I have code in python:

# Create a list of image categories and their corresponding range of image indices
categories = {
    'animals': range(1, 257),
    'people': range(257, 513),
    'nature': range(513, 769),
    'food': range(769, 1025)
}

# Define the distortions and levels, and adding an 'original' distortion type
distortions = ['01', '02', '03', 'orig']
levels = ['A', 'B', 'C']

# Function to create a list of image tuples for a given category, distortion, and level
def image_combinations(category, distortion, level):
    image_indices = categories[category]
    if distortion == 'orig':
        images = [(f"{idx}_orig_{category}",) for idx in image_indices]
    else:
        images = [(f"{idx}_{distortion}_{level}_{category}",) for idx in image_indices]
    return images

all_image_combinations = []

# Create a list of all possible image combinations
for category in categories:
    for distortion in distortions:
        if distortion == 'orig':
            all_image_combinations.extend(image_combinations(category, distortion, None))
        else:
            for level in levels:
                all_image_combinations.extend(image_combinations(category, distortion, level))



I want to look at the output in R. The image names are as follows:

df$image
[1] 637_03_A_nature.jpg 649_orig_nature.jpg 549_orig_nature.jpg 557_03_A_nature.jpg 21_01_A_animals.jpg
[6] 145_03_A_animals.jpg 569_orig_nature.jpg 725_02_A_nature.jpg 941_03_C_food.jpg 341_01_B_people.jpg
[11] 225_03_A_animals.jpg 517_03_A_nature.jpg 9_01_C_animals.jpg 857_03_B_food.jpg 721_01_C_nature.jpg
[16] 417_02_C_people.jpg 721_03_B_nature.jpg 25_03_A_animals.jpg 813_01_B_food.jpg 797_03_B_food.jpg
[21] 701_03_B_nature.jpg 829_01_A_food.jpg 325_03_B_people.jpg 401_01_B_people.jpg 421_03_A_people.jpg
[26] 9_03_B_animals.jpg 413_orig_people.jpg 941_02_A_food.jpg 857_01_C_food.jpg 289_03_C_people.jpg
[31] 193_03_C_animals.jpg 229_03_B_animals.jpg 273_02_B_people.jpg 441_01_B_people.jpg 205_03_A_animals.jpg
[36] 913_03_A_food.jpg 241_01_A_animals.jpg 825_02_B_food.jpg 661_03_B_nature.jpg 381_01_B_people.jpg
[41] 13_02_A_animals.jpg 769_02_C_food.jpg 265_03_B_people.jpg 161_01_A_animals.jpg 873_01_B_food.jpg
[46] 209_01_C_animals.jpg 97_02_B_animals.jpg 817_01_C_food.jpg 925_orig_food.jpg 561_03_B_nature.jpg

Please provide R code to extract the reference, distortion, level, and category from the image filenames and save them as new variables in df.

This code is wrong:

> # Function to extract the category from the image name
> get_category <- function(image_name) {
+ category <- strsplit(image_name, “”)[[1]][4] %>%
+ gsub(“.jpg”, “”, .)
+ return(category)
+ }
>
> # Extract reference, distortion, level, and category from the image filenames
> df <- df %>%
+ mutate(
+ reference = as.numeric(sub(“.”, “”, image)),
+ distortion = gsub(“.(\d{2}|orig).”, “\1”, image),
+ level = gsub(“.(\w{0,1}).*”, “\1”, image) %>% ifelse(distortion == “orig”, NA, .),
+ category = sapply(image, get_category)
+ )
Warning message:
There was 1 warning in mutate().
ℹ In argument: reference = as.numeric(sub(".", "", image)).
Caused by warning:
! NAs introduced by coercion
>
> print(head(df))
image id reference distortion level category
1 637_03_A_nature.jpg 1 NA 3703_A_nature.jpg 3 _
2 649_orig_nature.jpg 1 NA 49orig_nature.jpg 4 _
3 549_orig_nature.jpg 1 NA 49orig_nature.jpg 4 _
4 557_03_A_nature.jpg 1 NA 5703_A_nature.jpg 5 _
5 21_01_A_animals.jpg 1 NA 2101A_animals.jpg 1 0
6 145_03_A_animals.jpg 1 NA 4503_A_animals.jpg 4 _