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add progress bar #15

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add progress bar #15

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c2865db
requirements fix
Feb 6, 2023
6dd2029
add progress bar
UlkuTuncerKucuktas Feb 6, 2023
c4024af
add seed so it would create same result every tun
UlkuTuncerKucuktas Feb 6, 2023
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14 changes: 8 additions & 6 deletions cocosplit.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,9 @@
from sklearn.model_selection import train_test_split
from skmultilearn.model_selection import iterative_train_test_split
import numpy as np
from tqdm import tqdm

np.random.seed(42)

def save_coco(file, info, licenses, images, annotations, categories):
with open(file, 'wt', encoding='UTF-8') as coco:
Expand All @@ -13,14 +15,14 @@ def save_coco(file, info, licenses, images, annotations, categories):

def filter_annotations(annotations, images):
image_ids = funcy.lmap(lambda i: int(i['id']), images)
return funcy.lfilter(lambda a: int(a['image_id']) in image_ids, annotations)

filtered_annotations = funcy.lfilter(lambda a: int(a['image_id']) in image_ids, tqdm(annotations, desc='Filtering Annotations'))
return filtered_annotations

def filter_images(images, annotations):

annotation_ids = funcy.lmap(lambda i: int(i['image_id']), annotations)
filtered_images = funcy.lfilter(lambda a: int(a['id']) in annotation_ids, tqdm(images, desc='Filtering Images'))
return filtered_images

return funcy.lfilter(lambda a: int(a['id']) in annotation_ids, images)


parser = argparse.ArgumentParser(description='Splits COCO annotations file into training and test sets.')
Expand Down Expand Up @@ -67,7 +69,7 @@ def main(args):
annotations = funcy.lremove(lambda i: i['category_id'] not in annotation_categories , annotations)


X_train, y_train, X_test, y_test = iterative_train_test_split(np.array([annotations]).T,np.array([ annotation_categories]).T, test_size = 1-args.split)
X_train, y_train, X_test, y_test = iterative_train_test_split(np.array([annotations]).T,np.array([ annotation_categories]).T, test_size = 1-args.split, random_state=42)

save_coco(args.train, info, licenses, filter_images(images, X_train.reshape(-1)), X_train.reshape(-1).tolist(), categories)
save_coco(args.test, info, licenses, filter_images(images, X_test.reshape(-1)), X_test.reshape(-1).tolist(), categories)
Expand All @@ -76,7 +78,7 @@ def main(args):

else:

X_train, X_test = train_test_split(images, train_size=args.split)
X_train, X_test = train_test_split(images, train_size=args.split, random_state=42)

anns_train = filter_annotations(annotations, X_train)
anns_test=filter_annotations(annotations, X_test)
Expand Down
1 change: 1 addition & 0 deletions requirements.txt
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Expand Up @@ -2,3 +2,4 @@ sklearn
funcy
argparse
scikit-multilearn
tqdm