-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathtracker.py
163 lines (139 loc) · 5.87 KB
/
tracker.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
from collections import Counter
from colorsys import hls_to_rgb
from copy import deepcopy
import json
import numpy as np
from fish_length import Fish_Length
from sort import Sort
class Tracker:
def __init__(self, clip_info, algorithm=Sort, args={'max_age':1, 'min_hits':0, 'iou_threshold':0.05}, min_hits=3):
self.algorithm = algorithm(**args)
self.fish_ids = Counter()
self.min_hits = min_hits
self.json_data = deepcopy(clip_info)
self.frame_id = self.json_data['start_frame']
self.json_data['frames'] = []
# Boxes should be given in normalized [x1,y1,x2,y2,score,track_id]
def update(self, dets=np.empty((0, 6))):
new_frame_entries = []
for track in self.algorithm.update(dets):
self.fish_ids[int(track[5])] += 1
new_frame_entries.append({
'fish_id': int(track[5]),
'bbox': list(track[:4]),
'score': track[4],
'visible': 1,
'human_labeled': 0
})
new_frame_entries = sorted(new_frame_entries, key=lambda k: k['fish_id'])
self.json_data['frames'].append(
{
'frame_num': self.frame_id,
'fish': new_frame_entries
})
self.frame_id += 1
def finalize(self, output_path=None, min_length=-1.0): # vert_margin=0.0
json_data = deepcopy(self.json_data)
# map (valid) fish IDs to 0, 1, 2, ...
fish_id_map = {}
for fish_id, count in self.fish_ids.items():
if count >= self.min_hits:
fish_id_map[fish_id] = len(fish_id_map)
# separate frame boxes into tracks, keyed by mapped IDs
# each track is a list of tuples ( bbox, frame_num )
tracks = { v : [] for _, v in fish_id_map.items() }
for frame in json_data['frames']:
for bbox in frame['fish']:
# check if valid
if bbox['fish_id'] in fish_id_map.keys():
track_id = fish_id_map[bbox['fish_id']]
tracks[track_id].append((bbox['bbox'], frame['frame_num']))
# map IDs and keep frame['fish'] sorted by ID
for i, frame in enumerate(json_data['frames']):
new_frame_entries = []
for frame_entry in frame['fish']:
if frame_entry['fish_id'] in fish_id_map:
frame_entry['fish_id'] = fish_id_map[frame_entry['fish_id']]
new_frame_entries.append(frame_entry)
frame['fish'] = sorted(new_frame_entries, key=lambda k: k['fish_id'])
# create summary 'fish' entry for json data
json_data['fish'] = []
for track_id, boxes in tracks.items():
fish_entry = {}
fish_entry['id'] = track_id
fish_entry['length'] = -1
# top = False
# bottom = False
# for frame in json_data['frames']:
# for frame_entry in frame['fish']:
# if frame_entry['fish_id'] == track_id:
# if frame_entry['bbox'][3] > vert_margin:
# top = True
# if frame_entry['bbox'][1] < 1 - vert_margin:
# bottom = True
# break
# if not top or not bottom:
# continue
start_bbox = boxes[0][0]
end_bbox = boxes[-1][0]
fish_entry['direction'] = Tracker.get_direction(start_bbox, end_bbox)
fish_entry['start_frame_index'] = boxes[0][1]
fish_entry['end_frame_index'] = boxes[-1][1]
fish_entry['color'] = Tracker.selectColor(track_id)
json_data['fish'].append(fish_entry)
# filter 'fish' field by fish length
json_data = Fish_Length.add_lengths(json_data)
invalid_ids = []
if min_length != -1.0:
new_fish = []
for fish in json_data['fish']:
if fish['length'] > min_length:
new_fish.append(fish)
else:
invalid_ids.append(fish['id'])
json_data['fish'] = new_fish
# filter 'frames' field by fish length
if len(invalid_ids):
for frame in json_data['frames']:
new_fish = []
for fish in frame['fish']:
if fish['fish_id'] not in invalid_ids:
new_fish.append(fish)
frame['fish'] = new_fish
if output_path is not None:
with open(output_path,'w') as output:
json.dump(json_data, output, indent=2)
return json_data
def state(self, output_path=None):
json_data = deepcopy(self.json_data)
if output_path is not None:
with open(output_path,'w') as output:
json.dump(json_data, output, indent=2)
return json_data
@staticmethod
def selectColor(number):
hue = ((number * 137.508 + 60) % 360) / 360
return '#{0:02x}{1:02x}{2:02x}'.format(*(int(n * 255) for n in hls_to_rgb(hue, 0.5, 0.75)))
@staticmethod
def get_direction(start_bbox, end_bbox):
start_center = (start_bbox[2] + start_bbox[0])/2
end_center = (end_bbox[2] + end_bbox[0])/2
if start_center < 0.5 and end_center >= 0.5:
return 'right'
elif start_center >= 0.5 and end_center < 0.5:
return 'left'
else:
return 'none'
@staticmethod
def count_dirs(json_data):
right = 0
left = 0
none = 0
for fish_entry in json_data['fish']:
if fish_entry['direction'] == 'right':
right += 1
elif fish_entry['direction'] == 'left':
left += 1
else:
none += 1
return (right, left, none)