def create(c):
if not os.path.exists(image_folder) or not os.path.exists(
detection_file_name):
raise FileNotFoundError(
'cannot find the image folder and the detection file')
if not os.path.exists(args.log_folder):
os.mkdir(args.log_folder)
tracker = SSTTracker()
reader = MOTDataReader(image_folder=image_folder,
detection_file_name=detection_file_name,
min_confidence=0.0)
select_squences = [402, 404, 410, 422]
frame_index = 0
for i, item in enumerate(reader):
if i not in select_squences:
continue
if i > len(reader):
break
if item is None:
continue
img = item[0]
det = item[1]
if img is None or det is None or len(det) == 0:
continue
if len(det) > config['max_object']:
det = det[:config['max_object'], :]
h, w, _ = img.shape
det[:, [2, 4]] /= float(w)
det[:, [3, 5]] /= float(h)
image_org = tracker.update(img, det[:, 2:6], args.show_image,
frame_index)
frame_index += 1
if args.show_image and not image_org is None:
# det[:, [2, 4]] *= float(w)
# det[:, [3, 5]] *= float(h)
# boxes = det[:, 2:6].astype(int)
# for bid, b in enumerate(boxes):
# image_org = cv2.putText(image_org, '{}'.format(bid), tuple(b[:2]), cv2.FONT_HERSHEY_SIMPLEX, 1,
# (0, 0, 0), 2)
cv2.imshow('res', image_org)
cv2.imwrite(os.path.join(args.log_folder, '{0:06}.jpg'.format(i)),
image_org)
# cv2.waitKey(0)
print('frame: {}'.format(i))
def test(choice=None):
if args.type == 'train':
dataset_index = [2, 4, 5, 9, 10, 11, 13]
dataset_detection_type = {'-DPM', '-FRCNN', '-SDP'}
if args.type == 'test':
dataset_index = [1, 3, 6, 7, 8, 12, 14]
dataset_detection_type = {'-FRCNN', '-SDP', '-DPM'}
dataset_image_folder_format = os.path.join(
args.mot_root,
args.type + '/MOT' + str(args.mot_version) + '-{:02}{}/img1')
detection_file_name_format = os.path.join(
args.mot_root,
args.type + '/MOT' + str(args.mot_version) + '-{:02}{}/det/det.txt')
if not os.path.exists(args.log_folder):
os.mkdir(args.log_folder)
save_folder = ''
choice_str = ''
if not choice is None:
choice_str = TrackerConfig.get_configure_str(choice)
save_folder = os.path.join(args.log_folder, choice_str)
if not os.path.exists(save_folder):
os.mkdir(save_folder)
# else:
# return
saved_file_name_format = os.path.join(
save_folder, 'MOT' + str(args.mot_version) + '-{:02}{}.txt')
save_video_name_format = os.path.join(
save_folder, 'MOT' + str(args.mot_version) + '-{:02}{}.avi')
f = lambda format_str: [
format_str.format(index, type) for type in dataset_detection_type
for index in dataset_index
]
timer = Timer()
for image_folder, detection_file_name, saved_file_name, save_video_name in zip(
f(dataset_image_folder_format), f(detection_file_name_format),
f(saved_file_name_format), f(save_video_name_format)):
print('start processing ' + saved_file_name)
tracker = SSTTracker()
reader = MOTDataReader(image_folder=image_folder,
detection_file_name=detection_file_name,
min_confidence=0.0)
result = list()
result_str = saved_file_name
first_run = True
for i, item in enumerate(reader):
if i > len(reader):
break
if item is None:
continue
img = item[0]
det = item[1]
if img is None or det is None or len(det) == 0:
continue
if len(det) > config['max_object']:
det = det[:config['max_object'], :]
h, w, _ = img.shape
if first_run and args.save_video:
vw = cv2.VideoWriter(
save_video_name,
cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'), 10, (w, h))
first_run = False
det[:, [2, 4]] /= float(w)
det[:, [3, 5]] /= float(h)
timer.tic()
image_org = tracker.update(img, det[:, 2:6], args.show_image, i)
timer.toc()
print('{}:{}, {}, {}\r'.format(os.path.basename(saved_file_name),
i, int(i * 100 / len(reader)),
choice_str))
#if args.show_image and not image_org is None:
#plt.imshow('res', image_org)
#cv2.waitKey(1)
if args.save_video and not image_org is None:
vw.write(image_org)
# save result
for t in tracker.tracks:
n = t.nodes[-1]
if t.age == 1:
b = n.get_box(tracker.frame_index - 1, tracker.recorder)
result.append([i] + [t.id] +
[b[0] * w, b[1] * h, b[2] * w, b[3] * h] +
[-1, -1, -1, -1])
# save data
np.savetxt(saved_file_name, np.array(result).astype(int), fmt='%i')
print(result_str)
print(timer.total_time)
print(timer.average_time)
def test(choice=None):
video_name_list = config['video_name_list']
if not os.path.exists(args.log_folder):
os.mkdir(args.log_folder)
save_folder = ''
choice_str = ''
if not choice is None:
choice_str = TrackerConfig.get_configure_str(choice)
save_folder = os.path.join(args.log_folder, choice_str)
if not os.path.exists(save_folder):
os.mkdir(save_folder)
