目标检测目标的统计
1 对目标数量，占比的统计
2 对目标尺寸(长，宽及面积的箱型图)
统计时你只需要修改对应目标的字典即可(下载STLITI.TTF字体格式，放到当前位置,替换fname中的位置)
# encoding:utf-8
""""
#20200331 统计目标检测中的数据，需要输入dota格式的标签x1,y1....x4,y4,category
"""
import numpy as np
import os
import matplotlib.pyplot as plt
from matplotlib import font_manager
import random
#目标数据统计字典
totalnum={ 'ship' : 0,
"airplane" : 0,
"vehicle" : 0,
"overpass" : 0,
"basketballcourt" : 0,
"tenniscourt" : 0,
"airport" : 0,
'storagetank': 0,
"Expressway-Service-area": 0,
"harbor": 0,
"baseballfield": 0,
"bridge": 0,
"chimney": 0,
"groundtrackfield": 0,
"trainstation":0,
"stadium": 0,
"windmill": 0,
"golffield": 0,
"Expressway-toll-station": 0,
"dam":0
}
#每类目标的长宽数据统计
totalnum_wh_area={"ship" : {'w':[],'h':[],'area':[]},
"airplane" : {'w':[],'h':[],'area':[]},
"vehicle" : {'w':[],'h':[],'area':[]},
"overpass" : {'w':[],'h':[],'area':[]},
"basketballcourt" : {'w':[],'h':[],'area':[]},
"tenniscourt" : {'w':[],'h':[],'area':[]},
"airport" : {'w':[],'h':[],'area':[]},
"storagetank": {'w': [], 'h': [], 'area': []},
"Expressway-Service-area": {'w': [], 'h': [], 'area': []},
"harbor": {'w': [], 'h': [], 'area': []},
"baseballfield": {'w': [], 'h': [], 'area': []},
"bridge": {'w': [], 'h': [], 'area': []},
"chimney": {'w': [], 'h': [], 'area': []},
"groundtrackfield": {'w': [], 'h': [], 'area': []},
"trainstation": {'w': [], 'h': [], 'area': []},
"stadium": {'w': [], 'h': [], 'area': []},
"windmill": {'w': [], 'h': [], 'area': []},
"golffield": {'w': [], 'h': [], 'area': []},
"Expressway-toll-station": {'w': [], 'h': [], 'area': []},
"dam": {'w': [], 'h': [], 'area': []}
}
colors=['black','lightcoral','maroon','red','salmon','darksalmon','peru','orange',\
'darkgoldenrod','olivedrab','chartreuse','palegreen','lime','seagreen',\
'cyan','deepskyblue','skyblue','dodgerblue','lightslategray','crimson','b']
#标题名字
category_title="dota"
#画不同目标的总数量条形图及占比扇形图
def draw_totalnum(inputfiles,out_put):
files=os.listdir(inputfiles)
#统计不同目标的数据
for fliename in files:
txt_path=os.path.join(inputfiles,fliename)
txt_size=os.path.getsize(txt_path)
txt_f=open(txt_path,"r")
if txt_size != 0:
for line in txt_f.readlines():
split_line=line.replace("\n","").split(" ")
category=split_line[8]
category_label = category
#category_label=dict_category[category]
if category_label in totalnum.keys():
totalnum[category_label] += 1
else:
print("####category is not inputfiles:",inputfiles,category_label)
else:
print ("###txt_path_size is 0:",txt_path)
#根据统计的数目画柱状图
key_list = []
val_list = []
for key in totalnum.keys():
key_list.append(key)
val_list.append(totalnum[key])
#添加图像属性
plt.figure(1)
plt.figure(figsize=(10, 10))
my_font = font_manager.FontProperties(fname="/data/xx/PycharmProjects/object_detection_tool/image_label_data_convert/STLITI.TTF")
plt.xlabel("类别",fontproperties=my_font,size=10)
plt.ylabel("数量(个)",fontproperties=my_font,size=10)
plt.title(category_title+"数据统计",fontproperties=my_font,size=15)
#绘制Y轴信息
y=val_list
first_bar = plt.bar(range(len(y)), y, width=0.4, color='blue')
#绘制x轴的数据
index=range(0,len(y))
name_list=key_list
plt.xticks(index, name_list,fontproperties=my_font,rotation=-60) # 绘制x轴的标签
#添加数量
for data in first_bar:
y=data.get_height()
x=data.get_x()
plt.text(x,y,str(y),va="bottom")
plt.savefig(os.path.join(out_put,"ship_columnar.jpg"))
plt.close(1)
#画扇形图
plt.figure(2)
plt.figure(figsize=(12, 12))
labels= key_list
sizes=val_list
colors_=random.sample(colors,len(key_list))
explode=[]
for index in range(len(key_list)):
if val_list[index] < 300:
explode.append(random.uniform(0.025,0.1))
else:
explode.append(0)
explode=tuple(explode)
patches, l_text,p_text = plt.pie(sizes,
explode=explode,
labels=labels,
colors=colors,
pctdistance=0.8, # 设置百分比标签和圆心的距离
labeldistance=1.02, # 图例距圆心半径倍距离
autopct='%3.2f%%', # 数值保留固定小数位
shadow=False, # 无阴影设置
startangle=90, # 逆时针起始角度设置
# center=(10, 10), # 设置饼图的圆心(相当于X轴和Y轴的范围)
# radius=10, # 设置饼图的半径(相当于X轴和Y轴的范围)
wedgeprops={'linewidth': 1, 'edgecolor': 'green'}, # 设置饼图内外边界的属性值
