def run_vot(self, debug=None, visdom_info=None):
params = self.get_parameters()
params.tracker_name = self.name
params.param_name = self.parameter_name
params.run_id = self.run_id
debug_ = debug
if debug is None:
debug_ = getattr(params, 'debug', 0)
if debug is None:
visualization_ = getattr(params, 'visualization', False)
else:
visualization_ = True if debug else False
params.visualization = visualization_
params.debug = debug_
self._init_visdom(visdom_info, debug_)
tracker = self.create_tracker(params)
tracker.initialize_features()
import pytracking.evaluation.vot as vot
def _convert_anno_to_list(vot_anno):
vot_anno = [vot_anno[0][0][0], vot_anno[0][0][1], vot_anno[0][1][0], vot_anno[0][1][1],
vot_anno[0][2][0], vot_anno[0][2][1], vot_anno[0][3][0], vot_anno[0][3][1]]
return vot_anno
def _convert_image_path(image_path):
image_path_new = image_path[20:- 2]
return "".join(image_path_new)
"""Run tracker on VOT."""
handle = vot.VOT("polygon")
vot_anno_polygon = handle.region()
vot_anno_polygon = _convert_anno_to_list(vot_anno_polygon)
init_state = convert_vot_anno_to_rect(vot_anno_polygon, tracker.params.vot_anno_conversion_type)
image_path = handle.frame()
if not image_path:
return
image_path = _convert_image_path(image_path)
image = self._read_image(image_path)
tracker.initialize(image, {'init_bbox': init_state})
# Track
while True:
image_path = handle.frame()
if not image_path:
break
image_path = _convert_image_path(image_path)
image = self._read_image(image_path)
out = tracker.track(image)
state = out['target_bbox']
handle.report(vot.Rectangle(state[0], state[1], state[2], state[3]))
segmentation = out['segmentation'] if 'segmentation' in out else None
if self.visdom is not None:
tracker.visdom_draw_tracking(image, out['target_bbox'], segmentation)
elif tracker.params.visualization:
self.visualize(image, out['target_bbox'], segmentation)
def run_vot2020(self, debug=None, visdom_info=None):
params = self.get_parameters()
params.tracker_name = self.name
params.param_name = self.parameter_name
params.run_id = self.run_id
debug_ = debug
if debug is None:
debug_ = getattr(params, 'debug', 0)
if debug is None:
visualization_ = getattr(params, 'visualization', False)
else:
visualization_ = True if debug else False
params.visualization = visualization_
params.debug = debug_
self._init_visdom(visdom_info, debug_)
tracker = self.create_tracker(params)
tracker.initialize_features()
output_segmentation = tracker.predicts_segmentation_mask()
import pytracking.evaluation.vot2020 as vot
def _convert_anno_to_list(vot_anno):
vot_anno = [vot_anno[0], vot_anno[1], vot_anno[2], vot_anno[3]]
return vot_anno
def _convert_image_path(image_path):
return image_path
"""Run tracker on VOT."""
if output_segmentation:
handle = vot.VOT("mask")
else:
handle = vot.VOT("rectangle")
vot_anno = handle.region()
image_path = handle.frame()
if not image_path:
return
image_path = _convert_image_path(image_path)
image = self._read_image(image_path)
if output_segmentation:
vot_anno_mask = vot.make_full_size(vot_anno, (image.shape[1], image.shape[0]))
bbox = masks_to_bboxes(torch.from_numpy(vot_anno_mask), fmt='t').squeeze().tolist()
else:
bbox = _convert_anno_to_list(vot_anno)
vot_anno_mask = None
out = tracker.initialize(image, {'init_mask': vot_anno_mask, 'init_bbox': bbox})
if out is None:
out = {}
prev_output = OrderedDict(out)
# Track
while True:
image_path = handle.frame()
if not image_path:
break
image_path = _convert_image_path(image_path)
image = self._read_image(image_path)
info = OrderedDict()
info['previous_output'] = prev_output
out = tracker.track(image, info)
prev_output = OrderedDict(out)
if output_segmentation:
pred = out['segmentation'].astype(np.uint8)
else:
state = out['target_bbox']
pred = vot.Rectangle(*state)
handle.report(pred, 1.0)
segmentation = out['segmentation'] if 'segmentation' in out else None
if self.visdom is not None:
tracker.visdom_draw_tracking(image, out['target_bbox'], segmentation)
elif tracker.params.visualization:
self.visualize(image, out['target_bbox'], segmentation)
