vqdang / hover_net

Simultaneous Nuclear Instance Segmentation and Classification in H&E Histology Images.
MIT License
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Qupath, geojson format #257

Open merihdeniz19 opened 1 year ago

merihdeniz19 commented 1 year ago

Hi, I ran infer with WSI mode and was wondering if there's any way of converting the JSON files to GeoJSON or any other format compatible with Qupath. Thank you so much!

kaczmarj commented 10 months ago

i also ran into this issue and i created a script to convert from hovernet's json files to geojson. i am using the pannuke model weights. if you are using a different model, you will probably have to change the type_mapping dictionary.

"""Convert HoverNet outputs to GeoJSON format."""

import argparse
import gzip
import json
from pathlib import Path

from shapely.geometry import Polygon

# https://github.com/vqdang/hover_net/blob/842964dc5d26ffe196d236d16fad16643a103850/type_info.json
type_mapping = {
    0: "nolabel",
    1: "neoplastic",
    2: "inflammatory",
    3: "connective",
    4: "necrosis",
    5: "non-neoplastic",
}

def hovernet_to_feature_dict(instance_id: int, d: dict):
    # Convert to polygon to verify that coordinates
    # are valid.
    poly = Polygon(d["contour"])
    coordinates = list(poly.exterior.coords)
    return {
        "type": "Feature",
        "geometry": {
            "type": "Polygon",
            "coordinates": coordinates,
        },
        "properties": {
            "instance_id": int(instance_id),
            "type_str": type_mapping[d["type"]],
            "type_int": d["type"],
            "type_prob": d["type_prob"],
        },
    }

def hovernet_to_geojson(d: dict):
    assert "nuc" in d.keys(), "expected 'nuc' key"
    assert "mag" in d.keys(), "expected 'mag' key"
    assert d["mag"] == 40, "this script was designed for mag=40x"
    features = [hovernet_to_feature_dict(ii, dd) for ii, dd in d["nuc"].items()]
    return {
        "type": "FeatureCollection",
        "features": features,
    }

if __name__ == "__main__":
    p = argparse.ArgumentParser(description=__doc__)
    p.add_argument("input", help="JSON file with HoverNet predictions.")
    p.add_argument("output", help="Output GeoJSON file")
    args = p.parse_args()

    if not Path(args.input).exists():
        raise FileNotFoundError(f"Input file not found: {args.input}")
    if Path(args.output).exists():
        raise FileExistsError(f"Output file exists: {args.output}")

    print("Reading HoverNet polygons...")
    openfn = gzip.open if args.input.endswith("gz") else open
    with openfn(args.input) as f:
        d = json.load(f)

    print("Converting to GeoJSON...")
    geojson = hovernet_to_geojson(d)

    print(f"Writing output to {args.output}")
    openfn = gzip.open if args.output.endswith("gz") else open
    with openfn(args.output, "wt") as f:
        json.dump(geojson, f)

    print("Done.")
simongraham commented 3 weeks ago

Good work @kaczmarj

kaczmarj commented 3 weeks ago

one thing i learned is that if the original slide is 20X, the coordinates from hovernet need to be scaled by 1/2. otherwise the coordinates won't overlap with the nuclei