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Python3 compatibility and VQA 2.0 Dataset #36

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Python3 compatibility and VQA 2.0 Dataset #36

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18ba418
preprocessing code updated for Python 3 and VQA2
varunagrawal Jul 26, 2018
99e0fe1
updated to Python 3
varunagrawal Jul 26, 2018
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68 changes: 31 additions & 37 deletions data/vqa_preprocessing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,25 +12,25 @@
import argparse

def download_vqa():
os.system('wget http://visualqa.org/data/mscoco/vqa/Questions_Train_mscoco.zip -P zip/')
os.system('wget http://visualqa.org/data/mscoco/vqa/Questions_Val_mscoco.zip -P zip/')
os.system('wget http://visualqa.org/data/mscoco/vqa/Questions_Test_mscoco.zip -P zip/')
os.system('wget http://visualqa.org/data/mscoco/vqa/v2_Questions_Train_mscoco.zip -P zip/')
os.system('wget http://visualqa.org/data/mscoco/vqa/v2_Questions_Val_mscoco.zip -P zip/')
os.system('wget http://visualqa.org/data/mscoco/vqa/v2_Questions_Test_mscoco.zip -P zip/')

# Download the VQA Annotations
os.system('wget http://visualqa.org/data/mscoco/vqa/Annotations_Train_mscoco.zip -P zip/')
os.system('wget http://visualqa.org/data/mscoco/vqa/Annotations_Val_mscoco.zip -P zip/')
os.system('wget http://visualqa.org/data/mscoco/vqa/v2_Annotations_Train_mscoco.zip -P zip/')
os.system('wget http://visualqa.org/data/mscoco/vqa/v2_Annotations_Val_mscoco.zip -P zip/')


# Unzip the annotations
os.system('unzip zip/Questions_Train_mscoco.zip -d annotations/')
os.system('unzip zip/Questions_Val_mscoco.zip -d annotations/')
os.system('unzip zip/Questions_Test_mscoco.zip -d annotations/')
os.system('unzip zip/Annotations_Train_mscoco.zip -d annotations/')
os.system('unzip zip/Annotations_Val_mscoco.zip -d annotations/')
os.system('unzip zip/v2_Questions_Train_mscoco.zip -d annotations/')
os.system('unzip zip/v2_Questions_Val_mscoco.zip -d annotations/')
os.system('unzip zip/v2_Questions_Test_mscoco.zip -d annotations/')
os.system('unzip zip/v2_Annotations_Train_mscoco.zip -d annotations/')
os.system('unzip zip/v2_Annotations_Val_mscoco.zip -d annotations/')


def main(params):
if params['download'] == 'True':
if params.download:
download_vqa()

'''
Expand All @@ -41,14 +41,14 @@ def main(params):
test = []
imdir='%s/COCO_%s_%012d.jpg'

if params['split'] == 1:
if params.split == 1:

print 'Loading annotations and questions...'
train_anno = json.load(open('annotations/mscoco_train2014_annotations.json', 'r'))
val_anno = json.load(open('annotations/mscoco_val2014_annotations.json', 'r'))
print('Loading annotations and questions...')
train_anno = json.load(open('annotations/v2_mscoco_train2014_annotations.json', 'r'))
val_anno = json.load(open('annotations/v2_mscoco_val2014_annotations.json', 'r'))

train_ques = json.load(open('annotations/MultipleChoice_mscoco_train2014_questions.json', 'r'))
val_ques = json.load(open('annotations/MultipleChoice_mscoco_val2014_questions.json', 'r'))
train_ques = json.load(open('annotations/v2_OpenEnded_mscoco_train2014_questions.json', 'r'))
val_ques = json.load(open('annotations/v2_OpenEnded_mscoco_val2014_questions.json', 'r'))

subtype = 'train2014'
for i in range(len(train_anno['annotations'])):
Expand All @@ -57,9 +57,8 @@ def main(params):
image_path = imdir%(subtype, subtype, train_anno['annotations'][i]['image_id'])

question = train_ques['questions'][i]['question']
mc_ans = train_ques['questions'][i]['multiple_choices']

