class StruckTracker(GenericVisionTracker):
"""
TODO
"""
def __init__(self):
"""
Initialize the tracker
"""
self.name = 'struck_tracker'
f = open("config.txt", "w")
f.write(struck_config)
f.close()
self.reset()
def reset(self):
"""
Reset the tracker
:return:
"""
self._primed = False
self.bbox = None
def _prime(self, im, bounding_region):
"""
prime tracker on image and bounding box
:param im: input image (3 - channel numpy array)
:type im: numpy.ndarray
:param bounding_region: initial bounding region of the tracked object
:type bounding_region: PVM_tools.bounding_region.BoundingRegion
"""
self.bbox=bounding_region
bounding_box = bounding_region.get_box_pixels()
struck.STRUCK_init(im, bounding_box)
def _track(self, im):
"""
Track on given image, return a bounding box
:param im: image (3 - channel numpy array)
:type im: numpy.ndarray
:return: bounding box of the tracker object
:rtype: PVM_tools.bounding_region.BoundingRegion
"""
# this is required so that tracker is re-initialized if it is primed again
self._primed = False
struck.STRUCK_track(im)
struck_bbox = struck.STRUCK_get_bbox()
self.bounding_box = [struck_bbox["xmin"], struck_bbox["ymin"], struck_bbox["width"], struck_bbox["height"]]
if self.bounding_box == ():
self.bbox = BoundingRegion()
else:
self.bbox = BoundingRegion(image_shape=(im.shape[0], im.shape[1], 3), box=self.bounding_box)
return self.bbox.copy()
def get_heatmap(self, heatmap_name=None):
return self.bbox.get_mask()
class CenterVisionTracker(GenericVisionTracker):
"""
This class exposes the null vision tracker which just always
returns its priming bounding box
"""
def __init__(self, size_factor=0.2, new_name=None):
"""
Initialize the tracker
"""
if new_name is None:
self.name = 'center_tracker'
else:
self.name = new_name
self.size_factor = size_factor
def reset(self):
"""
Reset the tracker
:return:
"""
self._primed = False
self.bbox = None
def _prime(self, im, bounding_region):
"""
prime tracker on image and bounding box
:param im: input image (3 - channel numpy array)
:type im: numpy.ndarray
:param bounding_region: initial bounding region of the tracked object
:type bounding_region: PVM_tools.bounding_region.BoundingRegion
"""
box = np.array([(im.shape[1] - im.shape[1] * self.size_factor) / 2,
(im.shape[0] - im.shape[0] * self.size_factor) / 2,
im.shape[1] * self.size_factor,
im.shape[0] * self.size_factor]).astype(np.int)
self.bbox = BoundingRegion(image_shape=im.shape, box=box)
if not self._primed:
self._primed = True
def _track(self, im):
"""
Track on given image, rseturn a bounding box
:param im: image (3 - channel numpy array)
:type im: numpy.ndarray
:return: bounding box of the tracker object
:rtype: PVM_tools.bounding_region.BoundingRegion
"""
# this is required so that tracker is re-initialized if it is primed again
self._primed = False
return self.bbox.copy()
def get_heatmap(self, heatmap_name=None):
return self.bbox.get_mask()
class CenterVisionTracker(GenericVisionTracker):
"""
This class exposes the null vision tracker which just always
returns its priming bounding box
"""
def __init__(self, size_factor=0.2, new_name=None):
"""
Initialize the tracker
"""
if new_name is None:
self.name = 'center_tracker'
else:
self.name = new_name
self.size_factor = size_factor
def reset(self):
"""
Reset the tracker
:return:
"""
self._primed = False
self.bbox = None
def _prime(self, im, bounding_region):
"""
prime tracker on image and bounding box
:param im: input image (3 - channel numpy array)
:type im: numpy.ndarray
:param bounding_region: initial bounding region of the tracked object
:type bounding_region: PVM_tools.bounding_region.BoundingRegion
"""
box = np.array([(im.shape[1]-im.shape[1]*self.size_factor)/2,
(im.shape[0]-im.shape[0]*self.size_factor)/2,
im.shape[1]*self.size_factor,
im.shape[0]*self.size_factor]).astype(np.int)
self.bbox = BoundingRegion(image_shape=im.shape, box=box)
if not self._primed:
self._primed = True
def _track(self, im):
"""
Track on given image, rseturn a bounding box
:param im: image (3 - channel numpy array)
:type im: numpy.ndarray
:return: bounding box of the tracker object
:rtype: PVM_tools.bounding_region.BoundingRegion
"""
# this is required so that tracker is re-initialized if it is primed again
self._primed = False
return self.bbox.copy()
def get_heatmap(self, heatmap_name=None):
return self.bbox.get_mask()
class TLDVisionTracker(GenericVisionTracker):
"""
This class exposes the open tld tracker implemented in C++ by http://www.gnebehay.com/tld/.
