我正在尝试在我自己的自定义对象检测器上实现排序算法，但是对于空检测的情况，我遇到了一些问题(因为初始帧还没有对象(
我已经从 https://github.com/abewley/sort 克隆了原始排序存储库
这是引发错误的代码(来自 sort.py(：
class Sort(object):
def __init__(self,max_age=1,min_hits=3):
"""
Sets key parameters for SORT
"""
self.max_age = max_age
self.min_hits = min_hits
self.trackers = []
self.frame_count = 0
def update(self,dets):
"""
Params:
dets - a numpy array of detections in the format [[x1,y1,x2,y2,score],[x1,y1,x2,y2,score],...]
Requires: this method must be called once for each frame even with empty detections.
Returns the a similar array, where the last column is the object ID.
NOTE: The number of objects returned may differ from the number of detections provided.
"""
self.frame_count += 1
#get predicted locations from existing trackers.
trks = np.zeros((len(self.trackers),5))
to_del = []
ret = []
for t,trk in enumerate(trks):
#print("[INFO] trk before:", trk)
pos = self.trackers[t].predict()[0]
trk[:] = [pos[0], pos[1], pos[2], pos[3], 0]
#print("[INFO] trk after: ", trk)
if(np.any(np.isnan(pos))):
to_del.append(t)
trks = np.ma.compress_rows(np.ma.masked_invalid(trks))
for t in reversed(to_del):
self.trackers.pop(t)
matched, unmatched_dets, unmatched_trks = associate_detections_to_trackers(dets,trks)
#update matched trackers with assigned detections
for t,trk in enumerate(self.trackers):
if(t not in unmatched_trks):
d = matched[np.where(matched[:,1]==t)[0],0]
trk.update(dets[d,:][0])
#create and initialise new trackers for unmatched detections
for i in unmatched_dets:
print("[INFO] Detection ", i, " from tracker initialization: ", dets[i])
#if len(dets[i]) > 0:
trk = KalmanBoxTracker(dets[i,:])
self.trackers.append(trk)
i = len(self.trackers)
for trk in reversed(self.trackers):
d = trk.get_state()[0]
if((trk.time_since_update < 1) and (trk.hit_streak >= self.min_hits or self.frame_count <= self.min_hits)):
ret.append(np.concatenate((d,[trk.id+1])).reshape(1,-1)) # +1 as MOT benchmark requires positive
i -= 1
#remove dead tracklet
if(trk.time_since_update > self.max_age):
self.trackers.pop(i)
if(len(ret)>0):
return np.concatenate(ret)
return np.empty((0,5))
从以下代码实例化新的 KalmanBoxTracker 时：
def convert_bbox_to_z(bbox):
"""
Takes a bounding box in the form [x1,y1,x2,y2] and returns z in the form
[x,y,s,r] where x,y is the centre of the box and s is the scale/area and r is
the aspect ratio
"""
w = bbox[2]-bbox[0]
h = bbox[3]-bbox[1]
x = bbox[0]+w/2.
y = bbox[1]+h/2.
s = w*h #scale is just area
r = w/float(h)
return np.array([x,y,s,r]).reshape((4,1))
def convert_x_to_bbox(x,score=None):
"""
Takes a bounding box in the centre form [x,y,s,r] and returns it in the form
[x1,y1,x2,y2] where x1,y1 is the top left and x2,y2 is the bottom right
"""
w = np.sqrt(x[2]*x[3])
h = x[2]/w
if(score==None):
return np.array([x[0]-w/2.,x[1]-h/2.,x[0]+w/2.,x[1]+h/2.]).reshape((1,4))
else:
return np.array([x[0]-w/2.,x[1]-h/2.,x[0]+w/2.,x[1]+h/2.,score]).reshape((1,5))
有哪些可能的错误或如何克服这一点，如果没有检测到，我一直在尝试不进行更新，但这样做我无法估计新位置。
此外，注释指示即使没有检测到，也必须调用更新。
任何帮助将不胜感激，问候。
我不知道这是否有帮助。 解决方法之一是在调用跟踪器的位置使用它。但轨道 ID 将不断更新。创建一个单独的轨道 ID 函数以获得平滑的轨道更改。
if box is not None:
x, y, w, h = box
detections = np.array([[x,y,w,h,score]])
trackers = tracker.update(detections,infer_image)
try:
if len(trackers[0]>0):
print(trackers[0][4])
except:
print("nothing to track")
else:
detections = np.array([[0,0,0,0,0]])
trackers = tracker.update(detections,infer_image)
同样，这只是一种解决方法。 对我必须做的事情很有帮助。
更新： 替代解决方案： https://github.com/abewley/sort/issues/73#issuecomment-627327850