Quick Start
Get from whole‑slide images to enriched tile metadata in minutes.
Install
pip install "ratiopath"
Minimal Pipeline
from ratiopath.ray import read_slides
from ratiopath.tiling import grid_tiles
slides = read_slides("data", mpp=0.25, tile_extent=1024, stride=960)
def tiling(row):
return [
yield {
"slide_id": row["id"],
"tile_x": x,
"tile_y": y,
"level": row["level"],
}
for x, y in grid_tiles(
(row["extent_x"], row["extent_y"]),
(row["tile_extent_x"], row["tile_extent_y"]),
(row["stride_x"], row["stride_y"]),
last="keep",
)
]
tiles = slides.flat_map(tiling)
tiles.show(5)
Next Steps
- Build the full tiling pipeline: Tiling Tutorial
- Add annotation coverage: Annotation Coverage
Tips
- Use .stats() after an action to inspect performance.
- Repartition before expensive pixel reads.
- Keep slide metadata separate; avoid duplication.
Ready? Jump to the Tiling Tutorial.