def run_tracker(self):
"""
Run self.pipeline on VOT
"""
num_gpu = self._hyper_params["device_num"]
all_devs = [torch.device("cuda:%d" % i) for i in range(num_gpu)]
logger.info('runing test on devices {}'.format(all_devs))
vot_root = self._hyper_params["data_root"][self.dataset_name]
logger.info('Using dataset %s at: %s' % (self.dataset_name, vot_root))
# setup dataset
dataset = vot_benchmark.load_dataset(vot_root, self.dataset_name)
self.dataset = dataset
keys = list(dataset.keys())
keys.sort()
if self._hyper_params["video_name_list"]:
keys = self._hyper_params["video_name_list"]
nr_records = len(keys)
pbar = tqdm(total=nr_records)
mean_speed = -1
total_lost = 0
speed_list = []
result_queue = mp.Queue(500)
speed_queue = mp.Queue(500)
# set worker
if num_gpu == 1:
self.worker(keys, all_devs[0], result_queue, speed_queue)
for i in range(nr_records):
t = result_queue.get()
s = speed_queue.get()
total_lost += t
speed_list.append(s)
pbar.update(1)
else:
nr_video = math.ceil(nr_records / num_gpu)
procs = []
for i in range(num_gpu):
start = i * nr_video
end = min(start + nr_video, nr_records)
split_records = keys[start:end]
proc = mp.Process(target=self.worker,
args=(split_records, all_devs[i],
result_queue, speed_queue))
print('process:%d, start:%d, end:%d' % (i, start, end))
proc.start()
procs.append(proc)
for i in range(nr_records):
t = result_queue.get()
s = speed_queue.get()
total_lost += t
speed_list.append(s)
pbar.update(1)
for p in procs:
p.join()
# print result
mean_speed = float(np.mean(speed_list))
logger.info('Total Lost: {:d}'.format(total_lost))
logger.info('Mean Speed: {:.2f} FPS'.format(mean_speed))
self._state['speed'] = mean_speed
# from .paths import ROOT_PATH # isort:skip
import os.path as osp
import sys # isort:skip
# module_name = "debug"
# p = __file__
# while osp.basename(p) != module_name:
# p = osp.dirname(p)
p = osp.dirname(osp.realpath(__file__))
p = osp.dirname(p)
p = osp.join(p, "third_party", "video_analyst")
ROOT_PATH = p
# ROOT_CFG = osp.join(ROOT_PATH, 'config.yaml')
sys.path.insert(0, ROOT_PATH) # isort:skip
# ============== path ============== #
import cv2
from videoanalyst.evaluation import vot_benchmark
DATASET_DIR = osp.join(ROOT_PATH, "datasets/VOT/vot2018")
# dataset = vot_benchmark.load_dataset("/home/lan/Documents/xuyinda/Projects/video_analyst/datasets/VOT/vot2018", "VOT2018")
dataset = vot_benchmark.load_dataset(DATASET_DIR, "VOT2018")
if __name__ == "__main__":
from IPython import embed
embed()