def demo(opt):
result_root = opt.output_root if opt.output_root != '' else '.'
mkdir_if_missing(result_root)
logger.info('Starting tracking...')
assert osp.exists(opt.input_video), f'{opt.input_video} does NOT exist !'
file_name, file_ext = osp.splitext(opt.input_video)
if file_ext in ['.mp4', 'avi']:
dataloader = datasets.LoadVideo(opt.input_video, opt.img_size)
else:
dataloader = datasets.LoadImages(opt.input_video, opt.img_size)
dataloader.frame_rate = int(round(opt.frame_rate))
result_filename = os.path.join(result_root, 'results.txt')
frame_rate = dataloader.frame_rate
frame_dir = None if opt.output_format == 'text' else osp.join(
result_root, 'frame')
eval_seq(opt,
dataloader,
'mot',
result_filename,
save_dir=frame_dir,
show_image=False,
frame_rate=frame_rate,
use_cuda=opt.gpus != [-1])
if opt.output_format == 'video':
output_video_path = osp.join(result_root, 'MOT16-03-results.mp4')
frame_path = osp.join(result_root, 'frame')
cmd_str = f'ffmpeg -framerate {opt.frame_rate} -f image2 -i {frame_path}/%05d.jpg -b 5000k -c:v mpeg4 {output_video_path}'
os.system(cmd_str)
def demo(opt):
result_root = opt.output_root if opt.output_root != '' else '.'
mkdir_if_missing(result_root)
logger.info('Starting tracking...')
dataloader = datasets.LoadVideo(opt.input_video, opt.img_size)
result_filename = os.path.join(result_root, 'results.txt')
frame_rate = dataloader.frame_rate
frame_dir = None if opt.output_format == 'text' else osp.join(
result_root, 'frame')
eval_seq(opt,
dataloader,
'mot',
result_filename,
save_dir=frame_dir,
show_image=False,
frame_rate=frame_rate,
use_cuda=opt.gpus != [-1])
if opt.output_format == 'video':
output_video_path = osp.join(result_root, 'MOT16-03-results.mp4')
cmd_str = 'ffmpeg -f image2 -i {}/%05d.jpg -b 5000k -c:v mpeg4 {}'.format(
osp.join(result_root, 'frame'), output_video_path)
os.system(cmd_str)
def demo(opt):
result_root = opt.output_root if opt.output_root != "" else "."
mkdir_if_missing(result_root)
logger.info("Starting tracking...")
dataloader = datasets.LoadVideo(opt.input_video, opt.img_size)
result_filename = os.path.join(result_root, "results.txt")
frame_rate = dataloader.frame_rate
frame_dir = None if opt.output_format == "text" else osp.join(
result_root, "frame")
eval_seq(
opt,
dataloader,
"mot",
result_filename,
save_dir=frame_dir,
show_image=False,
frame_rate=frame_rate,
)
if opt.output_format == "video":
output_video_path = osp.join(result_root, "result.mp4")
cmd_str = "ffmpeg -f image2 -i {}/%05d.jpg -b 5000k -c:v mpeg4 {}".format(
osp.join(result_root, "frame"), output_video_path)
os.system(cmd_str)
def demo(opt):
result_root = opt.output_root if opt.output_root != '' else '.'
print('OPT: {}'.format(opt.input_video))
mkdir_if_missing(result_root)
logger.info('Starting tracking...')
dataloader = datasets.LoadVideo(opt.input_video, opt.img_size)
result_filename = os.path.join(result_root, 'results.txt')
frame_rate = dataloader.frame_rate
frame_dir = None if opt.output_format == 'text' else osp.join(
result_root, 'frame')
try:
eval_seq(opt,
dataloader,
'mot',
result_filename,
save_dir=frame_dir,
show_image=True,
frame_rate=frame_rate)
except Exception as e:
logger.info(e)
if opt.output_format == 'video':
output_video_path = osp.join(result_root, 'result.mp4')
cmd_str = 'ffmpeg -f image2 -i {}/%05d.jpg -b 5000k -c:v mpeg4 {}'.format(
osp.join(result_root, 'frame'), output_video_path)
os.system(cmd_str)
def demo(opt):
result_root = opt.output_root if opt.output_root != '' else '.'
mkdir_if_missing(result_root)
file_name = osp.basename(opt.input_video).split('.')[0].replace(' ', '_')
model_name = osp.basename(opt.load_model).split('.')[0]
base_name = f'{file_name}_{model_name}_{opt.conf_thres}'
logger.info('Starting tracking...')
