如何使用Python将文本添加到多个图像

I am new to using Python and I have a problem that I can not solve. What I am trying to do is that from an excel spreadsheet that contains three columns (address of the image, text 1, and text 2 respectively), the code should select the first image and then insert text 1 and 2 that belongs to its row. I was able to complete the code for a single image, but I encounter a problem when I try to process all the images.

我是使用Python的新手,我遇到了一个无法解决的问题。我想要做的是从excel电子表格包含三列(图像的地址,文本1和文本2),代码应选择第一个图像,然后插入属于其行的文本1和2 。我能够完成单个图像的代码,但是当我尝试处理所有图像时遇到问题。

import pandas as pd
from PIL import ImageFont
from PIL import Image
from PIL import ImageDraw

ruta_excel = pd.read_excel('C:/Users/san_2/Documents/Script/ARCPY/Direc.xls',
                           sheet_name=0)
ruta = ruta_excel.iat[0, 0]

image_files = Image.open(ruta)
font_type = ImageFont.truetype('C:/Windows.old/Windows/Fonts/Arial.ttf',18)
draw = ImageDraw.Draw(image_files)
draw.text(xy=(20, 550), text=ruta_excel.iat[0, 1], fill=(255, 255, 255),
          font=font_type)
draw.text(xy=(20, 570), text=ruta_excel.iat[0, 2], fill=(255, 255, 255),
          font=font_type)

image_files.save(ruta, 'JPEG', quality=90)

Thank you

2 个解决方案

#1

I don't know PIL but if your code works for the first image and your problem is the iteration, then you can do:

我不知道PIL但是如果你的代码适用于第一个图像而你的问题是迭代,那么你可以这样做:

import pandas as pd
from PIL import ImageFont
from PIL import Image
from PIL import ImageDraw

ruta_excel=pd.read_excel('C:/Users/san_2/Documents/Script/ARCPY/Direc.xls',sheet_name=0)
# iterate over rows with itertuples
for row in ruta_excel.itertuples(index=False):
    print (row) # to help you see what is happening but not necessary after
    # row is tuple, doing row[0] access to the first item (the first column)
    ruta=row[0]
    image_files = Image.open(ruta)
    font_type = ImageFont.truetype('C:/Windows.old/Windows/Fonts/Arial.ttf',18)
    draw = ImageDraw.Draw(image_files)
    # here you use row[1] and row[2]
    draw.text(xy=(20,550),text= row[1],fill=(255,255,255),font=font_type)
    draw.text(xy=(20,570),text= row[2],fill=(255,255,255),font=font_type)

    image_files.save(ruta, 'JPEG', quality=90)

#2

What you need to do is to loop over the items found by pd.read_excel. This function returns a DataFrame so you can use one of its three built-in iterators: itertuples, iteritems or iterrows.

您需要做的是遍历pd.read_excel找到的项目。此函数返回一个DataFrame,因此您可以使用其三个内置迭代器之一:itertuples,iteritems或iterrows。

Given this example XLS:

鉴于此示例XLS:

|   | A              | B            | C             |
| - | -------------- |--------------| --------------|
| 1 | /a/file/path/1 | first text 1 | second text 1 |
| 2 | /a/file/path/2 | first text 2 | second text 2 |
| 3 | /a/file/path/3 | first text 3 | second text 3 |
| 4 | /a/file/path/4 | first text 4 | second text 4 |
| 5 | /a/file/path/5 | first text 5 | second text 5 |

When reading the file with pandas and you have no header row in the XLS, you should specify header=None and provide the column names within names. If you have a header row and it is the first row of the XLS, just pass header=0 and omit names. By ensuring that you can map each column to a column name, you can work with itertuples which for your usecase is the best suited method - you can access the row values by their column names within the loop:

使用pandas读取文件并且XLS中没有标题行时,应指定header = None并在名称中提供列名称。如果您有一个标题行并且它是XLS的第一行,只需传递header = 0并省略名称。通过确保您可以将每个列映射到列名,您可以使用itertuples,对于您的usecase是最合适的方法 - 您可以通过循环中的列名访问行值:

import pandas as pd

exc = pd.read_excel('file_text_map.xlsx', header=None, names=('file_path', 'text1', 'text2',))

for row in exc.itertuples(index=False):
  print('file_path:', row.file_path, ', text1:', row.text1, ', text2:', row.text2)

Which will result in

这将导致

file_path: /a/file/path/1 , text1: first text 1 , text2: second text 1
file_path: /a/file/path/2 , text1: first text 2 , text2: second text 2
file_path: /a/file/path/3 , text1: first text 3 , text2: second text 3
file_path: /a/file/path/4 , text1: first text 4 , text2: second text 4
file_path: /a/file/path/5 , text1: first text 5 , text2: second text 5

#1