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# --------------------------------------------------------
# SiamMask
# Licensed under The MIT License
# Written by Qiang Wang (wangqiang2015 at ia.ac.cn)
# --------------------------------------------------------
from os.path import join, realpath, dirname, exists, isdir
from os import listdir
import logging
import glob
import numpy as np
import json
from collections import OrderedDict
def get_dataset_zoo():
root = realpath(join(dirname(__file__), '../data'))
zoos = listdir(root)
def valid(x):
y = join(root, x)
if not isdir(y): return False
return exists(join(y, 'list.txt')) \
or exists(join(y, 'train', 'meta.json')) \
or exists(join(y, 'ImageSets', '2016', 'val.txt')) \
or exists(join(y, 'ImageSets', '2017', 'test-dev.txt'))
zoos = list(filter(valid, zoos))
return zoos
dataset_zoo = get_dataset_zoo()
def load_dataset(dataset):
info = OrderedDict()
if 'VOT' in dataset:
base_path = join(realpath(dirname(__file__)), '../data', dataset)
if not exists(base_path):
logging.error("Please download test dataset!!!")
exit()
list_path = join(base_path, 'list.txt')
with open(list_path) as f:
videos = [v.strip() for v in f.readlines()]
for video in videos:
video_path = join(base_path, video)
image_path = join(video_path, '*.jpg')
image_files = sorted(glob.glob(image_path))
if len(image_files) == 0: # VOT2018
image_path = join(video_path, 'color', '*.jpg')
image_files = sorted(glob.glob(image_path))
gt_path = join(video_path, 'groundtruth.txt')
gt = np.loadtxt(gt_path, delimiter=',').astype(np.float64)
if gt.shape[1] == 4:
gt = np.column_stack((gt[:, 0], gt[:, 1], gt[:, 0], gt[:, 1] + gt[:, 3]-1,
gt[:, 0] + gt[:, 2]-1, gt[:, 1] + gt[:, 3]-1, gt[:, 0] + gt[:, 2]-1, gt[:, 1]))
info[video] = {'image_files': image_files, 'gt': gt, 'name': video}
elif 'DAVIS' in dataset and 'TEST' not in dataset:
base_path = join(realpath(dirname(__file__)), '../data', 'DAVIS')
list_path = join(realpath(dirname(__file__)), '../data', 'DAVIS', 'ImageSets', dataset[-4:], 'val.txt')
with open(list_path) as f:
videos = [v.strip() for v in f.readlines()]
for video in videos:
info[video] = {}
info[video]['anno_files'] = sorted(glob.glob(join(base_path, 'Annotations/480p', video, '*.png')))
info[video]['image_files'] = sorted(glob.glob(join(base_path, 'JPEGImages/480p', video, '*.jpg')))
info[video]['name'] = video
elif 'ytb_vos' in dataset:
base_path = join(realpath(dirname(__file__)), '../data', 'ytb_vos', 'valid')
json_path = join(realpath(dirname(__file__)), '../data', 'ytb_vos', 'valid', 'meta.json')
meta = json.load(open(json_path, 'r'))
meta = meta['videos']
info = dict()
for v in meta.keys():
objects = meta[v]['objects']
frames = []
anno_frames = []
info[v] = dict()
for obj in objects:
frames += objects[obj]['frames']
anno_frames += [objects[obj]['frames'][0]]
frames = sorted(np.unique(frames))
info[v]['anno_files'] = [join(base_path, 'Annotations', v, im_f+'.png') for im_f in frames]
info[v]['anno_init_files'] = [join(base_path, 'Annotations', v, im_f + '.png') for im_f in anno_frames]
info[v]['image_files'] = [join(base_path, 'JPEGImages', v, im_f+'.jpg') for im_f in frames]
info[v]['name'] = v
info[v]['start_frame'] = dict()
info[v]['end_frame'] = dict()
for obj in objects:
start_file = objects[obj]['frames'][0]
end_file = objects[obj]['frames'][-1]
info[v]['start_frame'][obj] = frames.index(start_file)
info[v]['end_frame'][obj] = frames.index(end_file)
elif 'TEST' in dataset:
base_path = join(realpath(dirname(__file__)), '../data', 'DAVIS2017TEST')
list_path = join(realpath(dirname(__file__)), '../data', 'DAVIS2017TEST', 'ImageSets', '2017', 'test-dev.txt')
with open(list_path) as f:
videos = [v.strip() for v in f.readlines()]
for video in videos:
info[video] = {}
info[video]['anno_files'] = sorted(glob.glob(join(base_path, 'Annotations/480p', video, '*.png')))
info[video]['image_files'] = sorted(glob.glob(join(base_path, 'JPEGImages/480p', video, '*.jpg')))
info[video]['name'] = video
else:
logging.error('Not support')
exit()
return info
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