add color detection
parent
b5f8305cc3
commit
4e28874afe
@ -0,0 +1,103 @@
|
||||
# -- coding: UTF-8
|
||||
import cv2
|
||||
import matplotlib.pyplot as plt
|
||||
from sklearn.cluster import KMeans
|
||||
import os
|
||||
|
||||
boundaries = [
|
||||
([100,80,0],[240,220,110]), # yellow
|
||||
([0,40,50],[110,180,250]), # blue
|
||||
([0,60,0],[60,160,70]), # green
|
||||
]
|
||||
color_attr = ["黄牌","蓝牌",'绿牌','白牌','黑牌']
|
||||
|
||||
threhold_green = 13
|
||||
threhold_blue = 13
|
||||
threhold_yellow1 = 50
|
||||
threhold_yellow2 = 70
|
||||
|
||||
# plt.figure()
|
||||
# plt.axis("off")
|
||||
# plt.imshow(image)
|
||||
# plt.show()
|
||||
|
||||
import numpy as np
|
||||
def centroid_histogram(clt):
|
||||
numLabels = np.arange(0, len(np.unique(clt.labels_)) + 1)
|
||||
(hist, _) = np.histogram(clt.labels_, bins=numLabels)
|
||||
|
||||
# normalize the histogram, such that it sums to one
|
||||
hist = hist.astype("float")
|
||||
hist /= hist.sum()
|
||||
|
||||
# return the histogram
|
||||
return hist
|
||||
|
||||
|
||||
def plot_colors(hist, centroids):
|
||||
bar = np.zeros((50, 300, 3), dtype="uint8")
|
||||
startX = 0
|
||||
|
||||
for (percent, color) in zip(hist, centroids):
|
||||
|
||||
endX = startX + (percent * 300)
|
||||
cv2.rectangle(bar, (int(startX), 0), (int(endX), 50),
|
||||
color.astype("uint8").tolist(), -1)
|
||||
startX = endX
|
||||
|
||||
# return the bar chart
|
||||
return bar
|
||||
|
||||
def search_boundaries(color):
|
||||
for i,color_bound in enumerate(boundaries):
|
||||
if np.all(color >= color_bound[0]) and np.all(color <= color_bound[1]):
|
||||
return i
|
||||
return -1
|
||||
|
||||
def judge_color(color):
|
||||
r = color[0]
|
||||
g = color[1]
|
||||
b = color[2]
|
||||
if g - r >= threhold_green and g - b >= threhold_green:
|
||||
return 2
|
||||
if b - r >= threhold_blue and b - g >= threhold_blue:
|
||||
return 1
|
||||
if r- b > threhold_yellow2 and g - b > threhold_yellow2:
|
||||
return 0
|
||||
if r > 200 and b > 200 and g > 200:
|
||||
return 3
|
||||
if r < 50 and b < 50 and g < 50:
|
||||
return 4
|
||||
return -1
|
||||
|
||||
def judge_plate_color(img):
|
||||
image = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
|
||||
image = image.reshape((image.shape[0] * image.shape[1], 3))
|
||||
clt = KMeans(n_clusters=2)
|
||||
clt.fit(image)
|
||||
|
||||
hist = centroid_histogram(clt)
|
||||
index = np.argmax(hist)
|
||||
#print clt.cluster_centers_[index]
|
||||
#color_index = search_boundaries(clt.cluster_centers_[index])
|
||||
color_index = judge_color(clt.cluster_centers_[index])
|
||||
if color_index == -1:
|
||||
if index == 0:
|
||||
secound_index = 1
|
||||
else:
|
||||
secound_index = 0
|
||||
color_index = judge_color(clt.cluster_centers_[secound_index])
|
||||
|
||||
if color_index == -1:
|
||||
print clt.cluster_centers_
|
||||
bar = plot_colors(hist, clt.cluster_centers_)
|
||||
# show our color bart
|
||||
plt.figure()
|
||||
plt.axis("off")
|
||||
plt.imshow(bar)
|
||||
plt.show()
|
||||
|
||||
if color_index != -1:
|
||||
return color_attr[color_index],clt.cluster_centers_[index]
|
||||
else:
|
||||
return None,clt.cluster_centers_[index]
|
@ -0,0 +1,17 @@
|
||||
# -- coding: UTF-8
|
||||
|
||||
import cv2
|
||||
import os
|
||||
import hyperlpr.colourDetection as hc
|
||||
import hyperlpr.config as hconfig
|
||||
|
||||
filepath = hconfig.configuration["colorTest"]["colorPath"]
|
||||
for filename in os.listdir(filepath):
|
||||
if filename.endswith(".jpg") or filename.endswith(".png") or filename.endswith(".bmp"):
|
||||
fileFullPath = os.path.join(filepath,filename)
|
||||
img = cv2.imread(fileFullPath.encode('utf-8'))
|
||||
color,rgb = hc.judge_plate_color(img)
|
||||
if color != None:
|
||||
print filename,"->",color,"->",rgb
|
||||
else:
|
||||
print filename,"->","unknown->",rgb
|
Loading…
Reference in New Issue