Added mean_color method

main.py

@@ -11,6 +11,7 @@ import cv2
 import numpy
 # Custom Modules
 import scripts
+import mean_color
 
 
 class SkinDetector(object):
@@ -76,6 +77,9 @@ class SkinDetector(object):
         logger.debug('Initialising process')
         dt = time.time()
         self.assert_image(img)
+        logger.debug('Generating mean-color image')
+        #img = mean_color.img_mean(img)
+        logger.debug('Conducting thresholding')
         self.n_mask = 0
         self.mask = numpy.zeros(img.shape[:2], dtype=numpy.uint8)
         self.get_mask_hsv(img)

mean_color.py

+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+__author__ = 'Will Brennan'
+
+
+# Built-in modules
+import time
+import logging
+# Standard modules
+import numpy
+import sklearn.utils
+import sklearn.cluster as cluster
+# Custom modules
+
+logger = logging.getLogger('main')
+
+
+def img_mean(frame, n_clusters=64):
+    result = frame.copy()
+    flat_frame = frame.reshape(-1, 3)
+    frame = sklearn.utils.shuffle(flat_frame)[:min(1000, frame.shape[0]*frame.shape[1])]
+    logger.debug('frame shape: {0}'.format(frame.shape))
+    logger.debug('starting training...')
+    t0 = time.time()
+    kmeans = cluster.KMeans(n_clusters=n_clusters, random_state=0).fit(frame)
+    logger.debug('training took {0}s'.format(round(time.time()-t0, 2)))
+    lookup = kmeans.predict(flat_frame)
+    label_idx = 0
+    for i in range(result.shape[0]):
+        for j in range(result.shape[1]):
+            result[i][j] = kmeans.cluster_centers_[lookup[label_idx]]
+            label_idx += 1
+    logger.debug('label shape: {0}'.format(result.shape))
+    result.astype(dtype=numpy.uint8)
+    return result
\ No newline at end of file