import os import re dir_name = os.path.dirname(os.path.abspath(__file__)) SUFFIX_FOR_VQA = {"yes_no": "Please answer Yes or No.", "multiple_choice": "Please output the letter corresponding to the correct option."} def get_scores(scores): """ Calculate various scores based on the given results. Args: scores (dict or list): A dictionary or list containing results where each result can be: - dict: {id: {"q0_i0": 1 or 0, "q0_i1": 1 or 0, "q1_i0": 1 or 0, "q1_i1": 1 or 0}, ...} - list: [[q0_i0 (1 or 0), q0_i1 (1 or 0), q1_i0 (1 or 0), q1_i1 (1 or 0)], ...] The keys "q0_i0", "q0_i1", "q1_i0", "q1_i1" represent combinations of questions and images: - "q0_i0" means question_0 on image_0 - "q0_i1" means question_0 on image_1 - "q1_i0" means question_1 on image_0 - "q1_i1" means question_1 on image_1 Returns: dict: A dictionary containing the calculated scores: - 'Acc': Average binary VQA acc - 'Q_Acc': Average question acc - 'I_Acc': Average image acc - 'G_Acc': Average group acc """ Q_Acc = 0.0 I_Acc = 0.0 Acc = 0.0 G_Acc = 0.0 num_samples = len(scores) def calculate_image_score(result): image_correct = 0 if isinstance(result, dict): if result["q0_i0"] == 1.0 and result["q1_i0"] == 0.0: image_correct += 1 if result["q1_i1"] == 1.0 and result["q0_i1"] == 0.0: image_correct += 1 elif isinstance(result, list): if result[0] == 1.0 and result[2] == 0.0: image_correct += 1 if result[3] == 1.0 and result[1] == 0.0: image_correct += 1 return image_correct def calculate_question_score(result): text_correct = 0 if isinstance(result, dict): if result["q0_i0"] == 1.0 and result["q0_i1"] == 0.0: text_correct += 1 if result["q1_i1"] == 1.0 and result["q1_i0"] == 0.0: text_correct += 1 else: if result[0] == 1.0 and result[1] == 0.0: text_correct += 1 if result[3] == 1.0 and result[2] == 0.0: text_correct += 1 return text_correct def calculate_binary_score(result): binary_score_correct = 0 if isinstance(result, dict): binary_score_correct += 1 if result["q0_i0"] == 1.0 else 0 binary_score_correct += 1 if result["q0_i1"] == 0.0 else 0 binary_score_correct += 1 if result["q1_i0"] == 0.0 else 0 binary_score_correct += 1 if result["q1_i1"] == 1.0 else 0 else: binary_score_correct += 1 if result[0] == 1.0 else 0 binary_score_correct += 1 if result[1] == 0.0 else 0 binary_score_correct += 1 if result[2] == 0.0 else 0 binary_score_correct += 1 if result[3] == 1.0 else 0 return binary_score_correct def calculate_group_score(result): group_correct = 0 if calculate_question_score(result) == 2 and calculate_image_score(result) == 2: group_correct += 1 return group_correct if isinstance(scores, dict): for _, result in scores.items(): Q_Acc += calculate_question_score(result) I_Acc += calculate_image_score(result) Acc += calculate_binary_score(result) G_Acc += calculate_group_score(result) else: for result in scores: Q_Acc += calculate_question_score(result) I_Acc += calculate_image_score(result) Acc += calculate_binary_score(result) G_Acc += calculate_group_score(result) results = {"Q_Acc": Q_Acc / float(num_samples * 2), "I_Acc": I_Acc / float(num_samples * 2), "Acc": Acc / float(num_samples * 4), "G_Acc": G_Acc / num_samples} return results def extract_answer(output_string, task_type="yes_no"): """ Extracts the answer from the output string based on the task type. Parameters: output_string (str): The output string. task_type (str): The type of task. Must be "yes_no" as CameraBench does not have "multiple_choice" questions. Returns: int: 1 if "yes" or "A" 0 if "no" or "B" -1 if no relevant answer is found. Raises a ValueError if an unsupported task_type is provided. """ def find_word_position(string, word): pattern = r"\b" + re.escape(word) + r"\b" match = re.search(pattern, string, re.IGNORECASE) if match: return match.start() return -1 if task_type != "yes_no": raise ValueError("Task type not supported. Must be 'yes_no'. CameraBench VQA only have 'yes_no' questions.") # if task_type == "yes_no": position_yes_and_a = find_word_position(output_string, "yes") position_no_and_b = find_word_position(output_string, "no") # elif task_type == "multiple_choice": # position_yes_and_a = find_word_position(output_string, "A") # position_no_and_b = find_word_position(output_string, "B") if position_yes_and_a == -1 and position_no_and_b == -1: print(f"No answer found in the output string: {output_string}.") return -1 elif position_yes_and_a != -1 and position_no_and_b != -1: return 1 if position_yes_and_a < position_no_and_b else 0 else: return 0 if position_yes_and_a == -1 else 1 def