Resize Images in Image Set and Save to New Location

Python

For images stored in a folder with filenames or IDs referenced in an accompanying csv file. Take all images, resize them and then save to a new folder.

 1|  import pandas as pd
 2|  from tqdm import tqdm
 3|  from PIL import Image  
 4|  
 5|  #Location of original images
 6|  train_path = 'data/raw/train_images/'
 7|  #Destination folder for resized images (folder must already be created)
 8|  train_dest_path = 'data/processed/train_resized_images/'
 9|  
10|  #Set new size
11|  NEW_SIZE = (255,255)
12|  
13|  #File that contains data on images. Image filename is contained in image_id field
14|  train = pd.read_csv('data/raw/train.csv')
15|  
16|  #Resize images and save to destination folder
17|  def resize_images(df, path, dest_path):
18|      for i in tqdm(range(df.shape[0])):
19|          im = Image.open(path + df['image_id'][i])
20|          im = im.resize(NEW_SIZE) 
21|          im.save(dest_path + df['image_id'][i]) 
22|  resize_images(train,train_path,train_dest_path)
detro
PIL | Resize
Did you find this snippet useful?

Sign up for free to to add this to your code library

Remove Stop Words from Text in DataFrame Column
Python

Pandas | Nltk | Nlp

133
LightGBM Custom Loss Function
Python

LightGBM | Loss function

121
Tuning XGBoost Hyperparameters with Grid Search
Python

XGBoost | Tuning

117
How to Convert DataFrame Values Into Percentages
Python

Lambda | Percentages | Pipe

109
How to Scale Data Using Standard Scaler But Keep Column Names
Python

Scaler | Standard

79
LightGBM Hyperparameter Tuning with GridSearch
Python

Python | LightGBM | Hyperparameter tuning | Gridsearch

77
Calculating Root Mean Squared Error (RMSE) with Sklearn and Python
Python

Rmse

77
Dynamically Create Columns in Pandas Dataframe
Python

Pandas | Columns

61
How to Train a Catboost Classifier with GridSearch Hyperparameter Tuning
Python

Catboost | Hyperparameter tuning

60
Overwriting a Python Logging File Instead of Appending
Python

Logging

55