textprops={'fontsize': 20, 'color': 'black', 'fontproperties': my_font}
)
for t in l_text:
t.set_fontproperties(my_font)
plt.axis("equal")
#第一个数值用于控制左右移动，值越大越向右边移动，第二个数值用于控制的上下移动，值越大越向上移动
plt.legend(loc='lower right', bbox_to_anchor=(1.1,-0.1))
plt.title(category_title+'类别数据占比', fontproperties=my_font,size=15)
plt.savefig(os.path.join(out_put,"ship_sector.jpg"))
print("####totalnum:",totalnum)
#统计目标的长宽和面积，并画出箱型图
def draw_box_length_width_area(inputfiles, out_put):
files = os.listdir(inputfiles)
# 统计不同目标的数据
for fliename in files:
txt_path = os.path.join(inputfiles, fliename)
txt_size = os.path.getsize(txt_path)
txt_f = open(txt_path, "r")
if txt_size != 0:
for line in txt_f.readlines():
split_line = line.replace("\n", "").split(" ")
category = split_line[8]
xmin = min(float(split_line[0]),float(split_line[2]),float(split_line[4]),float(split_line[6]))
ymin = min(float(split_line[1]), float(split_line[3]), float(split_line[5]), float(split_line[7]))
xmax = max(float(split_line[0]),float(split_line[2]),float(split_line[4]),float(split_line[6]))
ymax = max(float(split_line[1]), float(split_line[3]), float(split_line[5]), float(split_line[7]))
assert (xmax-xmin) >= 0, "w的值小于0"
w=round((xmax-xmin),3)
assert (ymax - ymin) >= 0, "h的值小于0"
h=round((ymax - ymin),3)
#category_label = dict_category[category]
category_label =category
area=round(w*h,3)
if category_label in totalnum.keys():
totalnum_wh_area[category_label]['w'].append(w)
totalnum_wh_area[category_label]['h'].append(h)
totalnum_wh_area[category_label]['area'].append(area)
else:
print("####category is not inputfiles:", inputfiles, category_label)
else:
print ("###txt_path_size is 0:", txt_path)
#print ("#####totalnum_wh_area:",totalnum_wh_area)
#画w,h的箱型图
#拿取出箱型图的数据
key_list = []
val_w_list = []
val_h_list = []
val_area_list = []
for key in totalnum_wh_area.keys():
key_list.append(key)
for key_ in totalnum_wh_area[key].keys():
if key_ =='w':
val_w_list.append(totalnum_wh_area[key][key_])
elif key_ == 'h':
val_h_list.append(totalnum_wh_area[key][key_])
elif key_ == 'area':
val_area_list.append(totalnum_wh_area[key][key_])
else:
print ("key_ is not exit")
#area画图
plt.figure(1)
fig, ax = plt.subplots(figsize=(8, 6))
my_font = font_manager.FontProperties(
fname="/data/xxx/PycharmProjects/object_detection_tool/image_label_data_convert/STLITI.TTF")
plt.xlabel("类别", fontproperties=my_font, size=10)
plt.ylabel("area像素点(个)", fontproperties=my_font, size=10)
plt.title(category_title+"_area数据统计", fontproperties=my_font, size=15)
data=val_area_list
labels=key_list
ax.boxplot(data)
ax.set_xticklabels(labels,fontproperties=my_font, size=10,rotation=-60)
fig.savefig(os.path.join(out_put, "ship_aera_box.jpg"))
plt.close(1)
#绘制w,h
plt.figure(2)
fig, ax = plt.subplots(figsize=(8,6))
my_font = font_manager.FontProperties(
fname="/data/xxx/PycharmProjects/object_detection_tool/image_label_data_convert/STLITI.TTF")
plt.xlabel("类别", fontproperties=my_font, size=10)
plt.ylabel("w像素点(个)", fontproperties=my_font, size=10)
plt.title(category_title+"_w数据统计", fontproperties=my_font, size=15)
data = val_w_list
labels = key_list
ax.boxplot(data)
ax.set_xticklabels(labels, fontproperties=my_font, size=10,rotation=-60)
fig.savefig(os.path.join(out_put, "ship_w_box.jpg"))
plt.close(2)
plt.figure(3)
fig, ax = plt.subplots(figsize=(8, 6))
my_font = font_manager.FontProperties(
fname="/data/xxx/PycharmProjects/object_detection_tool/image_label_data_convert/STLITI.TTF")
plt.xlabel("类别", fontproperties=my_font, size=10)
plt.ylabel("h像素点", fontproperties=my_font, size=10)
plt.title(category_title+"_h数据统计", fontproperties=my_font, size=15)
data = val_h_list
labels = key_list
ax.boxplot(data)
ax.set_xticklabels(labels, fontproperties=my_font, size=10,rotation=-60)
fig.savefig(os.path.join(out_put, "ship_h_box.jpg"))
plt.close(3)
if __name__=="__main__":
input_dota_txt="" #具体HBB数据格式的文件夹地址
out_put="" #生成图片的保存地址
draw_totalnum(input_dota_txt,out_put)
draw_box_length_width_area(input_dota_txt,out_put)
print ("finished!!!!")