fast-reid/fastreid/data/datasets/lpw.py

48 lines
1.4 KiB
Python

# encoding: utf-8
"""
@author: xingyu liao
@contact: sherlockliao01@gmail.com
"""
import os
from glob import glob
from fastreid.data.datasets import DATASET_REGISTRY
from fastreid.data.datasets.bases import ImageDataset
__all__ = ['LPW', ]
@DATASET_REGISTRY.register()
class LPW(ImageDataset):
dataset_dir = "pep_256x128"
dataset_name = "lpw"
def __init__(self, root='datasets', **kwargs):
self.root = root
self.train_path = os.path.join(self.root, self.dataset_dir)
required_files = [self.train_path]
self.check_before_run(required_files)
train = self.process_train(self.train_path)
super().__init__(train, [], [], **kwargs)
def process_train(self, train_path):
data = []
file_path_list = ['scen1', 'scen2', 'scen3']
for scene in file_path_list:
cam_list = os.listdir(os.path.join(train_path, scene))
for cam in cam_list:
camid = self.dataset_name + "_" + cam
pid_list = os.listdir(os.path.join(train_path, scene, cam))
for pid_dir in pid_list:
img_paths = glob(os.path.join(train_path, scene, cam, pid_dir, "*.jpg"))
for img_path in img_paths:
pid = self.dataset_name + "_" + scene + "-" + pid_dir
data.append([img_path, pid, camid])
return data