def __init__(self, img_dir, tracker_type, dataset_config):
self.img_dir = img_dir
self.tracker_type = tracker_type
self.frame_list = get_img_list(img_dir)
self.frame_list.sort()
dataname = img_dir.split('\\')[-2] # / in linux \\ in windows
self.gts = get_ground_truthes(img_dir[:-4])
if dataname in dataset_config.frames.keys():
start_frame, end_frame = dataset_config.frames[dataname][0:2]
if dataname != 'David':
self.init_gt = self.gts[start_frame-1]
else:
self.init_gt = self.gts[0]
self.frame_list = self.frame_list[start_frame-1:end_frame]
else:
self.init_gt = self.gts[0]
if self.tracker_type == 'MOSSE':
self.tracker = MOSSE()
elif self.tracker_type == 'KCF_CN':
self.tracker = KCF(features='cn', kernel='gaussian')
elif self.tracker_type == 'KCF_GRAY':
self.tracker = KCF(features='gray', kernel='gaussian')
elif self.tracker_type == 'KCF_HOG':
self.tracker = KCF(features='hog', kernel='gaussian')
elif self.tracker_type == 'DCF_GRAY':
self.tracker = KCF(features='gray', kernel='linear')
elif self.tracker_type == 'DCF_HOG':
self.tracker = KCF(features='hog', kernel='linear')
elif self.tracker_type == 'VGG16':
self.tracker = VGG16()
elif self.tracker_type == 'YOLOV4':
self.tracker = YOLOV4()
else:
raise NotImplementedError
def __init__(self,
img_dir,
tracker_type=None,
tracker_params=DEFAULT_PARAMS,
dataset_config=None,
max_frames=None,
IOUmin=0.33):
self.img_dir = img_dir
self.tracker_type = tracker_type
self.frame_list = get_img_list(img_dir)
self.frame_list.sort()
if max_frames:
self.frame_list = self.frame_list[:max_frames]
dataname = img_dir.split('/')[-2]
self.gts = get_ground_truthes(img_dir[:-4])
frame_list_len = len(self.frame_list)
gts_len = len(self.gts)
if gts_len > frame_list_len:
self.gts = self.gts[:frame_list_len]
elif gts_len < frame_list_len:
self.gts += [None] * (frame_list_len - gts_len)
self.tracker = CSRDCF(config=tracker_params)
self.init_gt = self.gts[0]
self.IOUmin = IOUmin
def __init__(self, img_dir, tracker_type, dataset_config):
self.img_dir = img_dir
self.tracker_type = tracker_type
self.frame_list = get_img_list(img_dir)
self.frame_list.sort()
dataname = img_dir.split('/')[-2]
self.gts = get_ground_truthes(img_dir[:-4])
if dataname in dataset_config.frames.keys():
start_frame, end_frame = dataset_config.frames[dataname][0:2]
if dataname != 'David':
self.init_gt = self.gts[start_frame - 1]
else:
self.init_gt = self.gts[0]
self.frame_list = self.frame_list[start_frame - 1:end_frame]
else:
self.init_gt = self.gts[0]
if self.tracker_type == 'MOSSE':
self.tracker = MOSSE()
elif self.tracker_type == 'CSK':
self.tracker = CSK()
elif self.tracker_type == 'CN':
self.tracker = CN()
elif self.tracker_type == 'DSST':
self.tracker = DSST()
elif self.tracker_type == 'Staple':
self.tracker = Staple(config=staple_config.StapleConfig())
elif self.tracker_type == 'Staple-CA':
self.tracker = Staple(config=staple_config.StapleCAConfig())
elif self.tracker_type == 'KCF_CN':
self.tracker = KCF(features='cn', kernel='gaussian')
elif self.tracker_type == 'KCF_GRAY':
self.tracker = KCF(features='gray', kernel='gaussian')
elif self.tracker_type == 'KCF_HOG':
self.tracker = KCF(features='hog', kernel='gaussian')
elif self.tracker_type == 'DCF_GRAY':
self.tracker = KCF(features='gray', kernel='linear')
elif self.tracker_type == 'DCF_HOG':
self.tracker = KCF(features='hog', kernel='linear')
elif self.tracker_type == 'DAT':
self.tracker = DAT()
elif self.tracker_type == 'ECO-HC':
self.tracker = ECO(config=otb_hc_config.OTBHCConfig())
elif self.tracker_type == 'ECO':
self.tracker = ECO(config=otb_deep_config.OTBDeepConfig())
elif self.tracker_type == 'BACF':
self.tracker = BACF()
elif self.tracker_type == 'CSRDCF':
self.tracker = CSRDCF()
elif self.tracker_type == 'SAMF':
self.tracker = SAMF()
elif self.tracker_type == 'LDES':
self.tracker = LDES(ldes_config.LDESDemoLinearConfig())
elif self.tracker_type == 'DSST_LP':
self.tracker = DSST_LP()
else:
raise NotImplementedError
#scale_params['number_of_interp_scales'] = 5 # default: 33
#scale_params['scale_step_filter'] = 1.14 # 2^(1/5)
#params['admm_iterations'] = 2 # default: 4
#params['template_size'] = 64 # default: 200
#params['top_channels'] = 7 # default: None; less is riskier
#scale_params['number_of_scales_filter'] = 21 # default: 33
#scale_params['number_of_interp_scales'] = 21 # default: 33
#scale_params['scale_step_filter'] = 1.034 # 2^(1/21)
