File size: 1,894 Bytes
c843d82 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 |
# imports
import logging, os
from pathlib import Path
from utils.constants import *
from utils.generate_split_images import ImageSplitter
from utils.generate_masks import MaskStitcher
from utils.generate_pngs import TiffToPngConverter
from model.run_cellpose import CellposeBatchProcessor
from utils.generate_image_overlays import OverlayGenerator
from utils.generate_training_dataset import *
from utils.generate_training_split_img_masks import split_folder
# constants
TILE_H = TILE_W = 1024 # training tile size
# generate - pngs
setup_logging(logging.INFO)
converter = TiffToPngConverter(scaling_factor=SCALING_FACTOR, tif_dir=TIF_IMAGES_DIR, output_dir=PNG_IMAGES_DIR)
converter.convert_all()
# generate - splits
setup_logging(logging.INFO)
splitter = ImageSplitter(source_dir=PNG_IMAGES_DIR, output_dir=SPLIT_IMAGES_DIR, sub_image_width=IMG_WIDTH, sub_image_height=IMG_HEIGHT)
splitter.split_all()
# generate - masks for training
setup_logging(logging.INFO)
os.makedirs(TRAIN_MASKS_DIR, exist_ok=True)
for image in TIF_IMAGES_DIR.glob("*.tif"):
img_path = Path(image)
geojson_path = GEOJSON_DIR / (img_path.stem + ".geojson")
mask_png = TRAIN_MASKS_DIR / (img_path.stem + "_masks.tif")
geojson_to_mask_png(img_path, geojson_path, mask_png)
label_mask = np.array(Image.open(mask_png), dtype=np.uint16)
make_bw_preview(label_mask, mask_png.with_name(img_path.stem + "_mask_bw.png"))
make_colored_preview(label_mask, mask_png.with_name(img_path.stem + "_mask_color.png"))
# generate - split images and masks for training
setup_logging(logging.INFO)
split_folder(TIF_IMAGES_DIR, TRAIN_MASKS_DIR, TRAIN_SPLIT_IMG_MASKS_DIR, TILE_H, TILE_W)
# img_path = Path("/Users/discovery/Downloads/SP24_008_2.ome.tif")
# geojson_path = Path("/Users/discovery/Downloads/SP24_088_2.geojson")
# mask_png = Path("/Users/discovery/Downloads/SP24_008_2_mask.tif")
|