mirror of https://github.com/JDAI-CV/fast-reid.git
46 lines
1.3 KiB
Python
46 lines
1.3 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__ = ['SenseReID', ]
|
||
|
|
|
||
|
|
|
||
|
|
@DATASET_REGISTRY.register()
|
||
|
|
class SenseReID(ImageDataset):
|
||
|
|
dataset_dir = "SenseReID"
|
||
|
|
dataset_name = "senseid"
|
||
|
|
|
||
|
|
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 = ['test_gallery', 'test_prob']
|
||
|
|
|
||
|
|
for file_path in file_path_list:
|
||
|
|
sub_file = os.path.join(train_path, file_path)
|
||
|
|
img_name = glob(os.path.join(sub_file, "*.jpg"))
|
||
|
|
for img_path in img_name:
|
||
|
|
img_name = img_path.split('/')[-1]
|
||
|
|
img_info = img_name.split('_')
|
||
|
|
pid = self.dataset_name + "_" + img_info[0]
|
||
|
|
camid = self.dataset_name + "_" + img_info[1].split('.')[0]
|
||
|
|
data.append([img_path, pid, camid])
|
||
|
|
return data
|