cambench_doc_to_visual(doc): try: default_path = os.path.join(os.getenv("HOME"), ".cache/huggingface") load_path = os.path.expanduser(os.path.join(os.getenv("HF_HOME", default_path), "camerabench_vqa/datasets--chancharikm--camerabench_vqa_lmms_eval/snapshots")) if not os.path.exists(load_path): raise FileNotFoundError(f"Dataset path not found: {load_path}") snapshots = os.listdir(load_path) if not snapshots: raise FileNotFoundError(f"No snapshots found in: {load_path}") snapshot_path = os.path.join(load_path, snapshots[0]) video_path = os.path.join(snapshot_path, doc["Video"]) if not os.path.exists(video_path): raise FileNotFoundError(f"Video file not found: {video_path}") return [video_path] except Exception as e: eval_logger.error(f"Error constructing video path: {e}") raise def cambench_doc_to_text(doc): question = doc["Question"] question = question + " " + SUFFIX_FOR_VQA["yes_no"] # if doc["Question_Type"] == "yes_no": # question = question + " " + SUFFIX_FOR_VQA["yes_no"] # elif doc["Question_Type"] == "multiple_choice": # question = question + " " + SUFFIX_FOR_VQA["multiple_choice"] return question def cambench_process_results(doc, results): """ Args: doc: a instance of the eval dataset results: [pred] Returns: a dictionary with key: metric name (in this case mme score), value: metric value """ pred = results[0] # type = doc["Question_Type"] gt_ans = extract_answer(pred, task_type="yes_no") return { "cambench_G_ACC": {"id": doc["Index"], "score": gt_ans}, "cambench_Q_ACC": {"id": doc["Index"], "score": gt_ans}, "cambench_I_ACC": {"id": doc["Index"], "score": gt_ans}, "cambench_ACC": {"id": doc["Index"], "score": gt_ans}, } def cambench_aggregate_results_G_ACC(results): """ Args: results: a list of values returned by process_results Returns: A score """ assert len(results) == 1900 * 4 answers = {} number_answered_samples = len(results) // 4 for i in range(number_answered_samples): assert int(results[i * 4]["id"]) == i * 4 assert int(results[i * 4 + 1]["id"]) == i * 4 + 1 assert int(results[i * 4 + 2]["id"]) == i * 4 + 2 assert int(results[i * 4 + 3]["id"]) == i * 4 + 3 answers[i] = {"q0_i0": results[i * 4]["score"], "q0_i1": results[i * 4 + 1]["score"], "q1_i0": results[i * 4 + 2]["score"], "q1_i1": results[i * 4 + 3]["score"]} scores = get_scores(answers) # eval_logger.info(f"G_Acc: {scores["G_Acc"]:.2f}") return scores["G_Acc"] def cambench_aggregate_results_Q_ACC(results): """ Args: results: a list of values returned by process_results Returns: A score """ assert len(results) == 1900 * 4 answers = {} number_answered_samples = len(results) // 4 for i in range(number_answered_samples): assert int(results[i * 4]["id"]) == i * 4 assert int(results[i * 4 + 1]["id"]) == i * 4 + 1 assert int(results[i * 4 + 2]["id"]) == i * 4 + 2 assert int(results[i * 4 + 3]["id"]) == i * 4 + 3 answers[i] = {"q0_i0": results[i * 4]["score"], "q0_i1": results[i * 4 + 1]["score"], "q1_i0": results[i * 4 + 2]["score"], "q1_i1": results[i * 4 + 3]["score"]} scores = get_scores(answers) # eval_logger.info(f"Q_Acc: {scores["Q_Acc"]:.2f}") return scores["Q_Acc"] def cambench_aggregate_results_I_ACC(results): """ Args: results: a list of values returned by process_results Returns: A score """ assert len(results) == 1900 * 4 answers = {} number_answered_samples = len(results) // 4 for i in range(number_answered_samples): assert int(results[i * 4]["id"]) == i * 4 assert int(results[i * 4 + 1]["id"]) == i * 4 + 1 assert int(results[i * 4 + 2]["id"]) == i * 4 + 2 assert int(results[i * 4 + 3]["id"]) == i * 4 + 3 answers[i] = {"q0_i0": results[i * 4]["score"], "q0_i1": results[i * 4 + 1]["score"], "q1_i0": results[i * 4 + 2]["score"], "q1_i1": results[i * 4 + 3]["score"]} scores = get_scores(answers) # eval_logger.info(f"I_Acc: {scores["I_Acc"]:.2f}") return scores["I_Acc"] def cambench_aggregate_results_ACC(results): """ Args: results: a list of values returned by process_results Returns: A score """ assert len(results) == 1900 * 4 answers = {} number_answered_samples = len(results) // 4 for i in range(number_answered_samples): assert int(results[i * 4]["id"]) == i * 4 assert int(results[i * 4 + 1]["id"]) == i * 4 + 1 assert int(results[i * 4 + 2]["id"]) == i * 4 + 2 assert int(results[i * 4 + 3]["id"]) == i * 4 + 3 answers[i] = {"q0_i0": results[i * 4]["score"], "q0_i1": results[i * 4 + 1]["score"], "q1_i0": results[i * 4 + 2]["score"], "q1_i1": results[i * 4 + 3]["score"]} scores = get_scores(answers) # eval_logger.info(f"Acc: {scores["Acc"]:.2f}") return scores["Acc"]