| import json |
| import logging |
| import os |
| import re |
| from tqdm import tqdm |
|
|
| logger = logging.getLogger(__name__) |
| handler = logging.StreamHandler() |
| logger.addHandler(handler) |
| logger.setLevel(logging.INFO) |
|
|
| COUNTING_BASE_PROMPT = 'You should output a json string with format {"answer": a int number}.Your output should be directly parsed by json.loads function. eg.```json{"answer": 1}```.\nNow the question is:' |
| RELATION_BASE_PROMPT = 'You should output a json string with format {"answer": "str"}, where str must be one of ["up", "under", "back", "front", "left", "right"]. Your output should be directly parsed by json.loads function. eg.```json{"answer": "left"}```.\nNow the question is:' |
| VALID_RELATIONS = ["up", "under", "back", "front", "left", "right"] |
| SPLIT_SYMBOL = "="*50 |
|
|
| def parse_model_answer(model_output, task_type="counting"): |
| """ |
| Parse the output JSON format answer of the model |
| :param model_output: |
| :param task_type: |
| :return: |
| """ |
| pattern = r'```json\s*(\{.*?\})\s*```' |
| match = re.search(pattern, model_output, re.DOTALL) |
| parsed_answer = None |
| if match: |
| try: |
| json_str = match.group(1) |
| result = json.loads(json_str) |
| answer = result.get('answer') |
| if task_type == "counting": |
| if isinstance(answer, str) and answer.isdigit(): |
| parsed_answer = int(answer) |
| elif isinstance(answer, int): |
| parsed_answer = answer |
| else: |
| parsed_answer = None |
| else: |
| parsed_answer = answer if answer in VALID_RELATIONS else None |
| except Exception as e: |
| logger.error(f"{model_output};\n{str(e)}") |
| return parsed_answer |
|
|
| def eval_loop(model, dataset, process_fn, task_type="counting", **kwargs): |
| """ |
| :param dataset: |
| :param model: |
| :param process_fn: |
| :param task_type: |
| :param kwargs: |
| :return: |
| """ |
| eval_result = [] |
| for item in tqdm(dataset): |
| result = process_fn(model, item, task_type=task_type, **kwargs) |
| resp = { |
| "id": item["id"], |
| "question": item["question"], |
| "image_path": item['image_path'], |
| "model_answer": result['model_answer'], |
| "parsed_answer": result['parsed_answer'], |
| "ground_truth": item['answer'] |
| } |
| eval_item_info = f"""\n{json.dumps(resp, indent=4)}\n""" |
| logger.info(eval_item_info) |
| eval_result.append(resp) |
| return eval_result |
|
|
|
|
| def eval_pipeline(model_name, current_dir, params): |
| results = {} |
| parent_dir = os.path.split(current_dir)[0] |
| |
| print("process counting dataset...") |
| counting_data_path = os.path.join(parent_dir, 'Counting.json') |
| relations_data_path = os.path.join(parent_dir, 'Relation.json') |
| combination_data_path = os.path.join(parent_dir, 'Combination.json') |
|
|
| counting_data = json.load(open(counting_data_path, 'r', encoding='utf-8')) |
| counting_results = eval_loop(dataset=counting_data, **params) |
| results["counting_results"] = counting_results |
|
|
| |
| print("process relations dataset...") |
| relations_data = json.load(open(relations_data_path, 'r', encoding='utf-8')) |
| relations_results = eval_loop(dataset=relations_data, task_type="relation", **params) |
| results["relations_results"] = relations_results |
|
|
| |
| print("process combination dataset...") |
|
|
| combination_data = json.load(open(combination_data_path, 'r', encoding='utf-8')) |
| combination_results = eval_loop(dataset=combination_data, **params) |
| results["combination_results"] = combination_results |
|
|
| result_parent_path = os.path.join(current_dir, './result/') |
| if not os.path.exists(result_parent_path): |
| os.makedirs(result_parent_path) |
|
|
| result_path = os.path.join(result_parent_path, f'{model_name}_results.json') |
| with open(result_path, 'w', encoding='utf-8') as f: |
| json.dump(results, f, ensure_ascii=False, indent=2) |
|
|
| print(f"The process has finished. The evaluation results are saved to ./result/{model_name}_results.json") |
| print(f"The number of counting samples processed successfully: {len(results['counting_results'])}") |
| print(f"The number of relationship samples processed successfully: {len(results['relations_results'])}") |
| print(f"The number of combination samples processed successfully: {len(results['combination_results'])}") |
