def save_images(zip_file, save_dir=None, train_test_split_file=None): """Rename and move all used images to a directory.""" print("Extracting zip file") root = osp.dirname(osp.abspath(zip_file)) if save_dir is None: save_dir = root may_make_dir(save_dir) with ZipFile(zip_file) as z: z.extractall(path=save_dir) print("Extracting zip file done") new_im_dir = osp.join(save_dir, 'images') may_make_dir(new_im_dir) raw_dir = osp.join(save_dir, osp.basename(zip_file)[:-4]) im_paths = [] nums = [] for dir_name in ['bounding_box_train', 'bounding_box_test', 'query']: im_paths_ = get_im_names(osp.join(raw_dir, dir_name), return_path=True, return_np=False) im_paths_.sort() im_paths += list(im_paths_) nums.append(len(im_paths_)) im_names = move_ims(im_paths, new_im_dir, parse_original_im_name, new_im_name_tmpl) split = dict() keys = ['trainval_im_names', 'gallery_im_names', 'q_im_names'] inds = [0] + nums inds = np.cumsum(inds) for i, k in enumerate(keys): split[k] = im_names[inds[i]:inds[i + 1]] save_pickle(split, train_test_split_file) print('Saving images done.') return split
def save_images(zip_file, save_dir=None, train_test_split_file=None): """Rename and move all used images to a directory.""" print("Extracting zip file") root = osp.dirname(osp.abspath(zip_file)) if save_dir is None: save_dir = root may_make_dir(save_dir) with ZipFile(zip_file) as z: z.extractall(path=save_dir) print("Extracting zip file done") new_im_dir = osp.join(save_dir, 'images') may_make_dir(new_im_dir) raw_dir = osp.join(save_dir, osp.basename(zip_file)[:-4]) im_paths = [] nums = [] for dir_name in ['bounding_box_train', 'bounding_box_test', 'query']: im_paths_ = get_im_names(osp.join(raw_dir, dir_name), return_path=True, return_np=False) im_paths_.sort() im_paths += list(im_paths_) nums.append(len(im_paths_)) im_names = move_ims( im_paths, new_im_dir, parse_original_im_name, new_im_name_tmpl) split = dict() keys = ['trainval_im_names', 'gallery_im_names', 'q_im_names'] inds = [0] + nums inds = np.cumsum(inds) for i, k in enumerate(keys): split[k] = im_names[inds[i]:inds[i + 1]] save_pickle(split, train_test_split_file) print('Saving images done.') return split
def save_images(zip_file, save_dir=None, train_test_split_file=None): """Rename and move all used images to a directory.""" print("Extracting zip file") root = osp.dirname(osp.abspath(zip_file)) if save_dir is None: save_dir = root may_make_dir(osp.abspath(save_dir)) with ZipFile(zip_file) as z: z.extractall(path=save_dir) print("Extracting zip file done") new_im_dir = osp.join(save_dir, 'images') may_make_dir(osp.abspath(new_im_dir)) raw_dir = osp.join(save_dir, osp.basename(zip_file)[:-4]) im_paths = [] nums = [] im_paths_ = get_im_names(osp.join(raw_dir, 'bounding_box_train'), return_path=True, return_np=False) im_paths_.sort() im_paths += list(im_paths_) nums.append(len(im_paths_)) im_paths_ = get_im_names(osp.join(raw_dir, 'bounding_box_test'), return_path=True, return_np=False) im_paths_.sort() im_paths_ = [p for p in im_paths_ if not osp.basename(p).startswith('-1')] im_paths += list(im_paths_) nums.append(len(im_paths_)) im_paths_ = get_im_names(osp.join(raw_dir, 'query'), return_path=True, return_np=False) im_paths_.sort() im_paths += list(im_paths_) nums.append(len(im_paths_)) q_ids_cams = set([(parse_original_im_name(osp.basename(p), 'id'), parse_original_im_name(osp.basename(p), 'cam')) for p in im_paths_]) im_paths_ = get_im_names(osp.join(raw_dir, 'gt_bbox'), return_path=True, return_np=False) im_paths_.sort() # Only gather images for those ids and cams used in testing. im_paths_ = [ p for p in im_paths_ if (parse_original_im_name(osp.basename(p), 'id'), parse_original_im_name(osp.basename(p), 'cam')) in q_ids_cams ] im_paths += list(im_paths_) nums.append(len(im_paths_)) im_names = move_ims(im_paths, new_im_dir, parse_original_im_name, new_im_name_tmpl) split = dict() keys = [ 'trainval_im_names', 'gallery_im_names', 'q_im_names', 'mq_im_names' ] inds = [0] + nums inds = np.cumsum(np.array(inds)) for i, k in enumerate(keys): split[k] = im_names[inds[i]:inds[i + 1]] save_pickle(split, train_test_split_file) print('Saving images done.') return split
def save_images(zip_file, save_dir=None, train_test_split_file=None): """Rename and move all used images to a directory.""" print("Extracting zip file") root = osp.dirname(osp.abspath(zip_file)) if save_dir is None: save_dir = root may_make_dir(osp.abspath(save_dir)) with ZipFile(zip_file) as z: z.extractall(path=save_dir) print("Extracting zip file done") new_im_dir = osp.join(save_dir, 'images') may_make_dir(osp.abspath(new_im_dir)) raw_dir = osp.join(save_dir, osp.basename(zip_file)[:-4]) im_paths = [] nums = [] im_paths_ = get_im_names(osp.join(raw_dir, 'bounding_box_train'), return_path=True, return_np=False) im_paths_.sort() im_paths += list(im_paths_) nums.append(len(im_paths_)) im_paths_ = get_im_names(osp.join(raw_dir, 'bounding_box_test'), return_path=True, return_np=False) im_paths_.sort() im_paths_ = [p for p in im_paths_ if not osp.basename(p).startswith('-1')] im_paths += list(im_paths_) nums.append(len(im_paths_)) im_paths_ = get_im_names(osp.join(raw_dir, 'query'), return_path=True, return_np=False) im_paths_.sort() im_paths += list(im_paths_) nums.append(len(im_paths_)) q_ids_cams = set([(parse_original_im_name(osp.basename(p), 'id'), parse_original_im_name(osp.basename(p), 'cam')) for p in im_paths_]) im_paths_ = get_im_names(osp.join(raw_dir, 'gt_bbox'), return_path=True, return_np=False) im_paths_.sort() # Only gather images for those ids and cams used in testing. im_paths_ = [p for p in im_paths_ if (parse_original_im_name(osp.basename(p), 'id'), parse_original_im_name(osp.basename(p), 'cam')) in q_ids_cams] im_paths += list(im_paths_) nums.append(len(im_paths_)) im_names = move_ims( im_paths, new_im_dir, parse_original_im_name, new_im_name_tmpl) split = dict() keys = ['trainval_im_names', 'gallery_im_names', 'q_im_names', 'mq_im_names'] inds = [0] + nums inds = np.cumsum(np.array(inds)) for i, k in enumerate(keys): split[k] = im_names[inds[i]:inds[i + 1]] save_pickle(split, train_test_split_file) print('Saving images done.') return split