def run_SiamFC(seq, rp, saveimage):
x = seq.init_rect[0]
y = seq.init_rect[1]
w = seq.init_rect[2]
h = seq.init_rect[3]
tic = time.clock()
# starting tracking
tracker = SiamFCTracker(config.model_path, config.gpu_id)
res = []
for idx, frame in enumerate(seq.s_frames):
frame = cv2.cvtColor(cv2.imread(frame), cv2.COLOR_BGR2RGB)
if idx == 0:
bbox = (x, y, w, h)
tracker.init(frame, bbox)
bbox = (bbox[0], bbox[1], bbox[0] + bbox[2], bbox[1] + bbox[3]
) # 1-idx
else:
bbox = tracker.update(frame)
res.append(
(bbox[0], bbox[1], bbox[2] - bbox[0], bbox[3] - bbox[1])) # 1-idx
duration = time.clock() - tic
result = {}
result['res'] = res
result['type'] = 'rect'
result['fps'] = round(seq.len / duration, 3)
return result
def main(video_dir, gpu_id, model_path):
# load videos
filenames = sorted(glob.glob(os.path.join(video_dir, "img/*.jpg")),
key=lambda x: int(os.path.basename(x).split('.')[0]))
frames = [
cv2.cvtColor(cv2.imread(filename), cv2.COLOR_BGR2RGB)
for filename in filenames
]
gt_bboxes = pd.read_csv(os.path.join(video_dir, "groundtruth_rect.txt"),
sep='\t|,| ',
header=None,
names=['xmin', 'ymin', 'width', 'height'],
engine='python')
title = video_dir.split('/')[-1]
# starting tracking
tracker = SiamFCTracker(model_path, gpu_id)
for idx, frame in enumerate(frames):
if idx == 0:
bbox = gt_bboxes.iloc[0].values
tracker.init(frame, bbox)
bbox = (bbox[0] - 1, bbox[1] - 1, bbox[0] + bbox[2] - 1,
bbox[1] + bbox[3] - 1)
else:
bbox = tracker.update(frame)
# bbox xmin ymin xmax ymax
frame = cv2.rectangle(frame, (int(bbox[0]), int(bbox[1])),
(int(bbox[2]), int(bbox[3])), (0, 255, 0), 2)
gt_bbox = gt_bboxes.iloc[idx].values
gt_bbox = (gt_bbox[0], gt_bbox[1], gt_bbox[0] + gt_bbox[2],
gt_bbox[1] + gt_bbox[3])
frame = cv2.rectangle(
frame,
(int(gt_bbox[0] - 1), int(gt_bbox[1] - 1)), # 0-index
(int(gt_bbox[2] - 1), int(gt_bbox[3] - 1)),
(255, 0, 0),
1)
if len(frame.shape) == 3:
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
frame = cv2.putText(frame, str(idx), (5, 20),
cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 255, 0), 1)
cv2.imshow(title, frame)
cv2.waitKey(30)
def main():
# parse arguments
parser = argparse.ArgumentParser(description="Demo SiamFC")
parser.add_argument('-v',
'--video',
default='./video/Basketball',
type=str,
help="the path of video directory")
parser.add_argument('-g',
'--gpuid',
default=0,
type=int,
help="the id of GPU")
parser.add_argument('-m',
'--model',
default='./models/siamfc_pretrained.pth',
type=str,
help="the path of model")
args = parser.parse_args()
video_dir = args.video
gpu_id = args.gpuid
model_path = args.model
# load videos
filenames = sorted(glob.glob(os.path.join(video_dir, "img/*.jpg")),
key=lambda x: int(os.path.basename(x).split('.')[0]))
frames = [
cv2.cvtColor(cv2.imread(filename), cv2.COLOR_BGR2RGB)
for filename in filenames
]
gt_bboxes = pd.read_csv(os.path.join(video_dir, "groundtruth_rect.txt"),
sep='\t|,| ',
header=None,
names=['xmin', 'ymin', 'width', 'height'],
engine='python')
title = video_dir.split('/')[-1]
# starting tracking
tracker = SiamFCTracker(model_path, gpu_id)
for idx, frame in enumerate(frames):
if idx == 0:
bbox = gt_bboxes.iloc[0].values
tracker.init(frame, bbox)
bbox = (bbox[0] - 1, bbox[1] - 1, bbox[0] + bbox[2] - 1,
bbox[1] + bbox[3] - 1)
else:
bbox = tracker.update(frame)
# bbox xmin ymin xmax ymax
frame = cv2.rectangle(frame, (int(bbox[0]), int(bbox[1])),
(int(bbox[2]), int(bbox[3])), (0, 255, 0), 2)
gt_bbox = gt_bboxes.iloc[idx].values
gt_bbox = (gt_bbox[0], gt_bbox[1], gt_bbox[0] + gt_bbox[2],
gt_bbox[1] + gt_bbox[3])
frame = cv2.rectangle(
frame,
(int(gt_bbox[0] - 1), int(gt_bbox[1] - 1)), # 0-index
(int(gt_bbox[2] - 1), int(gt_bbox[3] - 1)),
(255, 0, 0),
1)
if len(frame.shape) == 3:
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
frame = cv2.putText(frame, str(idx), (5, 20),
cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 255, 0), 1)
cv2.imshow(title, frame)
cv2.waitKey(30)
