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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"]
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