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import os
import Augmentor
tasks = ["1", "2", "3", "4", "5", "6"]
for task in tasks:
# Loop through all folders in Task 1 and generate augmented images for each class
for i in os.listdir("data/train/raw/Task " + task):
if i != ".DS_Store":
print("Augmenting images in class: ", i)
p = Augmentor.Pipeline(f"data/train/raw/Task {task}/{i}", output_directory=i, save_format="png")
p.rotate(probability=0.8, max_left_rotation=5, max_right_rotation=5)
p.flip_left_right(probability=0.8)
p.zoom_random(probability=0.8, percentage_area=0.8)
p.flip_top_bottom(probability=0.8)
p.random_brightness(probability=0.8, min_factor=0.5, max_factor=1.5)
p.random_contrast(probability=0.8, min_factor=0.5, max_factor=1.5)
p.random_color(probability=0.8, min_factor=0.5, max_factor=1.5)
# Generate 100 - total of original images so that the total number of images in each class is 100
p.sample(100 - len(p.augmentor_images))
# Move the folder to data/train/Task 1/augmented
# Create the folder if it does not exist
if not os.path.exists(f"data/train/augmented/Task {task}/"):
os.makedirs(f"data/train/augmented/Task {task}/")
# Move all images in the data/train/Task 1/i folder to data/train/Task 1/augmented/i
os.rename(
f"data/train/raw/Task {task}/{i}/{i}",
f"data/train/augmented/Task {task}/{i}",
)
# Rename all the augmented images to [01, 02, 03]
number = 0
for j in os.listdir(f"data/train/augmented/Task {task}/{i}"):
number = int(number) + 1
if len(str(number)) == 1:
number = "0" + str(number)
os.rename(
f"data/train/augmented/Task {task}/{i}/{j}",
f"data/train/augmented/Task {task}/{i}/{number}.png",
)
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