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Gleason_CNN masklerinden polygon CSV'si üretir → polygons.csv
Maske değer sözlüğü (palette PNG, tam sayı indeks):
0 = Benign
1 = Gleason_3 → G3
2 = Gleason_4 → G4
3 = Gleason_5 → G5
4 = unlabelled → atlanır
Üç kaynak klasör ve karşılık gelen creator:
Gleason_masks_train → "train"
Gleason_masks_test_pathologist1 → "test_pathologist1"
Gleason_masks_test_pathologist2 → "test_pathologist2"
Her polygon seyreltilir (approxPolyDP, epsilon_start=2.0, max_points=50).
"""
import csv
import json
import os
import re
from pathlib import Path
import cv2
import numpy as np
from PIL import Image
# ---------------------------------------------------------------------------
# Konfigürasyon
# ---------------------------------------------------------------------------
ORIGIN_DIR = Path("origin")
OUT_CSV = Path("polygons.csv")
LABEL_MAP = {0: "Benign", 1: "G3", 2: "G4", 3: "G5"} # 4 = unlabelled, atlanır
MIN_AREA = 150 # piksel cinsinden minimum alan (küçük artefaktları at)
EPSILON_START = 2.0 # approxPolyDP başlangıç epsilonu
MAX_POINTS = 50 # polygon başına maksimum köşe noktası
SOURCES = [
("Gleason_masks_train", "train", re.compile(r"^mask_(.+)\.png$")),
("Gleason_masks_test_pathologist1", "test_pathologist1", re.compile(r"^mask1_(.+)\.png$")),
("Gleason_masks_test_pathologist2", "test_pathologist2", re.compile(r"^mask2_(.+)\.png$")),
]
# ---------------------------------------------------------------------------
# Yardımcı fonksiyonlar
# ---------------------------------------------------------------------------
def simplify_contour(contour) -> list[list[int]] | None:
"""Kontur → basitleştirilmiş kapalı polygon noktaları [[x, y], ...]."""
approx = cv2.approxPolyDP(contour, EPSILON_START, closed=True)
eps = EPSILON_START
while len(approx) > MAX_POINTS and eps <= 20.0:
eps *= 1.5
approx = cv2.approxPolyDP(approx.astype(np.float32), eps, closed=True)
if len(approx) < 3:
return None
pts = [[int(p[0][0]), int(p[0][1])] for p in approx]
pts.append(pts[0]) # kapanış noktası
return pts
def remove_small_components(binary: np.ndarray) -> np.ndarray:
n, labels, stats, _ = cv2.connectedComponentsWithStats(binary, connectivity=8)
clean = np.zeros_like(binary)
for lid in range(1, n):
if stats[lid, cv2.CC_STAT_AREA] >= MIN_AREA:
clean[labels == lid] = 1
return clean
def process_mask(mask_path: Path, creator: str, image_name: str) -> list[dict]:
"""Maskten polygon satırlarını üretir."""
try:
arr = np.array(Image.open(mask_path))
except Exception as e:
print(f" UYARI okuma hatası ({mask_path.name}): {e}")
return []
rows = []
for class_idx, label in LABEL_MAP.items():
binary = (arr == class_idx).astype(np.uint8)
if binary.sum() == 0:
continue
binary = remove_small_components(binary)
if binary.sum() == 0:
continue
contours, _ = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
for cnt in contours:
if cv2.contourArea(cnt) < MIN_AREA:
continue
pts = simplify_contour(cnt)
if pts is None:
continue
rows.append({
"image_name": image_name,
"label": label,
"polygon": json.dumps(pts),
"creator": creator,
})
return rows
# ---------------------------------------------------------------------------
# Ana akış
# ---------------------------------------------------------------------------
def main():
all_rows: list[dict] = []
for folder_name, creator, name_re in SOURCES:
folder = ORIGIN_DIR / folder_name
if not folder.exists():
print(f"UYARI: klasör bulunamadı → {folder}")
continue
mask_files = sorted(
p for p in folder.glob("*.png")
if not p.name.startswith("._")
)
print(f"\n{folder_name} ({len(mask_files)} maske) creator='{creator}'")
skipped = 0
for mf in mask_files:
m = name_re.match(mf.name)
if not m:
skipped += 1
continue
image_name = m.group(1)
rows = process_mask(mf, creator, image_name)
all_rows.extend(rows)
if skipped:
print(f" {skipped} dosya isim kalıbına uymadı, atlandı.")
print(f"\nToplam {len(all_rows)} polygon satırı → {OUT_CSV}")
with open(OUT_CSV, "w", newline="") as f:
writer = csv.DictWriter(
f, fieldnames=["image_name", "label", "polygon", "creator"]
)
writer.writeheader()
writer.writerows(all_rows)
print("Tamamlandı.")
if __name__ == "__main__":
os.chdir(Path(__file__).parent)
main()
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