| # encoding: utf-8 | |
| """ | |
| @author: liaoxingyu | |
| @contact: sherlockliao01@gmail.com | |
| """ | |
| from torch.utils.data import Dataset | |
| from .data_utils import read_image | |
| class CommDataset(Dataset): | |
| """Image Person ReID Dataset""" | |
| def __init__(self, img_items, transform=None, relabel=True): | |
| self.img_items = img_items | |
| self.transform = transform | |
| self.relabel = relabel | |
| pid_set = set() | |
| cam_set = set() | |
| for i in img_items: | |
| pid_set.add(i[1]) | |
| cam_set.add(i[2]) | |
| self.pids = sorted(list(pid_set)) | |
| self.cams = sorted(list(cam_set)) | |
| if relabel: | |
| self.pid_dict = dict([(p, i) for i, p in enumerate(self.pids)]) | |
| self.cam_dict = dict([(p, i) for i, p in enumerate(self.cams)]) | |
| def __len__(self): | |
| return len(self.img_items) | |
| def __getitem__(self, index): | |
| img_item = self.img_items[index] | |
| img_path = img_item[0] | |
| pid = img_item[1] | |
| camid = img_item[2] | |
| viewid = img_item[3] | |
| img = read_image(img_path) | |
| if self.transform is not None: img = self.transform(img) | |
| if self.relabel: | |
| pid = self.pid_dict[pid] | |
| camid = self.cam_dict[camid] | |
| return { | |
| "images": img, | |
| "targets": pid, | |
| "camids": camid, | |
| "viewids": viewid, | |
| "img_paths": img_path, | |
| } | |
| def num_classes(self): | |
| return len(self.pids) | |
| def num_cameras(self): | |
| return len(self.cams) | |