Make it into installable package

.gitignore

@@ -1,2 +1,6 @@
 output/
 mot_benchmark
+venv
+dist
+build
+**/*egg-info

README.md

@@ -18,6 +18,8 @@ For your convenience, this repo also contains *Faster* RCNN detections for the M
 **Also see:**
 A new and improved version of SORT with a Deep Association Metric implemented in tensorflow is available at [https://github.com/nwojke/deep_sort](https://github.com/nwojke/deep_sort) .
 
+This fork packages the SORT algorithm as a pip package (simple-online-realtime-tracking).
+
 ### License
 
 SORT is released under the GPL License (refer to the LICENSE file for details) to promote the open use of the tracker and future improvements. If you require a permissive license contact Alex (alex@bewley.ai).
@@ -36,37 +38,13 @@ If you find this repo useful in your research, please consider citing:
       doi={10.1109/ICIP.2016.7533003}
     }
 
+### Installing:
 
-### Dependencies:
+To install the package:
-
-To install required dependencies run:
 ```
-$ pip install -r requirements.txt
+pip install simple-online-realtime-tracking==0.2
 ```
 
-
-### Demo:
-
-To run the tracker with the provided detections:
-
-```
-$ cd path/to/sort
-$ python sort.py
-```
-
-To display the results you need to:
-
-1. Download the [2D MOT 2015 benchmark dataset](https://motchallenge.net/data/2D_MOT_2015/#download)
-0. Create a symbolic link to the dataset
-  ```
-  $ ln -s /path/to/MOT2015_challenge/data/2DMOT2015 mot_benchmark
-  ```
-0. Run the demo with the ```--display``` flag
-  ```
-  $ python sort.py --display
-  ```
-
-
 ### Main Results
 
 Using the [MOT challenge devkit](https://motchallenge.net/devkit/) the method produces the following results (as described in the paper).
@@ -81,12 +59,11 @@ Using the [MOT challenge devkit](https://motchallenge.net/devkit/) the method pr
  KITTI-17       | 67.1 | 92.3 | 0.26 |  9   1   8   0|   38   225    9   16|  60.2  72.3  61.3
  *Overall*      | 49.5 | 77.5 | 1.24 | 234  48 111  75| 3311 11660  274  499|  34.0  73.3  35.1
 
-
 ### Using SORT in your own project
 
 Below is the gist of how to instantiate and update SORT. See the ['__main__'](https://github.com/abewley/sort/blob/master/sort.py#L239) section of [sort.py](https://github.com/abewley/sort/blob/master/sort.py#L239) for a complete example.
     
-    from sort import *
+    from sort import Sort
     
     #create instance of SORT
     mot_tracker = Sort() 

pyproject.toml

@@ -0,0 +1,6 @@
+[build-system]
+requires = [
+    "setuptools>=42",
+    "wheel"
+]
+build-backend = "setuptools.build_meta"

requirements.txt

@@ -1,3 +0,0 @@
-filterpy==1.4.5
-scikit-image==0.17.2
-lap==0.4.0

setup.cfg

@@ -0,0 +1,23 @@
+[metadata]
+name = simple-online-realtime-tracking
+version = 0.2
+author = Alex Bewley
+description = A simple online and realtime tracking algorithm for 2D multiple object tracking in video sequences
+long_description = file: README.md
+long_description_content_type = text/markdown
+url = https://github.com/timstokman/sort
+classifiers = 
+    Programming Language :: Python :: 3
+    Operating System :: OS Independent
+    License :: OSI Approved :: GNU General Public License v3 (GPLv3)
+
+[options]
+package_dir =
+    = src
+packages = sort
+python_requires = >=3.8
+install_requires =
+    filterpy==1.4.5
+    scikit-image==0.17.2
+    lap==0.4.0
+    numpy>=1.18.5

src/sort/__init__.py

@@ -0,0 +1,18 @@
+"""
+    SORT: A Simple, Online and Realtime Tracker
+    Copyright (C) 2016-2020 Alex Bewley alex@bewley.ai
+
+    This program is free software: you can redistribute it and/or modify
+    it under the terms of the GNU General Public License as published by
+    the Free Software Foundation, either version 3 of the License, or
+    (at your option) any later version.
+
+    This program is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+    GNU General Public License for more details.
+
+    You should have received a copy of the GNU General Public License
+    along with this program.  If not, see <http://www.gnu.org/licenses/>.
+"""
+from .sort import Sort

src/sort/sort.py

@@ -15,14 +15,8 @@
     You should have received a copy of the GNU General Public License
     along with this program.  If not, see <http://www.gnu.org/licenses/>.
 """
-from __future__ import print_function
-
 import os
 import numpy as np
-import matplotlib
-matplotlib.use('TkAgg')
-import matplotlib.pyplot as plt
-import matplotlib.patches as patches
 from skimage import io
 
