Count the number of labels in json and txt (using yolo)

---

Script function:

提示：遍历文件夹中的json文件，统计标签数量
Rendering: The category was cut off by me! ! !

Yolo Official Training Tips

• 111/ is my folder
• classes.txt is the classes file

"""
功能：
统计json文件中的类别，绘制柱形图并标记高度（每一个类别的数量）
"""
import json
import os
import matplotlib.pyplot as plt

plt.rcParams['font.sans-serif'] = ['SimHei']        #正常显示中文
plt.rcParams['axes.unicode_minus'] = False          #x,y轴的负号显示

classes_file = 'classes.txt'            # 类别文件路径
base_path = r'111/'						# json路径


read_classes = open(classes_file)
classes_dict = {
    
    }
for i in read_classes.readlines():
    classes_dict[i.replace('\n','')] = 0
print("类别数:",len(classes_dict))

def main():
    filelist = os.listdir(base_path)
    filelist.sort()                     #升序排列

    for name in filelist:
        filename = os.path.splitext(name)[0]            #文件名
        filename_suffix = os.path.splitext(name)[1]     #后缀
        try:
            if filename_suffix == '.json':
                fullname = base_path + filename + filename_suffix
                dataJson = json.load(open("{}".format(fullname),encoding='UTF-8'))
                # print("dataJson------", dataJson)
                label_name = dataJson['shapes']

                for _ in label_name:
                    classes_dict[_['label']]+=1
            else:
                pass
        except:
            pass
    print("classes_dict",classes_dict)
    fig,ax = plt.subplots(figsize=(10,8))
    plt.title("数量")
    plt.xticks(rotation = 90)       #设置x轴文字方向旋转90度
    bars = plt.bar(classes_dict.keys(),classes_dict.values())
    print("bar:",bars)
    for b in bars:
        height = b.get_height()
        ax.annotate("{}".format(height),
                    # xy控制的是，标注哪个点，x=x坐标+width/2，y=height,即柱子上平面的中间
                    xy = (b.get_x()+b.get_width() / 2,height),
                    xytext=(0,3),   #文本位置的位置，如果有textcoords,则表示是针对xy位置的偏移，否则是图中的固定位置
                    textcoords = 'offset points',   #两个选项，'offset pixels','offset pixels'
                    va = 'bottom',ha = 'center'
                    )
    plt.show()

if __name__ == '__main__':
    main()

I hope it is helpful to you, and the tag statistics of the "txt" version will be updated in the next issue! ! ! ! ! ! ! ! ! ! ! !

import matplotlib.pyplot as plt
import os
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False

cn_path=open("classes.txt")

class_dict={
    
    }
classes=[i.replace("/n","") for i in cn_path.readlines()]
print(classes)

for i in classes:
    class_dict[i]=0
print("类别数",len(class_dict))

def main():
    base_path=r"111/"
    FileList=os.listdir(base_path)
    # print("F+++",FileList)
    for file in FileList:
        if file.endswith(".txt"):
            with open(base_path+file,'r') as f:
                for i in f.readlines():
                    i=i.split(' ')
                    print(i)
                    class_dict[classes[int(i[0])]]+=1
    print(class_dict)
    fig, ax = plt.subplots(figsize=(10, 8))
    plt.title('数量')
    plt.xticks(rotation=90)     # 设置x轴文字方向旋转90度
    bars = plt.bar(class_dict.keys(), class_dict.values())
    for b in bars:
        height = b.get_height()
        ax.annotate('{}'.format(height),
                    # xy控制的是，标注哪个点，x=x坐标+width/2, y=height，即柱子上平面的中间
                    xy=(b.get_x() + b.get_width() / 2, height),
                    xytext=(0, 3), # 文本放置的位置，如果有textcoords，则表示是针对xy位置的偏移，否则是图中的固定位置
                    textcoords="offset points", # 两个选项 'offset pixels'，'offset pixels'
                    va='bottom', ha='center'# 代表verticalalignment 和horizontalalignment，控制水平对齐和垂直对齐。
        )
    plt.show()

if __name__ == '__main__':
    main()

Before training, be sure to do a good job of label statistics to ensure that the data is balanced