(args, "minmax") and args.minmax:
min_, max_ = map(int, args.minmax.split("-"))
annotation.make_masks(slide,
rule,
foreground="minmax",
min_=min_,
max_=max_)
else:
annotation.make_masks(slide, rule, foreground=True)
if not args.extract_foreground and "foreground" in annotation.classes:
annotation.classes.remove("foreground")
return annotation
def run_process(self):
wsiidx = self.selected_files.curselection()[0]
self.params["wsi"] = self.selected_files_list[wsiidx]
slide = wp.slide(self.params["wsi"])
if self.params["rule file"].get():
rule = wp.rule(self.params["rule file"].get())
else:
rule = False
if self.params["annotation file"].get():
annotation = wp.annotation(self.params["annotation file"].get())
annotation.make_masks(slide, rule, foreground=True)
annotation.classes.remove("foreground")
classes = annotation.classes
else:
annotation = wp.annotation("")
annotation.make_masks(slide, foreground=True)
classes = annotation.classes
patcher = wp.patcher(
slide,
self.params["method"].get(),
annotation=annotation,
save_to=self.params["where to save"].get(),
patch_width=self.params["patch width"].get(),
patch_height=self.params["patch height"].get(),
overlap_width=self.params["overlap width"].get(),
overlap_height=self.params["overlap height"].get(),
on_foreground=self.params["ratio of foreground"].get(),
on_annotation=self.params["ratio of annotation"].get(),
start_sample=False,
finished_sample=False,
extract_patches=True)
patcher.get_patch_parallel(classes)
if self.params["convert to voc"].get(
) or self.params["convert to coco"].get():
converter = wp.converter(
self.params["where to save"].get() + "/" + slide.filestem,
self.params["where to save"].get(), "8:1:1")
if self.params["convert to voc"].get():
converter.to_voc()
if self.params["convert to coco"].get():
converter.to_coco()
def cli(params):
slide = wp.slide(params.wsi)
if params.rule:
rule = wp.rule(params.rule)
else:
rule = False
if params.annotation:
annotation = wp.annotation(params.annotation)
annotation.make_masks(slide, rule, foreground=True)
annotation.classes.remove("foreground")
else:
annotation = wp.annotation("")
if params.on_annotation:
annotation.make_masks(slide, foreground=True)
patcher = wp.patcher(slide,
params.method,
annotation=annotation,
save_to=params.save_to,
patch_width=params.patch_width,
patch_height=params.patch_height,
overlap_width=params.overlap_width,
overlap_height=params.overlap_height,
offset_x=params.offset_x,
offset_y=params.offset_y,
on_foreground=params.on_foreground,
on_annotation=params.on_annotation,
no_patches=params.no_patches)
patcher.get_patch_parallel(annotation.classes)
if params.voc_style or params.coco_style or params.yolo_style:
converter = wp.converter(params.save_to / slide.filestem,
params.save_to, params.ratio)
if params.voc_style:
converter.to_voc()
if params.coco_style:
converter.to_coco()
if params.yolo_style:
converter.to_yolo()
import wsiprocess as wp
import cv2
slide = wp.slide("CMU-1.ndpi")
annotation = wp.annotation("", is_image=True)
target_classes = ["benign", "malignant"]
annotation.add_class(target_classes)
benign_mask = cv2.imread("benign_mask.png", 0) * 255
malignant_mask = cv2.imread("malignant_mask.png", 0) * 255
# Make sure your mask data includes only 0 as background or 255 as foreground
annotation.from_image(benign_mask, "benign")
annotation.from_image(malignant_mask, "malignant")
patcher = wp.patcher(slide, "classification", annotation=annotation)
patcher.get_patch_parallel(target_classes)
import wsiprocess as wp
import numpy as np
def example_function(thumb_gray):
assert len(thumb_gray.shape) == 2
assert isinstance(thumb_gray, np.ndarray)
thresh = 100
thumb_gray[thumb_gray > thresh] = 1
thumb_gray[thumb_gray <= thresh] = 0
assert np.sum((thumb_gray == 0) | (thumb_gray == 1)) == len(thumb_gray)
return thumb_gray
slide = wp.slide("CMU-1.ndpi")
annotation = wp.annotation("CMU-1_classification.xml")
annotation.make_masks(slide, foreground=example_function)
patcher = wp.patcher(slide, "classification", annotation)
patcher.get_patch_parallel(["benign"])