Most dominant color in RGB image - OpenCV / NumPy / Python

Question

I have a python image processing function, that uses tries to get the dominant color of an image. I make use of a function I found here https://github.com/tarikd/python-kmea

Answer 1

The equivalent code for cv2.calcHist() is to replace:

(hist, _) = np.histogram(clt.labels_, bins=num_labels)  

with

dmin, dmax, _, _ = cv2.minMaxLoc(clt.labels_)

if np.issubdtype(data.dtype, 'float'): dmax += np.finfo(data.dtype).eps
else: dmax += 1

hist = cv2.calcHist([clt.labels_], [0], None, [num_labels], [dmin, dmax]).flatten()

Note that cv2.calcHist only accepts uint8 and float32 as element type.

Update

It seems like opencv's and numpy's binning differs from each other as the histograms differ if the number of bins doesn't map the value range:

import numpy as np
from matplotlib import pyplot as plt
import cv2

#data = np.random.normal(128, 1, (100, 100)).astype('float32')
data = np.random.randint(0, 256, (100, 100), 'uint8')
BINS = 20

np_hist, _ = np.histogram(data, bins=BINS)

dmin, dmax, _, _ = cv2.minMaxLoc(data)
if np.issubdtype(data.dtype, 'float'): dmax += np.finfo(data.dtype).eps
else: dmax += 1

cv_hist = cv2.calcHist([data], [0], None, [BINS], [dmin, dmax]).flatten()

plt.plot(np_hist, '-', label='numpy')
plt.plot(cv_hist, '-', label='opencv')
plt.gcf().set_size_inches(15, 7)
plt.legend()
plt.show()