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File size: 2,509 Bytes
70d8fcf | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 | import os
import bisect
from dataset.msa_info_utils import (
load_msa_info,
)
from dataset.custom_types import MsaInfo
import glob
import pdb
import pandas as pd
def cal_acc(ann_info: MsaInfo | str, est_info: MsaInfo | str, post_digit: int = 3):
if type(ann_info) is str:
assert os.path.exists(ann_info), f"{ann_info} not exists"
ann_info = load_msa_info(ann_info)
if type(ann_info) is str:
assert os.path.exists(est_info), f"{est_info} not exists"
est_info = load_msa_info(est_info)
ann_info_time = [
int(round(time_, post_digit) * (10**post_digit)) for time_, label in ann_info
]
est_info_time = [
int(round(time_, post_digit) * (10**post_digit)) for time_, label in est_info
]
common_start_time = max(ann_info_time[0], est_info_time[0])
common_end_time = min(ann_info_time[-1], est_info_time[-1])
time_points = set()
time_points.add(common_start_time)
time_points.add(common_end_time)
for time_ in ann_info_time:
if time_ >= common_start_time and time_ <= common_end_time:
time_points.add(time_)
for time_ in est_info_time:
if time_ >= common_start_time and time_ <= common_end_time:
time_points.add(time_)
time_points = sorted(list(time_points))
total_duration = 0
total_score = 0
for idx in range(len(time_points) - 1):
duration = time_points[idx + 1] - time_points[idx]
ann_label = ann_info[bisect.bisect_right(ann_info_time, time_points[idx]) - 1][
1
]
est_label = est_info[bisect.bisect_right(est_info_time, time_points[idx]) - 1][
1
]
total_duration += duration
if ann_label == est_label:
total_score += duration
return total_score / total_duration
if __name__ == "__main__":
ext_paths = glob.glob("")
results = []
for ext_path in ext_paths:
try:
ann_path = os.path.join(
"",
os.path.basename(ext_path).split(".")[0] + ".txt",
)
results.append(
{
"data_id": os.path.basename(ext_path).split(".")[0],
"acc": cal_acc(
ann_info=ann_path,
est_info=ext_path,
),
}
)
except Exception as e:
print(e)
continue
df = pd.DataFrame(results)
print(df["acc"].mean())
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