train.append({'ques_id': question_id, 'img_path': image_path, 'question': question, 'MC_ans': mc_ans, 'ans': ans})
train.append({'ques_id': question_id, 'img_path': image_path, 'question': question, 'ans': ans})

subtype = 'val2014'
for i in range(len(val_anno['annotations'])):
Expand All @@ -68,17 +67,16 @@ def main(params):
image_path = imdir%(subtype, subtype, val_anno['annotations'][i]['image_id'])

question = val_ques['questions'][i]['question']
mc_ans = val_ques['questions'][i]['multiple_choices']

test.append({'ques_id': question_id, 'img_path': image_path, 'question': question, 'MC_ans': mc_ans})
test.append({'ques_id': question_id, 'img_path': image_path, 'question': question, 'ans': ans})
else:
print 'Loading annotations and questions...'
print('Loading annotations and questions...')
train_anno = json.load(open('annotations/mscoco_train2014_annotations.json', 'r'))
val_anno = json.load(open('annotations/mscoco_val2014_annotations.json', 'r'))

train_ques = json.load(open('annotations/MultipleChoice_mscoco_train2014_questions.json', 'r'))
val_ques = json.load(open('annotations/MultipleChoice_mscoco_val2014_questions.json', 'r'))
test_ques = json.load(open('annotations/MultipleChoice_mscoco_test2015_questions.json', 'r'))
train_ques = json.load(open('annotations/v2_OpenEnded_mscoco_train2014_questions.json', 'r'))
val_ques = json.load(open('annotations/v2_OpenEnded_mscoco_val2014_questions.json', 'r'))
test_ques = json.load(open('annotations/v2_OpenEnded_mscoco_test2015_questions.json', 'r'))

subtype = 'train2014'
for i in range(len(train_anno['annotations'])):
Expand All @@ -87,9 +85,8 @@ def main(params):
image_path = imdir%(subtype, subtype, train_anno['annotations'][i]['image_id'])

question = train_ques['questions'][i]['question']
mc_ans = train_ques['questions'][i]['multiple_choices']

train.append({'ques_id': question_id, 'img_path': image_path, 'question': question, 'MC_ans': mc_ans, 'ans': ans})
train.append({'ques_id': question_id, 'img_path': image_path, 'question': question, 'ans': ans})

subtype = 'val2014'
for i in range(len(val_anno['annotations'])):
Expand All @@ -98,21 +95,19 @@ def main(params):
image_path = imdir%(subtype, subtype, val_anno['annotations'][i]['image_id'])

question = val_ques['questions'][i]['question']
mc_ans = val_ques['questions'][i]['multiple_choices']

train.append({'ques_id': question_id, 'img_path': image_path, 'question': question, 'MC_ans': mc_ans, 'ans': ans})
train.append({'ques_id': question_id, 'img_path': image_path, 'question': question, 'ans': ans})

subtype = 'test2015'
for i in range(len(test_ques['questions'])):
question_id = test_ques['questions'][i]['question_id']
image_path = imdir%(subtype, subtype, test_ques['questions'][i]['image_id'])

question = test_ques['questions'][i]['question']
mc_ans = test_ques['questions'][i]['multiple_choices']

test.append({'ques_id': question_id, 'img_path': image_path, 'question': question, 'MC_ans': mc_ans})
test.append({'ques_id': question_id, 'img_path': image_path, 'question': question})

print 'Training sample %d, Testing sample %d...' %(len(train), len(test))
print('Training sample %d, Testing sample %d...' %(len(train), len(test)))

json.dump(train, open('vqa_raw_train.json', 'w'))
json.dump(test, open('vqa_raw_test.json', 'w'))
Expand All @@ -122,14 +117,13 @@ def main(params):
parser = argparse.ArgumentParser()

# input json
parser.add_argument('--download', default='False', help='Download and extract data from VQA server')
parser.add_argument('--download', action='store_true', default=False, help='Download and extract data from VQA server')
parser.add_argument('--split', default=1, type=int, help='1: train on Train and test on Val, 2: train on Train+Val and test on Test')

args = parser.parse_args()
params = vars(args)
print 'parsed input parameters:'
print json.dumps(params, indent = 2)
main(params)
print('parsed input parameters:')
print(json.dumps(vars(args), indent = 2))
main(args)



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