add dtb70 and tcolor128 interfaces

README.md

@@ -1,6 +1,8 @@
 # GOT-10k Python Toolkit
 
-This repository contains the official python toolkit for running experiments and evaluate performance on [GOT-10k](https://got-10k.github.io) benchmark. For convenience, it also provides unofficial implementation of tracking pipelines for [OTB](http://cvlab.hanyang.ac.kr/tracker_benchmark/index.html) and [VOT](http://votchallenge.net) benchmarks. The code is written in pure python and is compile-free. Although we support both python2 and python3, we recommend python3 for better performance.
+This repository contains the official python toolkit for running experiments and evaluate performance on [GOT-10k](https://got-10k.github.io) benchmark. The code is written in pure python and is compile-free. Although we support both python2 and python3, we recommend python3 for better performance.
+
+For convenience, the toolkit also provides unofficial implementation of dataset interfaces and tracking pipelines for [OTB](http://cvlab.hanyang.ac.kr/tracker_benchmark/index.html), [VOT](http://votchallenge.net), [DTB70](https://github.com/flyers/drone-tracking) and [TColor128](http://www.dabi.temple.edu/~hbling/data/TColor-128/TColor-128.html) benchmarks.
 
 [GOT-10k](https://got-10k.github.io) is a large, high-diversity and one-shot database for evaluating generic purposed visual trackers. If you use the GOT-10k database or toolkits for a research publication, please consider citing:
 

got10k/datasets/__init__.py

@@ -3,4 +3,6 @@
 from .got10k import GOT10k
 from .otb import OTB
 from .vot import VOT
+from .dtb70 import DTB70
+from .tcolor128 import TColor128
 from .vid import ImageNetVID

got10k/datasets/dtb70.py

@@ -0,0 +1,68 @@
+from __future__ import absolute_import, print_function
+
+import os
+import glob
+import numpy as np
+import six
+
+
+class DTB70(object):
+    """`DTB70 <https://github.com/flyers/drone-tracking>`_ Dataset.
+
+    Publication:
+        ``Visual object tracking for unmanned aerial vehicles: A benchmark and new motion models``,
+        Y. Wu, J. Lim and M.-H. Yang, IEEE TPAMI 2015.
+    
+    Args:
+        root_dir (string): Root directory of dataset where sequence
+            folders exist.
+    """
+    def __init__(self, root_dir):
+        super(DTB70, self).__init__()
+        self.root_dir = root_dir
+        self._check_integrity(root_dir)
+
+        self.anno_files = sorted(glob.glob(
+            os.path.join(root_dir, '*/groundtruth_rect.txt')))
+        self.seq_dirs = [os.path.dirname(f) for f in self.anno_files]
+        self.seq_names = [os.path.basename(d) for d in self.seq_dirs]
+
+    def __getitem__(self, index):
+        r"""        
+        Args:
+            index (integer or string): Index or name of a sequence.
+        
+        Returns:
+            tuple: (img_files, anno), where ``img_files`` is a list of
+                file names and ``anno`` is a N x 4 (rectangles) numpy array.
+        """
+        if isinstance(index, six.string_types):
+            if not index in self.seq_names:
+                raise Exception('Sequence {} not found.'.format(index))
+            index = self.seq_names.index(index)
+
+        img_files = sorted(glob.glob(
+            os.path.join(self.seq_dirs[index], 'img/*.jpg')))
+        anno = np.loadtxt(self.anno_files[index], delimiter=',')
+        assert len(img_files) == len(anno)
+        assert anno.shape[1] == 4
+
+        return img_files, anno
+
+    def __len__(self):
+        return len(self.seq_names)
+
+    def _check_integrity(self, root_dir):
+        seq_names = os.listdir(root_dir)
+        seq_names = [n for n in seq_names if not n[0] == '.']
+
+        if os.path.isdir(root_dir) and len(seq_names) > 0:
+            # check each sequence folder
+            for seq_name in seq_names:
+                seq_dir = os.path.join(root_dir, seq_name)
+                if not os.path.isdir(seq_dir):
+                    print('Warning: sequence %s not exist.' % seq_name)
+        else:
+            # dataset not exist
+            raise Exception('Dataset not found or corrupted. ' +
+                            'You can use download=True to download it.')

got10k/datasets/tcolor128.py

@@ -0,0 +1,98 @@
+from __future__ import absolute_import, print_function
+
+import os
+import glob
+import numpy as np
+import six
+
+from ..utils.ioutils import download, extract
+
+
+class TColor128(object):
+    """`TColor128 <http://www.dabi.temple.edu/~hbling/data/TColor-128/TColor-128.html>`_ Dataset.
+
+    Publication:
+        ``Encoding color information for visual tracking: algorithms and benchmark``,
+        P. Liang, E. Blasch and H. Ling, TIP, 2015.
+    
+    Args:
+        root_dir (string): Root directory of dataset where sequence
+            folders exist.
+    """
+    def __init__(self, root_dir, download=True):
+        super(TColor128, self).__init__()
+        self.root_dir = root_dir
+        if download:
+            self._download(root_dir)
+        self._check_integrity(root_dir)
+
+        self.anno_files = sorted(glob.glob(
+            os.path.join(root_dir, '*/*_gt.txt')))
+        self.seq_dirs = [os.path.dirname(f) for f in self.anno_files]
+        self.seq_names = [os.path.basename(d) for d in self.seq_dirs]
+        # valid frame range for each sequence
+        self.range_files = [os.path.join(
+            root_dir, '%s/%s_frames.txt' % (n, n))
+            for n in self.seq_names]
+
+    def __getitem__(self, index):
+        r"""        
+        Args:
+            index (integer or string): Index or name of a sequence.
+        
+        Returns:
+            tuple: (img_files, anno), where ``img_files`` is a list of
+                file names and ``anno`` is a N x 4 (rectangles) numpy array.
+        """
+        if isinstance(index, six.string_types):
+            if not index in self.seq_names:
+                raise Exception('Sequence {} not found.'.format(index))
+            index = self.seq_names.index(index)
+
+        # load valid frame range
+        frames = np.loadtxt(
+            self.range_files[index], dtype=int, delimiter=',')
+        img_files = [os.path.join(
+            self.seq_dirs[index], 'img/%04d.jpg' % f)
+            for f in range(frames[0], frames[1] + 1)]
+
+        # load annotations
+        anno = np.loadtxt(self.anno_files[index], delimiter=',')
+        assert len(img_files) == len(anno)
+        assert anno.shape[1] == 4
+
+        return img_files, anno
+
+    def __len__(self):
+        return len(self.seq_names)
+
+    def _download(self, root_dir):
+        if not os.path.isdir(root_dir):
+            os.makedirs(root_dir)
+        elif len(os.listdir(root_dir)) > 100:
+            print('Files already downloaded.')
+            return
+
+        url = 'http://www.dabi.temple.edu/~hbling/data/TColor-128/Temple-color-128.zip'
+        zip_file = os.path.join(root_dir, 'Temple-color-128.zip')
+        print('Downloading to %s...' % zip_file)
+        download(url, zip_file)
+        print('\nExtracting to %s...' % root_dir)
+        extract(zip_file, root_dir)
+
+        return root_dir
+
+    def _check_integrity(self, root_dir):
+        seq_names = os.listdir(root_dir)
+        seq_names = [n for n in seq_names if not n[0] == '.']
+
+        if os.path.isdir(root_dir) and len(seq_names) > 0:
+            # check each sequence folder
+            for seq_name in seq_names:
+                seq_dir = os.path.join(root_dir, seq_name)
+                if not os.path.isdir(seq_dir):
+                    print('Warning: sequence %s not exist.' % seq_name)
+        else:
+            # dataset not exist
+            raise Exception('Dataset not found or corrupted. ' +
+                            'You can use download=True to download it.')

got10k/experiments/__init__.py

@@ -3,3 +3,5 @@
 from .got10k import ExperimentGOT10k
 from .otb import ExperimentOTB
 from .vot import ExperimentVOT
+from .dtb70 import ExperimentDTB70
+from .tcolor128 import ExperimentTColor128

got10k/experiments/dtb70.py

@@ -0,0 +1,27 @@
+from __future__ import absolute_import
+
+import os
+
+from .otb import ExperimentOTB
+from ..datasets import DTB70
+
+
+class ExperimentDTB70(ExperimentOTB):
+    r"""Experiment pipeline and evaluation toolkit for DTB70 dataset.
+    
+    Args:
+        root_dir (string): Root directory of DTB70 dataset.
+        result_dir (string, optional): Directory for storing tracking
+            results. Default is ``./results``.
+        report_dir (string, optional): Directory for storing performance
+            evaluation results. Default is ``./reports``.
+    """
+    def __init__(self, root_dir,
+                 result_dir='results', report_dir='reports'):
+        self.dataset = DTB70(root_dir)
+        self.result_dir = os.path.join(result_dir, 'DTB70')
+        self.report_dir = os.path.join(report_dir, 'DTB70')
+        # as nbins_iou increases, the success score
+        # converges to the average overlap (AO)
+        self.nbins_iou = 21
+        self.nbins_ce = 51

got10k/experiments/otb.py

@@ -35,7 +35,8 @@ def __init__(self, root_dir, version=2015,
         self.nbins_ce = 51
 
     def run(self, tracker, visualize=False):
-        print('Running tracker %s on OTB...' % tracker.name)
+        print('Running tracker %s on %s...' % (
+            tracker.name, type(self.dataset).__name__))
 
