Convert all images in a pandas dataframe column to grayscale-CodePudding

I have a column of a pandas dataframe with 25 thousand images, and I want to convert the color of all of them to grayscale. What would be the simplest way to do this?

I know how to convert the color, which I must use a loop and do the conversion with numpy or opencv, but I don't know how to do this loop with a column of the dataframe.

CodePudding user response：

One way to convert the color of images in a pandas dataframe is to use the apply method on the column containing the image data. This method allows you to apply a custom function to each element of the column.

For example, if your dataframe has a column called 'images' containing the image data, you could convert the color of the images to grayscale using the following code:

def grayscale(image):
  return cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

df['images'] = df['images'].apply(grayscale)

CodePudding user response：

One way to loop through the images in the column and convert them to grayscale would be to use the apply method of the pandas dataframe. Here is an example:

import numpy as np
import cv2

# Convert an image to grayscale
def to_grayscale(image):
  return cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# Loop through the images in the column and convert them to grayscale
df['grayscale_images'] = df['images'].apply(to_grayscale)

This code will apply the to_grayscale function to each image in the images column of the dataframe, and store the resulting grayscale images in a new column called grayscale_images.

Alternatively, you could also use a for loop to iterate through the rows of the dataframe and convert the images in the images column to grayscale. Here is an example:

import numpy as np
import cv2

# Create a new column for the grayscale images
df['grayscale_images'] = np.nan

# Loop through the rows of the dataframe
for i, row in df.iterrows():
  # Convert the image to grayscale
  grayscale_image = cv2.cvtColor(row['images'], cv2.COLOR_BGR2GRAY)
  # Store the grayscale image in the new column
  df.at[i, 'grayscale_images'] = grayscale_image

Both of these approaches will loop through the images in the images column and convert them to grayscale.