#scale_params['nonuniform_scale_factors'] = True
#scale_params['do_poly_interp'] = True
# Don't uncomment! No use.
#scale_params['random_scale_factors'] = True # default: false
params['scale_params'] = scale_params
data_path = sys.argv[1]
gts = get_ground_truthes(data_path)
img_dir = os.path.join(data_path, 'img')
tracker = PyTracker(img_dir,
tracker_params=params,
max_frames=None,
IOUmin=0.33)
poses = tracker.tracking(verbose=True)
#tracker.updating_histograms()
#plot_success(gts,poses,os.path.join('../results/CF',data_name+'_success.jpg'))
#plot_precision(gts,poses,os.path.join('../results/CF',data_name+'_precision.jpg'))
def add_a_tracker(results_json_path, tracker_type, dst_json_path):
data_dir = '../dataset/OTB100'
data_names = os.listdir(data_dir)
f = open(results_json_path, 'r')
otb100_results = json.load(f)
dataset_config = OTBDatasetConfig()
for data_name in data_names:
print('data name:', data_name)
data_path = os.path.join(data_dir, data_name)
img_dir = os.path.join(data_path, 'img')
tracker = PyTracker(img_dir,
tracker_type=tracker_type,
dataset_config=dataset_config)
gts = get_ground_truthes(data_path)
if data_name in dataset_config.frames.keys():
start_frame, end_frame = dataset_config.frames[data_name][:2]
if data_name != 'David':
gts = gts[start_frame - 1:end_frame]
otb100_results[data_name]['gts'] = []
for gt in gts:
otb100_results[data_name]['gts'].append(list(gt.astype(np.int)))
tracker_preds = tracker.tracking()
otb100_results[data_name][tracker_type] = []
for tracker_pred in tracker_preds:
otb100_results[data_name][tracker_type].append(
list(tracker_pred.astype(np.int)))
threshes, precisions_tracker = get_thresh_precision_pair(
gts, tracker_preds)
idx20 = [i for i, x in enumerate(threshes) if x == 20][0]
plt.plot(threshes,
precisions_tracker,
label=tracker_type + ' ' + str(precisions_tracker[idx20])[:5])
plt.title(data_name + ' Precision')
plt.xlabel('thresh')
plt.ylabel('precision')
plt.legend()
if not os.path.exists('../results/tmp'):
print('test')
os.mkdir('../results/tmp/')
plt.savefig('../results/tmp/' + data_name + '_precision.jpg')
plt.clf()
threshes, successes_tracker = get_thresh_success_pair(
gts, tracker_preds)
plt.plot(threshes,
successes_tracker,
label=tracker_type + ' ' + str(calAUC(successes_tracker))[:5])
plt.title(data_name + ' Success')
plt.xlabel('thresh')
plt.ylabel('success')
plt.legend()
plt.savefig('../results/tmp/' + data_name + '_success.jpg')
plt.clf()
json_content = json.dumps(otb100_results, default=str)
f = open(dst_json_path, 'w')
f.write(json_content)
f.close()
def __init__(self,img_dir,tracker_type,dataset_config):
