Python





```python
yum whatprovides */lspci
yum install pciutils
```

这样就能：

```python
lspci  | grep -i vga
```

没有可用软件包 lspci yum install pciutils

Python





```python
img = cv2.imread(os.path.join(filepath, name))
dst = cv2.resize(img, (img.shape[1]//4, img.shape[0]//4))
cv2.imwrite(os.path.join(aimpath, "image" + str(num).zfill(6)) + ".jpg", dst)
```

Python opencv 图像缩放

Python tsfresh 自动计算大量的时间序列特征

[https://zhuanlan.zhihu.com/p/99069186](https://zhuanlan.zhihu.com/p/99069186)

LightGBM 决策树 gradient boosting framework

图片文件如果相同，md5是一样的。于是利用此进行图片去重。





```python
import os
import hashlib
def get_md5(file):
    file = open(file, 'rb')
    md5 = hashlib.md5(file.read())
    file.close()
    md5_values = md5.hexdigest()
    return md5_values
file_path =  r"D:\Users\Administrator\Desktop\smokingsig\yolov5k\images"
os.chdir(file_path)
file_list = os.listdir(file_path)
md5_list = []
for file in file_list:
    md5 = get_md5(file)
    if md5 not in md5_list:
        md5_list.append(md5)
    else:
        os.remove(file)
```

相似度  计算量非常大，不太好用：
```python
# -*- encoding=utf-8 -*-
import cv2
import os
class dup_picture:
    def __init__(self):
        self.orb = cv2.ORB_create()
        self.bf = cv2.BFMatcher(cv2.NORM_HAMMING)
    def get_pic_desc(self, img1_path: str):
        img1 = cv2.imread(img1_path, cv2.IMREAD_GRAYSCALE)
        kp1, des1 = self.orb.detectAndCompute(img1, None)
        return des1
    def get_similary(self, des1, des2):
        # knn筛选结果
        matches = self.bf.knnMatch(des1, trainDescriptors=des2, k=2)
        # 查看最大匹配点数目
        good = [m for (m, n) in matches if m.distance < 0.75 * n.distance]
        if len(matches) == 0:
            return 0
        similary = len(good) / len(matches)
        return similary
if __name__ == '__main__':
    duptool = dup_picture()
    file_path = r"D:\PycharmProjects\downloadpicture\all_smoking_picture"
    file_list = os.listdir(file_path)
    file_list = list(filter(lambda x: x.endswith(".jpg"), file_list))  # must .jpg pic
    os.chdir(file_path)
    unique_list = [duptool.get_pic_desc(file_list[0]), ]
    for k,file in enumerate(file_list[1:]):
        print(k)
        des = duptool.get_pic_desc(file)
        if des is None:
            os.remove(file)
            continue
        for des_i in unique_list:
            if duptool.get_similary(des, des_i) > 0.5:
                os.remove(file)
                print(file)
                break
        else:  # Smooth and uninterrupted execution completed
            unique_list.append(des)
```


其余labels处理：

```python
import os
imagespath = r"D:\Users\Administrator\Desktop\smokingsig\yolov5k\images"
labelspath = r"D:\Users\Administrator\Desktop\yololabels"
img_list = os.listdir(imagespath)
lab_list = os.listdir(labelspath)
# ---- read label ----> if none label ----> delete label file
for name in lab_list:
    lfile = os.path.join(labelspath, name)
    if "image" in name:
        with open(lfile, "r") as f:
            res = f.readlines()
        if len(res) == 0:
            os.remove(lfile)
# ---- read label ----> if  label str too short ----> delete label file
for name in lab_list:
    lfile = os.path.join(labelspath, name)
    if "image" in name:
        with open(lfile, "r") as f:
            res = f.readlines()
        if len(res[0]) < 3:
            os.remove(lfile)
# ---- read images names ----> if have not label file ----> delete imgfile
for name in img_list:
    if name[:-4] + ".txt" not in lab_list:
        os.remove(os.path.join(imagespath, name))
```

Python 图片去重 图片文件去重 依据相似度去重 cv2.ORB

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