# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#


import json
import string

# The paths need to be updated
visdial_train_data_file = 'visdial_0.9_train.json'
visdial_val_data_file = 'visdial_0.9_val.json'


vdtrain_questions_file = 'v2_OpenEnded_mscoco_vdtrain_questions.json'
vdval_questions_file = 'v2_OpenEnded_mscoco_vdval_questions.json'

vdtrain_annotations_file = 'v2_mscoco_vdtrain_annotations.json'
vdval_annotations_file = 'v2_mscoco_vdval_annotations.json'


translator = str.maketrans('', '', string.punctuation)

vdtrain_questions = []
vdval_questions = []
vdtrain_annotations = []
vdval_annotations = []

with open(visdial_train_data_file, 'r') as f:
    vdtrain_data = json.load(f)
    vdtrain_data_questions = vdtrain_data['data']['questions']
    vdtrain_data_answers = vdtrain_data['data']['answers']
    vdtrain_dialogs = vdtrain_data['data']['dialogs']
    count = 1
    for dialogs in vdtrain_data['data']['dialogs']:
        image_id = dialogs['image_id']
        for dialog in dialogs['dialog']:
            qid = dialog['question']
            aid = dialog['answer']
            q = vdtrain_data_questions[qid]
            a = vdtrain_data_answers[aid]
            question = {}
            annotation = {}
            question['image_id'] = image_id
            question['question_id'] = count
            question['question'] = q
            vdtrain_questions.append(question)
            a = a.translate(translator)
            a = a.lower()
            annotation['multiple_choice_answer'] = a
            annotation['question_id'] = count
            annotation['answers'] = []
            for i in range(10):
                answer = {}
                answer['answer'] = a
                answer['answer_confifence'] = 'yes'
                answer['answer_id'] = i + 1
                annotation['answers'].append(answer)
            vdtrain_annotations.append(annotation)
            count = count + 1
    print("Total qa train " + str(count))


with open(visdial_val_data_file, 'r') as f:
    vdval_data = json.load(f)
    vdval_data_questions = vdval_data['data']['questions']
    vdval_data_answers = vdval_data['data']['answers']
    vdval_dialogs = vdval_data['data']['dialogs']
    count = 1
    for dialogs in vdval_data['data']['dialogs']:
        image_id = dialogs['image_id']
        for dialog in dialogs['dialog']:
            qid = dialog['question']
            aid = dialog['answer']
            q = vdtrain_data_questions[qid]
            a = vdtrain_data_answers[aid]
            question = {}
            annotation = {}
            question['image_id'] = image_id
            question['question_id'] = count
            question['question'] = q
            vdval_questions.append(question)
            a = a.lower()
            a = a.translate(translator)
            annotation['multiple_choice_answer'] = a
            annotation['question_id'] = count
            annotation['answers'] = []
            for i in range(10):
                answer = {}
                answer['answer'] = a
                answer['answer_confifence'] = 'yes'
                answer['answer_id'] = i + 1
                annotation['answers'].append(answer)
            vdval_annotations.append(annotation)
            count = count + 1
    print("Total qa val " + str(count))

vdtrain_data = {}
vdtrain_data['questions'] = vdtrain_questions

vdval_data = {}
vdval_data['questions'] = vdval_questions

with open(vdtrain_questions_file, 'w') as f:
    json.dump(vdtrain_data, f)

with open(vdval_questions_file, 'w') as f:
    json.dump(vdval_data, f)

vdtrain_data = {}
vdtrain_data['annotations'] = vdtrain_annotations

vdval_data = {}
vdval_data['annotations'] = vdval_annotations


with open(vdtrain_annotations_file, 'w') as f:
    json.dump(vdtrain_data, f)

with open(vdval_annotations_file, 'w') as f:
    json.dump(vdval_data, f)

# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#


import json
import string

# The paths need to be updated
visdial_train_data_file = 'visdial_0.9_train.json'
visdial_val_data_file = 'visdial_0.9_val.json'


vdtrain_questions_file = 'v2_OpenEnded_mscoco_vdtrain_questions.json'
vdval_questions_file = 'v2_OpenEnded_mscoco_vdval_questions.json'

vdtrain_annotations_file = 'v2_mscoco_vdtrain_annotations.json'
vdval_annotations_file = 'v2_mscoco_vdval_annotations.json'


translator = str.maketrans('', '', string.punctuation)

vdtrain_questions = []
vdval_questions = []
vdtrain_annotations = []
vdval_annotations = []

with open(visdial_train_data_file, 'r') as f:
    vdtrain_data = json.load(f)
    vdtrain_data_questions = vdtrain_data['data']['questions']
    vdtrain_data_answers = vdtrain_data['data']['answers']
    vdtrain_dialogs = vdtrain_data['data']['dialogs']
    count = 1
    for dialogs in vdtrain_data['data']['dialogs']:
        image_id = dialogs['image_id']
        for dialog in dialogs['dialog']:
            qid = dialog['question']
            aid = dialog['answer']
            q = vdtrain_data_questions[qid]
            a = vdtrain_data_answers[aid]
            question = {}
            annotation = {}
            question['image_id'] = image_id
            question['question_id'] = count
            question['question'] = q
            vdtrain_questions.append(question)
            a = a.translate(translator)
            a = a.lower()
            annotation['multiple_choice_answer'] = a
            annotation['question_id'] = count
            annotation['answers'] = []
            for i in range(10):
                answer = {}
                answer['answer'] = a
                answer['answer_confifence'] = 'yes'
                answer['answer_id'] = i + 1
                annotation['answers'].append(answer)
            vdtrain_annotations.append(annotation)
            count = count + 1
    print("Total qa train " + str(count))


with open(visdial_val_data_file, 'r') as f:
    vdval_data = json.load(f)
    vdval_data_questions = vdval_data['data']['questions']
    vdval_data_answers = vdval_data['data']['answers']
    vdval_dialogs = vdval_data['data']['dialogs']
    count = 1
    for dialogs in vdval_data['data']['dialogs']:
        image_id = dialogs['image_id']
        for dialog in dialogs['dialog']:
            qid = dialog['question']
            aid = dialog['answer']
            q = vdtrain_data_questions[qid]
            a = vdtrain_data_answers[aid]
            question = {}
            annotation = {}
            question['image_id'] = image_id
            question['question_id'] = count
            question['question'] = q
            vdval_questions.append(question)
            a = a.lower()
            a = a.translate(translator)
            annotation['multiple_choice_answer'] = a
            annotation['question_id'] = count
            annotation['answers'] = []
            for i in range(10):
                answer = {}
                answer['answer'] = a
                answer['answer_confifence'] = 'yes'
                answer['answer_id'] = i + 1
                annotation['answers'].append(answer)
            vdval_annotations.append(annotation)
            count = count + 1
    print("Total qa val " + str(count))

vdtrain_data = {}
vdtrain_data['questions'] = vdtrain_questions

vdval_data = {}
vdval_data['questions'] = vdval_questions

with open(vdtrain_questions_file, 'w') as f:
    json.dump(vdtrain_data, f)

with open(vdval_questions_file, 'w') as f:
    json.dump(vdval_data, f)

vdtrain_data = {}
vdtrain_data['annotations'] = vdtrain_annotations

vdval_data = {}
vdval_data['annotations'] = vdval_annotations


with open(vdtrain_annotations_file, 'w') as f:
    json.dump(vdtrain_data, f)

with open(vdval_annotations_file, 'w') as f:
    json.dump(vdval_data, f)

# Copyright (c) Facebook, Inc. and its affiliates. # All rights reserved. # # This source code is licensed under the license found in the # LICENSE file in the root directory of this source tree. # # The paths need to be updated