Originally OpenTLD that was originally published in MATLAB by Zdenek Kalal.
"""
def __init__(self):
"""
Initialize the tracker
"""
self.name = 'tld_tracker'
self.reset()
def reset(self):
"""
Reset the tracker
:return:
"""
self.tld = None
self._primed = False
self.bbox = None
def _prime(self, im, bounding_region):
"""
prime tracker on image and bounding box
:param im: input image (3 - channel numpy array)
:type im: numpy.ndarray
:param bounding_region: initial bounding region of the tracked object
:type bounding_region: PVM_tools.bounding_region.BoundingRegion
"""
self.bbox = bounding_region
bounding_box = bounding_region.get_box_pixels()
if not self._primed:
self.tld = tld.TLD2()
self._primed = True
self.height, self.width = im.shape[:2]
self.tld.set_width_and_height((self.width, self.height))
im = cv2.cvtColor(im, cv2.COLOR_RGB2GRAY)
img_cvmat = cv2.cv.fromarray(im)
if bounding_box[0] + bounding_box[2] > self.width:
bounding_box[2] = self.width - bounding_box[0]
if bounding_box[1] + bounding_box[3] > self.height:
bounding_box[3] = self.height - bounding_box[1]
self.tld.selectObject(
img_cvmat,
tuple([
int(bounding_box[0]),
int(bounding_box[1]),
int(bounding_box[2]),
int(bounding_box[3])
]))
def _track(self, im):
"""
Track on given image, return a bounding box
:param im: image (3 - channel numpy array)
:type im: numpy.ndarray
:return: bounding box of the tracker object
:rtype: PVM_tools.bounding_region.BoundingRegion
"""
# this is required so that tracker is re-initialized if it is primed again
self._primed = False
img_cvmat = cv2.cv.fromarray(im)
self.tld.processImage(img_cvmat)
self.bounding_box = self.tld.getCurrBB()
self.confidence = self.tld.currConf
if self.bounding_box == ():
self.bbox = BoundingRegion()
else:
self.bbox = BoundingRegion(image_shape=(im.shape[0], im.shape[1],
3),
box=self.bounding_box,
confidence=self.confidence)
return self.bbox.copy()
def get_heatmap(self, heatmap_name=None):
return self.bbox.get_mask()
class CMTVisionTracker(GenericVisionTracker):
"""
This class exposes the CMT tracker implemented in http://www.gnebehay.com/CMT/.
"""
def __init__(self):
"""
Initialize the tracker
"""
self.name = 'cmt_tracker'
self.reset()
def reset(self):
"""
Reset the tracker
:return:
"""
self.cmt = None
self._primed = False
self.bbox = None
def _prime(self, im, bounding_region):
"""
prime tracker on image and bounding box
:param im: input image (3 - channel numpy array)
:type im: numpy.ndarray
:param bounding_region: initial bounding region of the tracked object
:type bounding_region: PVM_tools.bounding_region.BoundingRegion
"""
self.bbox=bounding_region
bounding_box = bounding_region.get_box_pixels()
if not self._primed:
this_dir = os.path.dirname(os.path.realpath(__file__))
sys.path.append(this_dir+"/original_cmt/")
from CMT import CMT
self.cmt = CMT()
self._primed = True
self.height, self.width = im.shape[:2]
im = cv2.cvtColor(im, cv2.COLOR_RGB2GRAY)
self.cmt.initialise(im_gray0=im,
tl=tuple([bounding_box[0], bounding_box[1]]),
br=tuple([bounding_box[0]+bounding_box[2], bounding_box[1]+bounding_box[3]]))
self.im_prev = im
def _track(self, im):
"""
Track on given image, return a bounding box
:param im: image (3 - channel numpy array)
:type im: numpy.ndarray
:return: bounding box of the tracker object
:rtype: PVM_tools.bounding_region.BoundingRegion
"""
# this is required so that tracker is re-initialized if it is primed again
self._primed = False
self.im_prev = im
im = cv2.cvtColor(im, cv2.COLOR_RGB2GRAY)
self.cmt.process_frame(im)
self.confidence = 1
if np.isnan(self.cmt.bb).any():
self.bbox = BoundingRegion()
else:
self.bbox = BoundingRegion(image_shape=im.shape, box=self.cmt.bb, confidence=self.confidence)