save_file_name_format = os.path.join(save_folder, '{}.txt')
save_video_name_format = os.path.join(save_folder, '{}.avi')
timer = Timer()
for video_name in video_name_list:
if video_name == 'AVG-TownCentre':
TrackerConfig.set_configure((4, 0, 4, 4, 5, 4))
else:
TrackerConfig.set_configure(choice)
mot_root = os.path.join(config['mot_root'], config['dataset_type'])
mot_root = os.path.join(mot_root, video_name)
image_folder = os.path.join(mot_root, 'img1')
detection_file_name = os.path.join(mot_root, 'det/det.txt')
save_video_name = save_video_name_format.format(video_name)
save_file_name = save_file_name_format.format(video_name)
reader = MOTDataReader(image_folder=image_folder,
detection_file_name=detection_file_name,
min_confidence=None)
tracker = SSTTracker()
result = list()
result_str = save_file_name
force_init = True
for i, item in enumerate(reader):
if i > len(reader):
break
if item is None:
continue
img = item[0]
det = item[1]
if img is None or det is None or len(det) == 0:
continue
if len(det) > config['max_object']:
det = det[:config['max_object'], :]
h, w, _ = img.shape
if i == 1 and args.save_video:
vw = cv2.VideoWriter(
save_video_name,
cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'), 10, (w, h))
det = det.astype(float)
det[:, [2, 4]] /= float(w)
det[:, [3, 5]] /= float(h)
timer.tic()
image_org = tracker.update(img, det[:, 2:6], args.show_image, i,
force_init)
force_init = False
timer.toc()
print('{}:{}, {}, {}\r'.format(os.path.basename(save_file_name), i,
int(i * 100 / len(reader)),
choice_str))
if args.show_image and not image_org is None:
cv2.imshow('res', image_org)
cv2.waitKey(1)
if args.save_video and not image_org is None:
try:
vw.write(image_org)
except:
pass
# save result
for t in tracker.tracks:
n = t.nodes[-1]
if t.age == 1:
b = n.get_box(tracker.frame_index - 1, tracker.recorder)
result.append([i + 1] + [t.id + 1] +
[b[0] * w, b[1] * h, b[2] * w, b[3] * h] +
[-1, -1, -1, -1])
# save data
np.savetxt(save_file_name, np.array(result).astype(int), fmt='%i')
print(result_str)
print(timer.total_time)
print(timer.average_time)
def test():
if args.type == 'train':
dataset_index = [2, 4, 5, 9, 10, 11, 13]
# dataset_index = [10]
dataset_detection_type = {'-DPM', '-FRCNN', '-SDP'}
dataset_detection_type = {'-FRCNN'}
if args.type == 'test':
# dataset_index = [1, 3, 6, 7, 8, 12, 14]
dataset_index = [3]
dataset_detection_type = {'-DPM', '-FRCNN', '-SDP'}
dataset_detection_type = {'-FRCNN'}
dataset_detection_type = {''}
dataset_image_folder_format = os.path.join(
args.mot_root,
args.type + '/MOT' + str(args.mot_version) + '-{:02}{}/img1')
detection_file_name_format = os.path.join(
args.mot_root,
args.type + '/MOT' + str(args.mot_version) + '-{:02}{}/det/det.txt')
saved_file_name_format = 'MOT' + str(args.mot_version) + '-{:02}{}.txt'
save_video_name_format = 'MOT' + str(args.mot_version) + '-{:02}{}.avi'
f = lambda format_str: [
format_str.format(index, type) for type in dataset_detection_type
for index in dataset_index
]
timer = Timer()
for image_folder, detection_file_name, saved_file_name, save_video_name in zip(
f(dataset_image_folder_format), f(detection_file_name_format),
f(saved_file_name_format), f(save_video_name_format)):
print('start processing ' + saved_file_name)
tracker = SSTTracker()
reader = MOTDataReader(image_folder=image_folder,
detection_file_name=detection_file_name)
i = 0
result = list()
result_str = saved_file_name
for item in reader:
i += 1
if i > len(reader):
break
if item is None:
continue
img = item[0]
det = item[1]
if img is None or det is None or len(det) == 0:
continue
if len(det) > config['max_object']:
det = det[:config['max_object'], :]
h, w, _ = img.shape
if i == 1 and args.save_video:
vw = cv2.VideoWriter(
save_video_name,
cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'), 10, (w, h))
det[:, [2, 4]] /= float(w)
det[:, [3, 5]] /= float(h)
timer.tic()
image_org = tracker.update(img, det[:, 2:6], args.show_image)
timer.toc()
print('{}:{}, {}\r'.format(saved_file_name, i,
int(i * 100 / len(reader))))
if args.show_image and not image_org is None:
cv2.imshow('res', image_org)
cv2.waitKey(10)
if args.save_video and not image_org is None:
vw.write(image_org)
# save result
# for t in tracker.tracks:
# n = t.nodes[-1]
# if t.age == 1:
# b = n.box
# result.append(
# [i] + [t.id] + [b[0]*w, b[1]*h, b[2]*w, b[3]*h] + [-1, -1, -1, -1]
# )
# save data
np.savetxt(saved_file_name, np.array(result).astype(int), fmt='%i')
print(result_str)
print(timer.total_time)
print(timer.average_time)