Make package

README.md

@@ -39,7 +39,7 @@ If you find this repo useful in your research, please consider citing:
 
 ### Dependencies:
 
-To install required dependencies run:
+To install required dependencies for SORT and the demo, run:
 ```
 $ pip install -r requirements.txt
 ```
@@ -51,7 +51,7 @@ To run the tracker with the provided detections:
 
 ```
 $ cd path/to/sort
-$ python sort.py
+$ python demo.py
 ```
 
 To display the results you need to:
@@ -63,7 +63,7 @@ To display the results you need to:
   ```
 0. Run the demo with the ```--display``` flag
   ```
-  $ python sort.py --display
+  $ python demo.py --display
   ```
 
 
@@ -84,7 +84,9 @@ Using the [MOT challenge devkit](https://motchallenge.net/devkit/) the method pr
 
 ### 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.
+To use SORT in your project, you can either install it locally with `pip install .` or simply copy [sort.py](sort/sort.py).
+
+Below is the gist of how to instantiate and update SORT. See the [`__main__`](demo.py#L28) section of [demo.py](demo.py) for a complete example.
 
     from sort import *
 

demo.py

@@ -0,0 +1,85 @@
+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
+import time
+import argparse
+
+from sort import Sort
+
+np.random.seed(0)
+
+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')
+    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() #create instance of the SORT tracker
+    seq_dets = np.loadtxt(seq_dets_fn, delimiter=',')
+    seq = seq_dets_fn[pattern.find('*'):].split('/')[0]
+
+    with open('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 = 'mot_benchmark/%s/%s/img1/%06d.jpg'%(phase, seq, 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")

setup.py

@@ -0,0 +1,11 @@
+from setuptools import setup, find_packages
+
+setup(
+    name='sort',
+    version='1.0',
+    author='Alex Bewley',
+    packages=find_packages(),
+    install_requires=['filterpy', 'lap'],
+    python_requires='>=3.6'
+)
+

sort/__init__.py

@@ -0,0 +1 @@
+from .sort import Sort

sort.py → sort/sort.py

@@ -15,19 +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
-import time
-import argparse
 from filterpy.kalman import KalmanFilter
 
 try:
@@ -36,8 +25,6 @@
   def jit(func):
     return func
 
-np.random.seed(0)
-
 
 def linear_assignment(cost_matrix):
   try:
@@ -258,70 +245,3 @@ def update(self, dets=np.empty((0, 5))):
       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')
-    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() #create instance of the SORT tracker
-    seq_dets = np.loadtxt(seq_dets_fn, delimiter=',')
-    seq = seq_dets_fn[pattern.find('*'):].split('/')[0]
-
-    with open('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 = 'mot_benchmark/%s/%s/img1/%06d.jpg'%(phase, seq, 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")