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reIDfolder.py
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"""
Copyright (C) 2018 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
from torchvision import datasets
import os
import numpy as np
import random
class ReIDFolder(datasets.ImageFolder):
def __init__(self, root, transform):
super(ReIDFolder, self).__init__(root, transform)
targets = np.asarray([s[1] for s in self.samples])
self.targets = targets
self.img_num = len(self.samples)
print(self.img_num)
def _get_cam_id(self, path):
camera_id = []
filename = os.path.basename(path)
camera_id = filename.split('c')[1][0]
return int(camera_id)-1
def _get_pos_sample(self, target, index, path):
pos_index = np.argwhere(self.targets == target)
pos_index = pos_index.flatten()
pos_index = np.setdiff1d(pos_index, index)
if len(pos_index)==0: # in the query set, only one sample
return path
else:
rand = random.randint(0,len(pos_index)-1)
return self.samples[pos_index[rand]][0]
def _get_neg_sample(self, target):
neg_index = np.argwhere(self.targets != target)
neg_index = neg_index.flatten()
rand = random.randint(0,len(neg_index)-1)
return self.samples[neg_index[rand]]
def __getitem__(self, index):
path, target = self.samples[index]
sample = self.loader(path)
pos_path = self._get_pos_sample(target, index, path)
pos = self.loader(pos_path)
if self.transform is not None:
sample = self.transform(sample)
pos = self.transform(pos)
if self.target_transform is not None:
target = self.target_transform(target)
return sample, target, pos
class ReIDFolder_mix(datasets.ImageFolder):
def __init__(self, root, transform, idx_list):
super(ReIDFolder_mix, self).__init__(root, transform)
self.idx_list = idx_list
targets = np.asarray([s[1] for s in self.samples])
self.targets = targets
self.img_num = len(self.samples)
print(self.img_num)
def _get_cam_id(self, path):
camera_id = []
filename = os.path.basename(path)
camera_id = filename.split('c')[1][0]
return int(camera_id)-1
def _get_pos_sample(self, target, index, path):
pos_index = np.argwhere(self.targets == target)
pos_index = pos_index.flatten()
pos_index = np.setdiff1d(pos_index, index)
if len(pos_index)==0: # in the query set, only one sample
return path
else:
rand = random.randint(0,len(pos_index)-1)
return self.samples[pos_index[rand]][0]
def _get_neg_sample(self, target):
neg_index = np.argwhere(self.targets != target)
neg_index = neg_index.flatten()
rand = random.randint(0,len(neg_index)-1)
return self.samples[neg_index[rand]]
def __getitem__(self, index):
idx = self.idx_list[index]
path, target = self.samples[idx]
sample = self.loader(path)
pos_path = self._get_pos_sample(target, idx, path)
pos = self.loader(pos_path)
if self.transform is not None:
sample = self.transform(sample)
pos = self.transform(pos)
if self.target_transform is not None:
target = self.target_transform(target)
return sample, target, pos
def __len__(self):
return len(self.idx_list)