""" 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()