From bad3635f0a56e9b34ad707eed1cecff0622fba26 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E5=88=98=E8=88=AA=E5=AE=87?= <3364451258@qq.com>
Date: Thu, 7 May 2026 22:09:13 +0800
Subject: [PATCH] =?UTF-8?q?feat:=20=E5=8E=9F=E7=89=88=E5=A2=9E=E5=8A=A0?=
 =?UTF-8?q?=E6=96=91=E7=82=B9=E6=95=B0=E9=87=8F=E7=BB=9F=E8=AE=A1?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

输出检测到的有效斑点数、面积统计（最小/最大/均值/中位数）
---
 src/cDNA_segmentation.py | 18 +++++++++++++++++-
 1 file changed, 17 insertions(+), 1 deletion(-)

diff --git a/src/cDNA_segmentation.py b/src/cDNA_segmentation.py
index 8d9dc37..80a348d 100644
--- a/src/cDNA_segmentation.py
+++ b/src/cDNA_segmentation.py
@@ -410,7 +410,23 @@ def main() -> None:
     bw_img.save(os.path.join(OUTPUT_DIR, 'result_I_bw.png'))
     print("  保存: result_I_bw.png")
 
-    # ---- 步骤4: 网格叠加图 ----
+    # ---- 步骤4: 统计点数 ----
+    print("\n[步骤4] 统计斑点数量...")
+    labeled_spots, num_spots = ndimage.label(bw_full)
+    # 统计每个斑点的面积
+    spot_sizes = []
+    for i in range(1, num_spots + 1):
+        size = int(np.sum(labeled_spots == i))
+        spot_sizes.append(size)
+    spot_sizes = np.array(spot_sizes)
+    # 过滤极小噪声
+    valid_spots = spot_sizes[spot_sizes >= 10]
+    print(f"  检测到 {len(valid_spots)} 个斑点 (面积≥10像素)")
+    print(f"  斑点面积: 最小 {valid_spots.min()}, 最大 {valid_spots.max()}, "
+          f"均值 {valid_spots.mean():.1f}, 中位数 {np.median(valid_spots):.0f}")
+    print(f"  网格子块数 (理论值): {(len(x_grid)-1) * (len(y_grid)-1)}")
+
+    # ---- 步骤5: 网格叠加图 ----
     if img.ndim == 3:
         overlay = img[:, :, :3].copy()
     else: