diff --git a/vot_iter/__init__.py b/vot_iter/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/vot_iter/tracker_SiamRPNpp.m b/vot_iter/tracker_SiamRPNpp.m
new file mode 100644
index 0000000000000000000000000000000000000000..7c2f80050ea5940c707175be63d4697acb122b21
--- /dev/null
+++ b/vot_iter/tracker_SiamRPNpp.m
@@ -0,0 +1,27 @@
+
+% error('Tracker not configured! Please edit the tracker_test.m file.'); % Remove this line after proper configuration
+
+% The human readable label for the tracker, used to identify the tracker in reports
+% If not set, it will be set to the same value as the identifier.
+% It does not have to be unique, but it is best that it is.
+tracker_label = ['SiamRPNpp'];
+
+% For Python implementations we have created a handy function that generates the appropritate
+% command that will run the python executable and execute the given script that includes your
+% tracker implementation.
+%
+% Please customize the line below by substituting the first argument with the name of the
+% script of your tracker (not the .py file but just the name of the script) and also provide the
+% path (or multiple paths) where the tracker sources % are found as the elements of the cell
+% array (second argument).
+setenv('MKL_NUM_THREADS','1');
+pysot_root = 'path/to/pysot';
+track_build_path = 'path/to/track/build';
+tracker_command = generate_python_command('vot_iter.vot_iter', {pysot_root; [track_build_path '/python/lib']})
+
+tracker_interpreter = 'python';
+
+tracker_linkpath = {track_build_path};
+
+% tracker_linkpath = {}; % A cell array of custom library directories used by the tracker executable (optional)
+
diff --git a/vot_iter/vot.py b/vot_iter/vot.py
new file mode 100644
index 0000000000000000000000000000000000000000..d8f905e2e1feb62619aac63aac085b461f8b7e88
--- /dev/null
+++ b/vot_iter/vot.py
@@ -0,0 +1,117 @@
+"""
+\file vot.py
+
+@brief Python utility functions for VOT integration
+
+@author Luka Cehovin, Alessio Dore
+
+@date 2016
+
+"""
+
+import sys
+import copy
+import collections
+
+try:
+ import trax
+except ImportError:
+ raise Exception('TraX support not found. Please add trax module to Python path.')
+
+Rectangle = collections.namedtuple('Rectangle', ['x', 'y', 'width', 'height'])
+Point = collections.namedtuple('Point', ['x', 'y'])
+Polygon = collections.namedtuple('Polygon', ['points'])
+
+class VOT(object):
+ """ Base class for Python VOT integration """
+ def __init__(self, region_format, channels=None):
+ """ Constructor
+
+ Args:
+ region_format: Region format options
+ """
+ assert(region_format in [trax.Region.RECTANGLE, trax.Region.POLYGON])
+
+ if channels is None:
+ channels = ['color']
+ elif channels == 'rgbd':
+ channels = ['color', 'depth']
+ elif channels == 'rgbt':
+ channels = ['color', 'ir']
+ elif channels == 'ir':
+ channels = ['ir']
+ else:
+ raise Exception('Illegal configuration {}.'.format(channels))
+
+ self._trax = trax.Server([region_format], [trax.Image.PATH], channels)
+
+ request = self._trax.wait()
+ assert(request.type == 'initialize')
+ if isinstance(request.region, trax.Polygon):
+ self._region = Polygon([Point(x[0], x[1]) for x in request.region])
+ else:
+ self._region = Rectangle(*request.region.bounds())
+ self._image = [x.path() for k, x in request.image.items()]
+ if len(self._image) == 1:
+ self._image = self._image[0]
+
+ self._trax.status(request.region)
+
+ def region(self):
+ """
+ Send configuration message to the client and receive the initialization
+ region and the path of the first image
+
+ Returns:
+ initialization region
+ """
+
+ return self._region
+
+ def report(self, region, confidence = None):
+ """
+ Report the tracking results to the client
+
+ Arguments:
+ region: region for the frame
+ """
+ assert(isinstance(region, Rectangle) or isinstance(region, Polygon))
+ if isinstance(region, Polygon):
+ tregion = trax.Polygon.create([(x.x, x.y) for x in region.points])
+ else:
+ tregion = trax.Rectangle.create(region.x, region.y, region.width, region.height)
+ properties = {}
+ if not confidence is None:
+ properties['confidence'] = confidence
+ self._trax.status(tregion, properties)
+
+ def frame(self):
+ """
+ Get a frame (image path) from client
+
+ Returns:
+ absolute path of the image
+ """
+ if hasattr(self, "_image"):
+ image = self._image
+ del self._image
+ return image
+
+ request = self._trax.wait()
+
+ if request.type == 'frame':
+ image = [x.path() for k, x in request.image.items()]
+ if len(image) == 1:
+ return image[0]
+ return image
+ else:
+ return None
+
+
+ def quit(self):
+ if hasattr(self, '_trax'):
+ self._trax.quit()
+
+ def __del__(self):
+ self.quit()
+
diff --git a/vot_iter/vot_iter.py b/vot_iter/vot_iter.py
new file mode 100644
index 0000000000000000000000000000000000000000..eb87aca25b5a5af295e8bb2063e57756fa34f097
--- /dev/null
+++ b/vot_iter/vot_iter.py
@@ -0,0 +1,76 @@
+import sys
+import cv2
+import torch
+import numpy as np
+import os
+from os.path import join
+
+from pysot.core.config import cfg
+from pysot.models.model_builder import ModelBuilder
+from pysot.tracker.tracker_builder import build_tracker
+from pysot.utils.bbox import get_axis_aligned_bbox
+from pysot.utils.model_load import load_pretrain
+from toolkit.datasets import DatasetFactory
+from toolkit.utils.region import vot_overlap, vot_float2str
+
+from . import vot
+from .vot import Rectangle, Polygon, Point
+
+
+# modify root
+
+cfg_root = "path/to/expr"
+model_file = join(cfg_root, 'model.pth')
+cfg_file = join(cfg_root, 'config.yaml')
+
+def warmup(model):
+ for i in range(10):
+ model.template(torch.FloatTensor(1,3,127,127).cuda())
+
+def setup_tracker():
+ cfg.merge_from_file(cfg_file)
+
+ model = ModelBuilder()
+ model = load_pretrain(model, model_file).cuda().eval()
+
+ tracker = build_tracker(model)
+ warmup(model)
+ return tracker
+
+
+tracker = setup_tracker()
+
+handle = vot.VOT("polygon")
+region = handle.region()
+try:
+ region = np.array([region[0][0][0], region[0][0][1], region[0][1][0], region[0][1][1],
+ region[0][2][0], region[0][2][1], region[0][3][0], region[0][3][1]])
+except:
+ region = np.array(region)
+
+cx, cy, w, h = get_axis_aligned_bbox(region)
+
+image_file = handle.frame()
+if not image_file:
+ sys.exit(0)
+
+im = cv2.imread(image_file) # HxWxC
+# init
+target_pos, target_sz = np.array([cx, cy]), np.array([w, h])
+gt_bbox_ = [cx-(w-1)/2, cy-(h-1)/2, w, h]
+tracker.init(im, gt_bbox_)
+
+while True:
+ img_file = handle.frame()
+ if not img_file:
+ break
+ im = cv2.imread(img_file)
+ outputs = tracker.track(im)
+ pred_bbox = outputs['bbox']
+ result = Rectangle(*pred_bbox)
+ score = outputs['best_score']
+ if cfg.MASK.MASK:
+ pred_bbox = outputs['polygon']
+ result = Polygon(Point(x[0], x[1]) for x in pred_bbox)
+
+ handle.report(result, score)