logger.info(f'Working on: {opt.input_video}')
dataloader = datasets.LoadVideo(opt.input_video, opt.img_size)
result_filename = os.path.join(result_root, f'{base_name}_results.txt')
frame_rate = dataloader.frame_rate
frame_dir = None if opt.output_format == 'text' else osp.join(
result_root, f'{file_name}-frames')
eval_seq(opt,
dataloader,
'kitti',
result_filename,
save_dir=frame_dir,
show_image=False,
frame_rate=frame_rate)
if opt.output_format == 'video':
output_video_path = osp.join(result_root, f'{base_name}_result.mp4')
cmd_str = 'ffmpeg -f image2 -i {}/%05d.jpg -b 5000k -c:v mpeg4 {}'.format(
osp.join(result_root, f'{file_name}-frames'), output_video_path)
os.system(cmd_str)
def recogniton(opt):
print("start tracking")
if opt.input_stream == '':
dataloader = datasets.LoadVideo(opt.input_camera, opt.img_size)
else:
dataloader = datasets.LoadVideo(opt.input_stream, opt.img_size)
frame_rate = dataloader.frame_rate
if opt.save:
result_root = opt.output_root if opt.output_root != '' else '.'
mkdir_if_missing(result_root)
result_filename = os.path.join(result_root, 'results.txt')
frame_dir = None if opt.output_format == 'text' else os.path.join(
result_root, 'frame')
eval_seq(opt, dataloader, 'mot', result_filename,
save_dir=frame_dir, show_image=opt.show, frame_rate=frame_rate,
use_cuda=opt.gpus != [-1])
else:
eval_seq(opt, dataloader, 'mot', show_image=opt.show,
frame_rate=frame_rate, use_cuda=opt.gpus != [-1])
def demo(opt):
paths = pickle.load(open(opt.paths_pkl, 'rb'))
gpu_list = opt.custom_gpus.split(',')
if opt.range[1] == -1:
opt.range[1] = len(paths)
tasks = paths[opt.range[0]:opt.range[1]]
to_del_list = []
for idx, path in enumerate(tasks):
video_name = osp.splitext(osp.split(path)[1])[0]
result_root = opt.output_root if opt.output_root != '' else '.'
result_filename = os.path.join(result_root, '%s.txt' % video_name)
if os.path.exists(result_filename):
to_del_list.append(idx)
deleted_tasks = [
tasks[idx] for idx in range(len(tasks)) if idx not in to_del_list
]
opt.range[0] = 0
opt.range[1] = len(deleted_tasks)
if len(gpu_list) > 1:
pickle.dump(deleted_tasks, open('cache.pkl', 'wb'))
opt.paths_pkl = 'cache.pkl'
multiproc(opt, gpu_list, len(deleted_tasks))
else:
for idx, path in enumerate(deleted_tasks):
video_name = osp.splitext(osp.split(path)[1])[0]
result_root = opt.output_root if opt.output_root != '' else '.'
mkdir_if_missing(result_root)
result_filename = os.path.join(result_root, '%s.txt' % video_name)
if os.path.exists(result_filename):
continue
# logger.info('Starting tracking...')
# dataloader = datasets.LoadVideo(opt.input_video, opt.img_size)
dataloader = datasets.LoadVideo(path, opt.img_size)
frame_rate = dataloader.frame_rate
frame_dir = None if opt.output_format == 'text' else osp.join(
result_root, 'frame')
eval_seq(opt,
dataloader,
'mot',
result_filename,
save_dir=frame_dir,
show_image=False,
frame_rate=frame_rate,
tasks_num=len(deleted_tasks),
idx=idx)
def recogniton():
result_root = opt.output_root if opt.output_root != '' else '.'
mkdir_if_missing(result_root)
print("start tracking")
dataloader = datasets.LoadVideo(0, opt.img_size)
result_filename = os.path.join(result_root, 'results.txt')
frame_rate = dataloader.frame_rate
frame_dir = None if opt.output_format == 'text' else os.path.join(
result_root, 'frame')
eval_seq(opt,
dataloader,
'mot',
result_filename,
save_dir=frame_dir,
show_image=True,
frame_rate=frame_rate)
def demo(opt):
result_root = opt.output_root if opt.output_root != '' else '.'
mkdir_if_missing(result_root)
logger.info('Starting tracking...')
dataloader = datasets.LoadVideo(opt.input_video, opt.img_size)
result_filename = os.path.join(result_root, 'results.txt')
frame_rate = dataloader.frame_rate
frame_dir = None if opt.output_format == 'text' else osp.join(
result_root, 'frame')
eval_seq(opt,
dataloader,
'mot',
result_filename,
save_dir=frame_dir,
show_image=False,
frame_rate=frame_rate)
