如果名称图像与 Python 中 csv 文件中的 image_id 匹配，则从文件夹中裁剪多张图像

Question

I have got a list of about 300 image_id and bounding box position in a csv file. I also have a folder of about 300 images with each image id matching the name of each image. How do I compare the name of the image and the image_id if it matches me, I will crop it.

I use the python language and ubuntu os.

Answer 1

import os, pandas

data = pandas.read_csv(your_csv_file) #read csv file

# Get the directory of images
path = "path folder"

#Edit2 you may have to add dtype str, as pandas will assume int if you only have integers
dirs = os.listdir( path, dtype=str ) #get all files in folder

# Get all the files and split at '.' to get the names
listoffiles = []
for file in dirs:
    basename = os.path.splitext(file)[0] #this will get you the basename 
    listoffiles.append(basename)         #you will have a list of all filenames

matches = data[data['image_id'].isin(listoffiles)] #now in matches you have a table containing only rows that correspond to filenames
print(matches.head()) 

Hope this helps.

Edit: you can later iterate matches to actually do the cropping:

for index, row in matches.iterrows():
     print(row['image_id'], row['bounding_box'])
     # do cropping here

Answer 2

In my opinion you could build upon the json.loads method

In [23]: from json import loads 
    ...:  
    ...: data = '''\ 
    ...: 1693884003  {'right': 0.6428571428571429, 'bottom': 0.9761904761904762, 'top': 0.38095238095238093, 'left': 0.22857142857142856} 
    ...: 1693884030  {'right': 0.6571428571428571, 'bottom': 0.9285714285714286, 'top': 0.38095238095238093, 'left': 0.3142857142857143} 
    ...: 1735837028  {'right': 0.68, 'bottom': 0.9, 'top': 0.4, 'left': 0.34} 
    ...: 1740301012  {'right': 0.6142857142857143, 'bottom': 0.9523809523809523, 'top': 0.38095238095238093, 'left': 0.35714285714285715} 
    ...: 1779624112  {'right': 0.7142857142857143, 'bottom': 0.9047619047619048, 'top': 0.5357142857142857, 'left': 0.21428571428571427}\ 
    ...: ''' 
    ...: images = {} 
    ...: for line in data.splitlines(): 
    ...:     image, bounds = line.split(' ', 1) 
    ...:     images[image] = loads(bounds.replace("'", '"')) 
    ...: from pprint import pprint 
    ...: pprint(images) 
{'1693884003': {'bottom': 0.9761904761904762,                                                                                             
                'left': 0.22857142857142856,                                                                                              
                'right': 0.6428571428571429,                                                                                              
                'top': 0.38095238095238093},                                                                                              
 '1693884030': {'bottom': 0.9285714285714286,                                                                                             
                'left': 0.3142857142857143,
                'right': 0.6571428571428571,
                'top': 0.38095238095238093},
 '1735837028': {'bottom': 0.9, 'left': 0.34, 'right': 0.68, 'top': 0.4},
 '1740301012': {'bottom': 0.9523809523809523,
                'left': 0.35714285714285715,
                'right': 0.6142857142857143,
                'top': 0.38095238095238093},
 '1779624112': {'bottom': 0.9047619047619048,
                'left': 0.21428571428571427,
                'right': 0.7142857142857143,
                'top': 0.5357142857142857}}

In [24]: 

Note that I read from a string while you will be reading from an open file,
note also that json.loads expects double quotes only as a delimiter, so we have to replace the single quotes in your data with double quotes before using json.loads .