Get diagonal squares coordinates in numpy distance symmetric matrix

Question

How to get the coordinates of the big rectangles that line on the diagonal.

For example yellow [0,615], [615,1438], [1438,1526]

import numpy as np; 
import pandas as pd
from sklearn.metrics.pairwise import cosine_similarity

df = pd.DataFrame(array) # array is image numpy
df.shape #(1526, 360)
s = cosine_similarity(df) #(1526, 1526)
plt.matshow(s)

i try get peaks in first row, but have noise information

speak = 1-s[0]

peaks, _ = find_peaks(speak, distance=160, height=0.1)
print(peaks, len(peaks))
np.diff(peaks)

plt.plot(speak)
plt.plot(peaks, speak[peaks], "x")
plt.show()

Update, add another example And upload to colab full script https://colab.research.google.com/drive/1hyDIDs-QjLjD2mVIX4nNOXOcvCZY4O2c?usp=sharing

Answer 1

Solve with DBSCAN clustering (find in same question DBSCAN for clustering of geographic location data)

from sklearn.cluster import DBSCAN

clustering = DBSCAN(eps=.5, min_samples=10).fit_predict(s)

peaks = np.where(clustering[:-1] != clustering[1:])[0]