File size: 2,455 Bytes
61e8d5c 0efc9e6 61e8d5c 0efc9e6 61e8d5c |
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 |
import csv as csv_module
import json
from pathlib import Path
import tqdm
ROOT = "./labels"
ANNOTATION_FREQ = 100 # ms per frame
LABEL_MAPPING = {
"0": "Female speech",
"1": "Male speech",
"2": "Clapping",
"3": "Telephone",
"4": "Laughter",
"5": "Domestic sounds",
"6": "Footsteps",
"7": "Door",
"8": "Music",
"9": "Musical instrument",
"10": "Water tap",
"11": "Bell",
"12": "Knock",
}
def get_csvs(root):
metadata_root = Path(root)
assert metadata_root.exists(), "Metadata root does not exist"
metadata_files = list(sorted(metadata_root.glob("*/*.csv")))
splits = {}
for file in metadata_files:
file = str(file.absolute())
file_name, folder = file.split("/")[-1].replace(".csv", ""), file.split("/")[-2]
splits.setdefault(folder, []).append(file_name)
assert len(metadata_files) > 0, "Folder does not contain any csv files"
return metadata_files, splits
def process_csv(csv_path):
path = Path(csv_path)
assert path.exists(), f"CSV Path {csv_path} does not exist"
# Load all rows from CSV and group by label (ignoring source)
data = []
with open(path, newline='') as csvfile:
reader = csv_module.reader(csvfile, delimiter=',')
for row in reader:
if len(row) >= 2: # At minimum we need frame and class
frame_idx = int(row[0])
class_idx = int(row[1])
label = LABEL_MAPPING[str(class_idx)]
data.append({
"label": label,
"start": float(frame_idx * ANNOTATION_FREQ),
"end": float((frame_idx + 1) * ANNOTATION_FREQ)
})
return data
def map_to_splits(audios, fold_to_split):
fold_data = {k : {} for k in fold_to_split}
for k, file_names in fold_to_split.items():
for file_name in file_names:
fold_data[k][file_name + ".wav"] = audios[file_name]
return fold_data
if __name__ == "__main__":
csvs, splits = get_csvs(ROOT)
folds = {}
for i in tqdm.tqdm(csvs):
file_name = i.stem
folds[file_name] = process_csv(i)
json_files = map_to_splits(folds, splits)
done = set()
for data in splits.keys():
if data in done:
continue
with open(data + ".json", "w") as js_file:
json.dump(json_files[data], js_file, indent=4)
done.add(data) |