 import glob
@@ -119,6 +113,7 @@ class KalmanBoxTracker(object):
     self.hits = 0
     self.hit_streak = 0
     self.age = 0
+    self.original_id = bbox[5]
 
   def update(self,bbox):
     """
@@ -128,6 +123,7 @@ class KalmanBoxTracker(object):
     self.history = []
     self.hits += 1
     self.hit_streak += 1
+    self.original_id = bbox[5]
     self.kf.update(convert_bbox_to_z(bbox))
 
   def predict(self):
@@ -243,7 +239,7 @@ class Sort(object):
     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
+          ret.append(np.concatenate((d,[trk.id+1],[trk.original_id])).reshape(1,-1)) # +1 as MOT benchmark requires positive
         i -= 1
         # remove dead tracklet
         if(trk.time_since_update > self.max_age):
@@ -251,80 +247,3 @@ class Sort(object):
     if(len(ret)>0):
       return np.concatenate(ret)
     return np.empty((0,5))
-
-def parse_args():
-    """Parse input arguments."""
-    parser = argparse.ArgumentParser(description='SORT demo')
-    parser.add_argument('--display', dest='display', help='Display online tracker output (slow) [False]',action='store_true')
-    parser.add_argument("--seq_path", help="Path to detections.", type=str, default='data')
-    parser.add_argument("--phase", help="Subdirectory in seq_path.", type=str, default='train')
-    parser.add_argument("--max_age", 
-                        help="Maximum number of frames to keep alive a track without associated detections.", 
-                        type=int, default=1)
-    parser.add_argument("--min_hits", 
-                        help="Minimum number of associated detections before track is initialised.", 
-                        type=int, default=3)
-    parser.add_argument("--iou_threshold", help="Minimum IOU for match.", type=float, default=0.3)
-    args = parser.parse_args()
-    return args
-
-if __name__ == '__main__':
-  # all train
-  args = parse_args()
-  display = args.display
-  phase = args.phase
-  total_time = 0.0
-  total_frames = 0
-  colours = np.random.rand(32, 3) #used only for display
-  if(display):
-    if not os.path.exists('mot_benchmark'):
-      print('\n\tERROR: mot_benchmark link not found!\n\n    Create a symbolic link to the MOT benchmark\n    (https://motchallenge.net/data/2D_MOT_2015/#download). E.g.:\n\n    $ ln -s /path/to/MOT2015_challenge/2DMOT2015 mot_benchmark\n\n')
-      exit()
-    plt.ion()
-    fig = plt.figure()
-    ax1 = fig.add_subplot(111, aspect='equal')
-
-  if not os.path.exists('output'):
-    os.makedirs('output')
-  pattern = os.path.join(args.seq_path, phase, '*', 'det', 'det.txt')
-  for seq_dets_fn in glob.glob(pattern):
-    mot_tracker = Sort(max_age=args.max_age, 
-                       min_hits=args.min_hits,
-                       iou_threshold=args.iou_threshold) #create instance of the SORT tracker
-    seq_dets = np.loadtxt(seq_dets_fn, delimiter=',')
-    seq = seq_dets_fn[pattern.find('*'):].split(os.path.sep)[0]
-    
-    with open(os.path.join('output', '%s.txt'%(seq)),'w') as out_file:
-      print("Processing %s."%(seq))
-      for frame in range(int(seq_dets[:,0].max())):
-        frame += 1 #detection and frame numbers begin at 1
-        dets = seq_dets[seq_dets[:, 0]==frame, 2:7]
-        dets[:, 2:4] += dets[:, 0:2] #convert to [x1,y1,w,h] to [x1,y1,x2,y2]
-        total_frames += 1
-
-        if(display):
-          fn = os.path.join('mot_benchmark', phase, seq, 'img1', '%06d.jpg'%(frame))
-          im =io.imread(fn)
-          ax1.imshow(im)
-          plt.title(seq + ' Tracked Targets')
-
-        start_time = time.time()
-        trackers = mot_tracker.update(dets)
-        cycle_time = time.time() - start_time
-        total_time += cycle_time
-
-        for d in trackers:
-          print('%d,%d,%.2f,%.2f,%.2f,%.2f,1,-1,-1,-1'%(frame,d[4],d[0],d[1],d[2]-d[0],d[3]-d[1]),file=out_file)
-          if(display):
-            d = d.astype(np.int32)
-            ax1.add_patch(patches.Rectangle((d[0],d[1]),d[2]-d[0],d[3]-d[1],fill=False,lw=3,ec=colours[d[4]%32,:]))
-
-        if(display):
-          fig.canvas.flush_events()
-          plt.draw()
-          ax1.cla()
-
-  print("Total Tracking took: %.3f seconds for %d frames or %.1f FPS" % (total_time, total_frames, total_frames / total_time))
-
-  if(display):
-    print("Note: to get real runtime results run without the option: --display")