         # loop over the complete dataset
         for s, (img_files, anno) in enumerate(self.dataset):

got10k/experiments/tcolor128.py

@@ -0,0 +1,27 @@
+from __future__ import absolute_import
+
+import os
+
+from .otb import ExperimentOTB
+from ..datasets import TColor128
+
+
+class ExperimentTColor128(ExperimentOTB):
+    r"""Experiment pipeline and evaluation toolkit for TColor128 dataset.
+    
+    Args:
+        root_dir (string): Root directory of TColor128 dataset.
+        result_dir (string, optional): Directory for storing tracking
+            results. Default is ``./results``.
+        report_dir (string, optional): Directory for storing performance
+            evaluation results. Default is ``./reports``.
+    """
+    def __init__(self, root_dir,
+                 result_dir='results', report_dir='reports'):
+        self.dataset = TColor128(root_dir)
+        self.result_dir = os.path.join(result_dir, 'TColor128')
+        self.report_dir = os.path.join(report_dir, 'TColor128')
+        # as nbins_iou increases, the success score
+        # converges to the average overlap (AO)
+        self.nbins_iou = 21
+        self.nbins_ce = 51

got10k/experiments/vot.py

@@ -60,7 +60,8 @@ def __init__(self, root_dir, version=2017,
                      'size_change', 'motion_change', 'empty']
 
     def run(self, tracker, visualize=False):
-        print('Running tracker %s on VOT...' % tracker.name)
+        print('Running tracker %s on %s...' % (
+            tracker.name, type(self.dataset).__name__))
 
         # run all specified experiments
         if 'supervised' in self.experiments:

tests/test_datasets.py

@@ -4,7 +4,7 @@
 import os
 import random
 
-from got10k.datasets import GOT10k, OTB, VOT, ImageNetVID
+from got10k.datasets import GOT10k, OTB, VOT, DTB70, TColor128, ImageNetVID
 
 
 class TestDatasets(unittest.TestCase):
@@ -38,6 +38,16 @@ def test_vot(self):
         dataset = VOT(root_dir, anno_type='rect', return_meta=True)
         self._check_dataset(dataset)
 
+    def test_dtb70(self):
+        root_dir = os.path.join(self.data_dir, 'DTB70')
+        dataset = DTB70(root_dir)
+        self._check_dataset(dataset)
+
+    def test_tcolor128(self):
+        root_dir = os.path.join(self.data_dir, 'Temple-color-128')
+        dataset = TColor128(root_dir)
+        self._check_dataset(dataset)
+
     def test_vid(self):
         root_dir = os.path.join(self.data_dir, 'ILSVRC')
         dataset = ImageNetVID(root_dir, subset=('train', 'val'))

tests/test_experiments.py

@@ -5,7 +5,7 @@
 
 from got10k.trackers import IdentityTracker
 from got10k.experiments import ExperimentGOT10k, ExperimentOTB, \
-    ExperimentVOT
+    ExperimentVOT, ExperimentDTB70, ExperimentTColor128
 
 
 class TestExperiments(unittest.TestCase):
@@ -41,6 +41,22 @@ def test_vot(self):
         # report performance
         experiment.report([self.tracker.name])
 
+    def test_dtb70(self):
+        root_dir = os.path.join(self.data_dir, 'DTB70')
+        # run experiment
+        experiment = ExperimentDTB70(root_dir)
+        experiment.run(self.tracker, visualize=False)
+        # report performance
+        experiment.report([self.tracker.name])
+
+    def test_tcolor128(self):
+        root_dir = os.path.join(self.data_dir, 'Temple-color-128')
+        # run experiment
+        experiment = ExperimentTColor128(root_dir)
+        experiment.run(self.tracker, visualize=False)
+        # report performance
+        experiment.report([self.tracker.name])
+
 
 if __name__ == '__main__':
     unittest.main()