import os
import cv2
import numpy as np
import argparse
import pickle
from tqdm import tqdm
parser = argparse.ArgumentParser(description='Test')
parser.add_argument('--input_train_path', default='', type=str,
help='Root path of train.')
parser.add_argument('--input_gallery_path', default='', type=str,
help='Root path of gallery.')
parser.add_argument('--input_probe_path', default='', type=str,
help='Root path of probe.')
parser.add_argument('--output_path', default='', type=str,
help='Root path for output.')
opt = parser.parse_args()
OUTPUT_PATH = opt.output_path
print('Pretreatment Start.\n'
'Input train path: {}\n'
'Input gallery path: {}\n'
'Input probe path: {}\n'
'Output path: {}\n'.format(
opt.input_train_path, opt.input_gallery_path, opt.input_probe_path, OUTPUT_PATH))
INPUT_PATH = opt.input_train_path
print("Walk the input train path")
id_list = os.listdir(INPUT_PATH)
id_list.sort()
for _id in tqdm(id_list):
seq_type = os.listdir(os.path.join(INPUT_PATH, _id))
seq_type.sort()
for _seq_type in seq_type:
out_dir = os.path.join(OUTPUT_PATH, _id, _seq_type, "default")
count_frame = 0
all_imgs = []
frame_list = sorted(os.listdir(
os.path.join(INPUT_PATH, _id, _seq_type)))
for _frame_name in frame_list:
frame_path = os.path.join(
INPUT_PATH, _id, _seq_type, _frame_name)
img = cv2.imread(frame_path, cv2.IMREAD_GRAYSCALE)
if img is not None:
# Save the img
all_imgs.append(img)
count_frame += 1
all_imgs = np.asarray(all_imgs)
if count_frame > 0:
os.makedirs(out_dir, exist_ok=True)
all_imgs_pkl = os.path.join(out_dir, '{}.pkl'.format(_seq_type))
pickle.dump(all_imgs, open(all_imgs_pkl, 'wb'))
# Warn if the sequence contains less than 5 frames
if count_frame < 5:
print('Seq:{}-{}, less than 5 valid data.'.format(_id, _seq_type))
print("Walk the input gallery path")
INPUT_PATH = opt.input_gallery_path
id_list = os.listdir(INPUT_PATH)
id_list.sort()
for _id in tqdm(id_list):
seq_type = os.listdir(os.path.join(INPUT_PATH, _id))
seq_type.sort()
for _seq_type in seq_type:
out_dir = os.path.join(OUTPUT_PATH, _id, _seq_type, "default")
count_frame = 0
all_imgs = []
frame_list = sorted(os.listdir(
os.path.join(INPUT_PATH, _id, _seq_type)))
for _frame_name in frame_list:
frame_path = os.path.join(
INPUT_PATH, _id, _seq_type, _frame_name)
img = cv2.imread(frame_path, cv2.IMREAD_GRAYSCALE)
if img is not None:
# Save the img
all_imgs.append(img)
count_frame += 1
all_imgs = np.asarray(all_imgs)
if count_frame > 0:
os.makedirs(out_dir, exist_ok=True)
all_imgs_pkl = os.path.join(out_dir, '{}.pkl'.format(_seq_type))
pickle.dump(all_imgs, open(all_imgs_pkl, 'wb'))
# Warn if the sequence contains less than 5 frames
if count_frame < 5:
print('Seq:{}-{}, less than 5 valid data.'.format(_id, _seq_type))
print("Finish {}".format(_id))
print("Walk the input probe path")
INPUT_PATH = opt.input_probe_path
seq_type = os.listdir(INPUT_PATH)
seq_type.sort()
_id = "probe"
for _seq_type in tqdm(seq_type):
out_dir = os.path.join(OUTPUT_PATH, _id, _seq_type, "default")
count_frame = 0
all_imgs = []
frame_list = sorted(os.listdir(
os.path.join(INPUT_PATH, _seq_type)))
for _frame_name in frame_list:
frame_path = os.path.join(
INPUT_PATH, _seq_type, _frame_name)
img = cv2.imread(frame_path, cv2.IMREAD_GRAYSCALE)
if img is not None:
# Save the img
all_imgs.append(img)
count_frame += 1
all_imgs = np.asarray(all_imgs)
if count_frame > 0:
os.makedirs(out_dir, exist_ok=True)
all_imgs_pkl = os.path.join(out_dir, '{}.pkl'.format(_seq_type))
pickle.dump(all_imgs, open(all_imgs_pkl, 'wb'))
# Warn if the sequence contains less than 5 frames
if count_frame < 5:
print('Seq:{}-{}, less than 5 valid data.'.format(_id, _seq_type))