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import json
import random
def get_qa_type(question):
question_type = "other"
if "how did the camera" in question.lower() or "is the camera moving" in question.lower():
question_type = "action_sequence"
if ("need to go" in question.lower()):
question_type = "goal_aim"
if "any of the objects in the initial" in question.lower():
question_type = "obj_movement"
if "if i" in question.lower():
question_type = "action_consequence"
if 'if i move to the' in question.lower() or "for someone at the" in question.lower():
question_type = "perspective"
return question_type
def convert_to_conversation(json_data):
for item in json_data:
question = item["question"]
answers = item["answers"]
correct_answer = item["correct_answer"]
# 更新question_type
item["question_type"] = get_qa_type(question)
# 构造human部分
prompt = question + " Answer the question using a single word or phrase."
# 处理答案选项
if len(answers) > 1:
ans_choice_order = answers.copy()
ans_choice_order = ['"' + ans + '"' for ans in ans_choice_order]
random.shuffle(ans_choice_order)
answer_choices_format = " or ".join(ans_choice_order)
if answer_choices_format != "":
prompt += f" Choose between the following options: {answer_choices_format}."
# 添加conversations字段到原数据
item["conversations"] = [
{
"from": "human",
"value": prompt
},
{
"from": "gpt",
"value": correct_answer
}
]
return json_data
# 读取JSON文件
def process_json_file(input_file, output_file):
with open(input_file, 'r', encoding='utf-8') as f:
data = json.load(f)
# 转换为conversations格式
enhanced_data = convert_to_conversation(data)
# 保存结果
with open(output_file, 'w', encoding='utf-8') as f:
json.dump(enhanced_data, f, ensure_ascii=False, indent=2)
print(f"已处理 {len(enhanced_data)} 条数据，结果保存到 {output_file}")
# 使用示例
if __name__ == "__main__":
# 如果要处理文件，取消注释下面的行
process_json_file('train_data.json', 'train_data_convs.json')
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