# img_directory is an attribute
self.img_dir=img_dir
# tracker type definition
self.tracker_type=tracker_type
# get_img_list function appends the name of all jpg files into a list.
self.frame_list = get_img_list(img_dir)
# Sorting the frame_list
self.frame_list.sort()
# name of the folder
dataname=img_dir.split('/')[-2]
# Getting the ground truth
self.gts=get_ground_truthes(img_dir[:-4])
if dataname in dataset_config.frames.keys():
start_frame,end_frame=dataset_config.frames[dataname][0:2]
if dataname!='David':
self.init_gt=self.gts[start_frame-1]
else:
self.init_gt=self.gts[0]
self.frame_list=self.frame_list[start_frame-1:end_frame]
else:
self.init_gt=self.gts[0]
# Calling the appropriate tracker class as asked for.
if self.tracker_type == 'MOSSE':
self.tracker=MOSSE()
elif self.tracker_type=='CSK':
self.tracker=CSK()
elif self.tracker_type=='CN':
self.tracker=CN()
elif self.tracker_type=='DSST':
self.tracker=DSST(dsst_config.DSSTConfig())
elif self.tracker_type=='Staple':
self.tracker=Staple(config=staple_config.StapleConfig())
elif self.tracker_type=='Staple-CA':
self.tracker=Staple(config=staple_config.StapleCAConfig())
elif self.tracker_type=='KCF_CN':
self.tracker=KCF(features='cn',kernel='gaussian')
elif self.tracker_type=='KCF_GRAY':
self.tracker=KCF(features='gray',kernel='gaussian')
elif self.tracker_type=='KCF_HOG':
self.tracker=KCF(features='hog',kernel='gaussian')
elif self.tracker_type=='DCF_GRAY':
self.tracker=KCF(features='gray',kernel='linear')
elif self.tracker_type=='DCF_HOG':
self.tracker=KCF(features='hog',kernel='linear')
elif self.tracker_type=='DAT':
self.tracker=DAT()
elif self.tracker_type=='ECO-HC':
self.tracker=ECO(config=otb_hc_config.OTBHCConfig())
elif self.tracker_type=='ECO':
self.tracker=ECO(config=otb_deep_config.OTBDeepConfig())
elif self.tracker_type=='BACF':
self.tracker=BACF()
elif self.tracker_type=='CSRDCF':
self.tracker=CSRDCF(config=csrdcf_config.CSRDCFConfig())
elif self.tracker_type=='CSRDCF-LP':
self.tracker=CSRDCF(config=csrdcf_config.CSRDCFLPConfig())
elif self.tracker_type=='SAMF':
self.tracker=SAMF()
elif self.tracker_type=='LDES':
self.tracker=LDES(ldes_config.LDESDemoLinearConfig())
elif self.tracker_type=='DSST-LP':
self.tracker=DSST(dsst_config.DSSTLPConfig())
elif self.tracker_type=='MKCFup':
self.tracker=MKCFup(config=mkcf_up_config.MKCFupConfig())
elif self.tracker_type=='MKCFup-LP':
self.tracker=MKCFup(config=mkcf_up_config.MKCFupLPConfig())
elif self.tracker_type=='STRCF':
self.tracker=STRCF()
elif self.tracker_type=='MCCTH-Staple':
self.tracker=MCCTHStaple(config=mccth_staple_config.MCCTHOTBConfig())
elif self.tracker_type=='MCCTH':
self.tracker=MCCTH(config=mccth_config.MCCTHConfig())
else:
raise NotImplementedError
if __name__ == '__main__':
data_dir = 'C:/Users/17321/Desktop/OTB100/OTB100_test'
img_dir = '/digger/'
#model = 'KCF'
models = ['TLD', 'BOOSTING', 'KCF']
result_dir = 'C:/Users/17321/Desktop/pyCFTrackers-master/results/' + models[
0] + '/'
poses_list = []
for model in models:
gTracker = Tracker(tracker_type=model)
img = cv2.imread(data_dir + img_dir + 'img/' + '0000.jpg')
gts = get_ground_truthes(data_dir + img_dir)
gTracker.initWorking(img, (gts[0][0], gts[0][1], gts[0][2], gts[0][3]))
poses = []
index = 1
for img_path in sorted(os.listdir(data_dir + img_dir + '/img/')):
if img_path != '0000.jpg':
img = cv2.imread(data_dir + img_dir + '/img/' + img_path)
bbox = gTracker.track(img)
x, y, w, h = bbox
x_t, y_t, w_t, h_t = gts[index]
index += 1
cv2.rectangle(img, (x_t, y_t), (x_t + w_t, y_t + h_t),
(0, 255, 0), 1)
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)