python v 3.7.3
matplotlib 3.1.1
running on Google colab
I have a dataset containing 101 folders, with about 750 images per folder. I would like to randomly display 16 of these images, from any given folder. The images are organized as such:
Train directory
- folder1
- ---> image1
- ---> image2
- ---> imagen
- folder2
- ---> image1
- ---> image2
and so on.
I tried to create code that iterates through each folder and selects a random image 16 times TOTAL (not per folder).
Here is my code thus far:
import random
from PIL import Image
for folder in os.listdir(train_folder):
for image in os.listdir(train_folder + '/' + folder):
img = os.path.join(train_folder, folder, image)
#print(img)
plt.figure(1, figsize=(15, 9))
plt.axis('off')
n = 0
for i in range(16):
n += 1
random_img = random.choice(img)
imgs = imread(random_img)
plt.subplot(4, 4, n)
axis('off')
plt.imshow(imgs)
plt.show()
Here is the error:
FileNotFoundError Traceback (most recent call last)
<ipython-input-19-2f47ab853e7c> in <module>()
13 n += 1
14 random_img = random.choice(img)
---> 15 imgs = imread(random_img)
16 plt.subplot(4, 4, n)
17 #plt.subplots_adjust(hspace = 0.5, wspace = 0.5)
1 frames
/usr/local/lib/python3.6/dist-packages/PIL/Image.py in open(fp, mode)
2764
2765 if filename:
-> 2766 fp = builtins.open(filename, "rb")
2767 exclusive_fp = True
2768
FileNotFoundError: [Errno 2] No such file or directory: '6'
I am not sure where to present the argument to randomly select one of the images. I also think that the structure I am using might not be the most efficient, as it may require multiple iterations through the folders. It would be nice for it to just go through the folders once, and select 16 images. Is there an efficient way to do this in python? I do not know its limitations yet.
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