From 6af81cbf921220d84e0f37f2fb276b1bf08442c1 Mon Sep 17 00:00:00 2001
From: Timur <stud182932@vyatsu.ru>
Date: Sat, 30 May 2026 11:59:32 +0300
Subject: [PATCH] Add spectral clustering image segmentation

---
 04_spectral_clustering/image_segmentation.py | 67 ++++++++++++++++++++
 1 file changed, 67 insertions(+)
 create mode 100644 04_spectral_clustering/image_segmentation.py

diff --git a/04_spectral_clustering/image_segmentation.py b/04_spectral_clustering/image_segmentation.py
new file mode 100644
index 0000000..affa036
--- /dev/null
+++ b/04_spectral_clustering/image_segmentation.py
@@ -0,0 +1,67 @@
+import time
+import numpy as np
+import matplotlib.pyplot as plt
+import logging
+from scipy.ndimage import gaussian_filter
+from skimage.data import coins
+from skimage.transform import rescale
+from sklearn.cluster import spectral_clustering
+from sklearn.feature_extraction import image
+
+# Настройка логирования
+logging.basicConfig(level=logging.INFO, 
+                    format='%(asctime)s [%(levelname)s] %(message)s')
+
+def main():
+    logging.info("Загрузка и обработка изображения...")
+    
+    # Загрузка изображения
+    orig_coins = coins()
+    smoothed = gaussian_filter(orig_coins, sigma=2)
+    rescaled = rescale(smoothed, 0.2, mode="reflect", anti_aliasing=False)
+    
+    logging.info(f"Изображение: {rescaled.shape}")
+    
+    # Построение графа
+    logging.info("Построение графа...")
+    graph = image.img_to_graph(rescaled)
+    beta = 10
+    eps = 1e-6
+    graph.data = np.exp(-beta * graph.data / graph.data.std()) + eps
+    
+    # Кластеризация
+    n_regions = 26
+    methods = ('kmeans', 'discretize', 'cluster_qr')
+    
+    for method in methods:
+        logging.info(f"Метод: {method}")
+        t0 = time.time()
+        
+        labels = spectral_clustering(
+            graph,
+            n_clusters=n_regions + 3,
+            eigen_tol=1e-7,
+            assign_labels=method,
+            random_state=42
+        )
+        
+        duration = time.time() - t0
+        labels = labels.reshape(rescaled.shape)
+        
+        logging.info(f"Завершено за {duration:.2f} сек.")
+        
+        # Визуализация
+        plt.figure(figsize=(6, 6))
+        plt.imshow(rescaled, cmap=plt.cm.gray)
+        plt.title(f"{method}, {duration:.2f} сек.")
+        plt.axis('off')
+        
+        for l in range(n_regions):
+            color = plt.cm.nipy_spectral((l + 4) / float(n_regions + 4))
+            plt.contour(labels == l, colors=[color], linewidths=0.5)
+        
+        plt.tight_layout()
+        plt.show()
+
+if __name__ == '__main__':
+    main()
\ No newline at end of file