return self.bbox.copy()
def get_heatmap(self, heatmap_name=None):
return self.bbox.get_mask()
class StruckTracker(GenericVisionTracker):
"""
TODO
"""
def __init__(self):
"""
Initialize the tracker
"""
self.name = 'struck_tracker'
f = open("config.txt", "w")
f.write(struck_config)
f.close()
self.reset()
def reset(self):
"""
Reset the tracker
:return:
"""
self._primed = False
self.bbox = None
def _prime(self, im, bounding_region):
"""
prime tracker on image and bounding box
:param im: input image (3 - channel numpy array)
:type im: numpy.ndarray
:param bounding_region: initial bounding region of the tracked object
:type bounding_region: PVM_tools.bounding_region.BoundingRegion
"""
self.bbox = bounding_region
bounding_box = bounding_region.get_box_pixels()
struck.STRUCK_init(im, bounding_box)
def _track(self, im):
"""
Track on given image, return a bounding box
:param im: image (3 - channel numpy array)
:type im: numpy.ndarray
:return: bounding box of the tracker object
:rtype: PVM_tools.bounding_region.BoundingRegion
"""
# this is required so that tracker is re-initialized if it is primed again
self._primed = False
struck.STRUCK_track(im)
struck_bbox = struck.STRUCK_get_bbox()
self.bounding_box = [
struck_bbox["xmin"], struck_bbox["ymin"], struck_bbox["width"],
struck_bbox["height"]
]
if self.bounding_box == ():
self.bbox = BoundingRegion()
else:
self.bbox = BoundingRegion(image_shape=(im.shape[0], im.shape[1],
3),
box=self.bounding_box)
return self.bbox.copy()
def get_heatmap(self, heatmap_name=None):
return self.bbox.get_mask()
class TLDVisionTracker(GenericVisionTracker):
"""
This class exposes the open tld tracker implemented in C++ by http://www.gnebehay.com/tld/.
Originally OpenTLD that was originally published in MATLAB by Zdenek Kalal.
"""
def __init__(self):
"""
Initialize the tracker
"""
self.name = 'tld_tracker'
self.reset()
def reset(self):
"""
Reset the tracker
:return:
"""
self.tld = None
self._primed = False
self.bbox = None
def _prime(self, im, bounding_region):
"""
prime tracker on image and bounding box
:param im: input image (3 - channel numpy array)
:type im: numpy.ndarray
:param bounding_region: initial bounding region of the tracked object
:type bounding_region: PVM_tools.bounding_region.BoundingRegion
"""
self.bbox=bounding_region
bounding_box = bounding_region.get_box_pixels()
if not self._primed:
self.tld = tld.TLD2()
self._primed = True
self.height, self.width = im.shape[:2]
self.tld.set_width_and_height((self.width, self.height))
im = cv2.cvtColor(im, cv2.COLOR_RGB2GRAY)
img_cvmat = cv2.cv.fromarray(im)
if bounding_box[0] + bounding_box[2] > self.width:
bounding_box[2] = self.width - bounding_box[0]
if bounding_box[1] + bounding_box[3] > self.height:
bounding_box[3] = self.height - bounding_box[1]
self.tld.selectObject(img_cvmat, tuple([int(bounding_box[0]), int(bounding_box[1]), int(bounding_box[2]), int(bounding_box[3])]))
def _track(self, im):
"""
Track on given image, return a bounding box
:param im: image (3 - channel numpy array)
:type im: numpy.ndarray
:return: bounding box of the tracker object
:rtype: PVM_tools.bounding_region.BoundingRegion
"""
# this is required so that tracker is re-initialized if it is primed again
self._primed = False
img_cvmat = cv2.cv.fromarray(im)
self.tld.processImage(img_cvmat)
self.bounding_box = self.tld.getCurrBB()
self.confidence = self.tld.currConf
if self.bounding_box == ():
self.bbox = BoundingRegion()
else:
self.bbox = BoundingRegion(image_shape=(im.shape[0], im.shape[1], 3), box=self.bounding_box, confidence=self.confidence)
return self.bbox.copy()
def get_heatmap(self, heatmap_name=None):
return self.bbox.get_mask()
