Can get colors and HSV

radio.py

@@ -3,7 +3,7 @@ import numpy as np
 import math
 import itertools as it
 
-DENSITY = 5
+DENSITY = 4
 RED = [0, 0, 255]
 N_COLORS = 3
 
@@ -13,16 +13,17 @@ def draw_rectangle(frame, sp, ep):
     return cv2.rectangle(frame, sp, ep, RED)
 
 
-def analyze_block(frame, sp, ep):
+def analyze_block(frame, index, sp, ep):
     """ Analyze a block """
-    block = np.float32(frame[sp[1]:ep[1], sp[0]:ep[0], 0:3])
-    block = block.reshape((-1, 3))
-    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 10, .2)
-    compactness, labels, palette = cv2.kmeans(block, N_COLORS, None, criteria,
-                                              2, cv2.KMEANS_RANDOM_CENTERS)
-    unique, counts = np.unique(labels.flatten(), return_counts=True)
-    for index, count in zip(unique, counts):
-        print(index, count, palette[index])
+    block = frame[sp[1]:ep[1], sp[0]:ep[0], 0:3]
+    average_color = np.average(block, (0, 1))
+    sp2 = tuple(int(x) for x in (2 * np.array(sp) + np.array(ep)) / 3)
+    ep2 = tuple(int(x) for x in (np.array(sp) + 2 * np.array(ep)) / 3)
+    average_color = [int(x) for x in average_color]
+    frame = cv2.rectangle(frame, sp2, ep2, average_color, 5)
+    average_color = np.uint8([[average_color]])
+    h, s, v = cv2.cvtColor(average_color, cv2.COLOR_BGR2HSV)[0][0]
+    print(index, h, s, v)
     return frame
 
 
@@ -33,11 +34,11 @@ def analyze(frame):
     m = math.ceil(n * (height / width))
     dx = width / n
     dy = height / m
-    for x, y in it.product(range(n), range(m)):
+    for index, (x, y) in enumerate(it.product(range(n), range(m))):
         sp = (int(x * dx), int(y * dy))
         ep = (int(x * dx + dx), int(y * dy + dy))
         frame = draw_rectangle(frame, sp, ep)
-        frame = analyze_block(frame, sp, ep)
+        frame = analyze_block(frame, index, sp, ep)
     return frame