Saving Info from CSV to Text

Question

I've a dataframe as follows:

image_id  x   y    w   h   x_center  y_center img_height img_width  lable
01       500 400  250 500    309.4     543.5    2500       4000       0
01       560 430  260 570    306.7     553.4    2200       3000       0
01       540 440  270 580    387.8     563.5    2700       2000       0
02       545 340  250 590    377.8     543.5    2100       2030       1
04       546 240  240 500    367.8     553.5    2300       2000       2
04       586 270  640 400    467.8     556.5    2400       1000       2

I need to save these informatin for YOLO model type Text file for each image_id. To do that, I need to save info as

labels x_center y_center w h 

Also While saving information into text file, I need to normalize the x_center and w by the image width (img_width) and y_center and height by the image height (img_height).

My Trial

df = pd.read_csv('data.csv')
df_img_id = df.groupby('image_id')

for index, row in df_img_id:
    img_w = row['img_width']
    img_h = row['img_height']

    with open(f'{row['imgage_id']}.txt], 'w+') as f1:
        ft.write()
        f1.close()

Stuck at this point. :(

Answer 1

We can achieve it as following. Let's create a dummy data frame first.

import pandas as pd
import random

info = {
    'image_id': ['01', '01', '01', '02', '04', '04'],
    'x':random.sample(range(500, 600), 6),
    'y':random.sample(range(200, 500), 6),
    'w':random.sample(range(200, 300), 6),
    'h':random.sample(range(400, 600), 6),
    'x_center':random.sample(range(250, 460), 6),
    'y_center':random.sample(range(250, 460), 6),
    'img_height':random.sample(range(2100, 3000), 6), 
    'img_width':random.sample(range(1100, 4000), 6), 
    'labels':[0,0,0,1,2,2]
}

df = pd.DataFrame(data=info)
df.head()

--------------------------

    image_id    x    y   w  h   x_center  y_center  img_height  img_width   labels
0     01       561  435 290 449 303        318      2105        2806         0
1     01       583  447 265 427 394        421      2338        2047         0
2     01       520  417 262 592 429        395      2947        3388         0
3     02       516  415 214 470 455        319      2649        1594         1
4     04       522  386 204 514 343        394      2847        1770         2

Next, we will groupyby the image id and iterate over each row.

df_image_id = df.groupby('image_id') # group by id

for _ , row in df_image_id:
    for _ , each in row.iterrows(): # iterate each samples within same id 
        img_w = each['img_width']  
        img_h = each['img_height']

        content = [
            each['labels'], 
            each['x_center']/each['img_width'],
            each['y_center']/each['img_height'],
            each['w']/each['img_width'],
            each['h']/each['img_height']
        ]

        id = each['image_id']
        with open(f'{id}.txt', 'a') as f1:
            f1.write(" ".join(str(x) for x in content)+ '\n')