import json import csv if __name__ == '__main__': answer_dict_file = '/system/user/publicdata/LMM_benchmarks/MMFM_challenge_final/doc-vl-eval/answer_dicts/coverted_output_test_all_datasets.json' answer_dict_w_question_phase1_file = '/system/user/publicdata/LMM_benchmarks/MMFM_challenge_final/doc-vl-eval/answer_dicts/converted_output_test_for_mixtral_eval.json' answer_dict_w_question_phase2_file = '/system/user/publicdata/LMM_benchmarks/MMFM_challenge_final/doc-vl-eval/answer_dicts/converted_output_test_private_for_mixtral_eval.json' solution_file = 'MMFM_Challenge_solution.csv' category_to_sample_ids_dict_file = 'category_to_sample_ids_dict.json' answer_dict_for_mixtral_eval_file = 'answer_dict_for_mixtral_eval.json' header = ['id', 'pred', 'split'] # id is in format docvqa_docvqa_0_4 # answer_dict = {} with open(answer_dict_file, 'r') as f: answer_dict = json.load(f) # 2000 samples, 200 samples x 10 datasets answer_dict_w_question_phase1 = json.load(open(answer_dict_w_question_phase1_file)) # 800(=200*4) samples answer_dict_w_question_phase2 = json.load(open(answer_dict_w_question_phase2_file)) # 200+400+428=1028 samples answer_dict = {**answer_dict, **answer_dict_w_question_phase2} answer_dict_w_question = {**answer_dict_w_question_phase1, **answer_dict_w_question_phase2} category_to_sample_ids_dict = {} answer_dict_for_mixtral_eval = {} datasets_w_mixtral_eval_phase1 = ['docvqa', 'infographicvqa', 'websrc', 'wtq'] datasets_w_mixtral_eval_phase2 = ['mydoc', 'mychart', 'myinfographic'] long_key_to_short_key_in_answer_dict = {} short_key_to_long_key_in_answer_dict = {} for sample_key in answer_dict.keys(): short_key = '_'.join( sample_key.split('_')[:-1]) long_key_to_short_key_in_answer_dict.update({sample_key: short_key}) short_key_to_long_key_in_answer_dict.update({short_key: sample_key}) long_key_to_short_key_in_answer_dict_w_question = {} short_key_to_long_key_in_answer_dict_w_question = {} for sample_key in answer_dict_w_question.keys(): short_key = '_'.join( sample_key.split('_')[:-1]) long_key_to_short_key_in_answer_dict_w_question.update({sample_key: short_key}) short_key_to_long_key_in_answer_dict_w_question.update({short_key: sample_key}) with open(solution_file, 'w', newline='') as f: writer = csv.writer(f) writer.writerow(header) dataset_counter_dict = {} for sample_key, data_dict in answer_dict.items(): items = sample_key.split('_') id_ = '_'.join(items[:-1]) if items[0] in datasets_w_mixtral_eval_phase2: category = items[0] else: if items[0] == items[1]: category = items[0] else: category = items[0] + '_' + items[1] if category not in category_to_sample_ids_dict: category_to_sample_ids_dict[category] = [] if category not in dataset_counter_dict: dataset_counter_dict[category] = 0 # id_ = f'{category}_{dataset_counter_dict[category]}' category_to_sample_ids_dict[category].append(id_) # write to the solution file writer.writerow([id_, data_dict['ground_truth'], 'public']) if category in datasets_w_mixtral_eval_phase1 + datasets_w_mixtral_eval_phase2: short_key = long_key_to_short_key_in_answer_dict[sample_key] sample_key_w_question = short_key_to_long_key_in_answer_dict_w_question[short_key] answer_dict_for_mixtral_eval.update({ id_: { "question_type": "short-answer", "ground_truth": answer_dict_w_question[sample_key_w_question]['ground_truth'], 'question': answer_dict_w_question[sample_key_w_question]['question'], "dataset": category, } }) dataset_counter_dict[category] += 1 with open(category_to_sample_ids_dict_file, 'w') as f: json.dump(category_to_sample_ids_dict, f) with open(answer_dict_for_mixtral_eval_file, 'w') as f: json.dump(answer_dict_for_mixtral_eval, f)