def prepro_signal():
print('Preprocessing signal')
# Load data
fpaths, texts, _ = data.read_meta(os.path.join(args.data_path, args.meta))
# Creates folders
if not os.path.exists(os.path.join(args.data_path, args.mel_dir)):
os.mkdir(os.path.join(args.data_path, args.mel_dir))
if not os.path.exists(os.path.join(args.data_path, args.mag_dir)):
os.mkdir(os.path.join(args.data_path, args.mag_dir))
# Creates pool
p = Pool(NUM_JOBS)
total_files = len(fpaths)
with tqdm(total=total_files) as pbar:
for _ in tqdm(p.imap_unordered(f, list(zip(fpaths, texts)))):
pbar.update()
def prepro(seed):
"""
Preprocess meta data and splits them for train and test set
"""
print('Preprocessing meta')
meta = data.read_meta(os.path.join(args.data_path, args.meta))
# Creates folders
if not os.path.exists(os.path.join(args.data_path, args.mel_dir)):
os.mkdir(os.path.join(args.data_path, args.mel_dir))
# if not os.path.exists(os.path.join(args.data_path, args.mag_dir)):
# os.mkdir(os.path.join(args.data_path, args.mag_dir))
# Creates pool
p = Pool(NUM_JOBS)
total_files = len(meta)
fpaths = meta.fpath.values
with tqdm(total=total_files) as pbar:
for _ in tqdm(p.imap_unordered(f, fpaths)):
pbar.update()
print('Complete')
from tqdm import tqdm
dataset_detect_path = "../dataset/test"
label_path = "yolov5/runs/detect/exp11/labels"
result_save_path = "submission/"
if __name__ == '__main__':
detect_files = os.listdir(dataset_detect_path)
with open(os.path.join(result_save_path, "submission4.txt"), 'a') as f:
f.write('image_id,PredictionString\n')
for file in tqdm(detect_files):
try:
meta = read_meta(os.path.join(dataset_detect_path, file))
x_size = int(meta["(0028, 0010)"]) # Rows
y_size = int(meta["(0028, 0011)"]) # Columns
except Exception(e):
print(e)
file = file.replace(".dicom", "")
result_list = []
if os.path.exists(os.path.join(label_path, file+".txt")):
with open(os.path.join(label_path, file+".txt")) as ff:
result_list = ff.readlines()
result_list = [[float(y) for y in x.split(' ')] for x in result_list]
result_list = [[x[0], x[1] - x[3] / 2, x[2] - x[4] / 2, x[1] + x[3] / 2, x[2] + x[4]/2, x[5]] for x in result_list]
result_list = [[x[0], x[5], x[1] * x_size, x[2] * y_size, x[3] * x_size, x[4] * y_size] for x in result_list]
result_lists_temp = [[int(y) for y in x] for x in result_list]
for i in range(len(result_lists_temp)):
result_lists_temp[i][1] = result_list[i][1]