add color detection

master
Marcus Universe 8 years ago
parent b5f8305cc3
commit 4e28874afe

@ -11,5 +11,8 @@
"detectTest":{ "detectTest":{
"detectPath":"/Users/universe/Documents/work/data/Plate/boundingbox", "detectPath":"/Users/universe/Documents/work/data/Plate/boundingbox",
"outputPath":"/Users/universe/ProgramUniverse/python/Forked/HyperLPR/out/detect_test" "outputPath":"/Users/universe/ProgramUniverse/python/Forked/HyperLPR/out/detect_test"
},
"colorTest":{
"colorPath":"/Users/universe/Documents/work/data/Plate/colour/u"
} }
} }

@ -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]

@ -2,5 +2,5 @@ import json
with open("/Users/universe/ProgramUniverse/python/Forked/HyperLPR/config.json") as f: with open("/Users/universe/ProgramUniverse/zeusees/HyperLPR/config.json") as f:
configuration = json.load(f) configuration = json.load(f)

@ -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
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