From e0c1fb5f769a692474b24dbead8c16e38bd1dd68 Mon Sep 17 00:00:00 2001
From: Alexander Mordvintsev <no@email>
Date: Mon, 28 May 2012 08:51:50 +0000
Subject: [PATCH] updated video_threaded.py sample: - switch btw threaded and
 non-threaded mode - performance counters - description

---
 samples/python2/common.py         | 11 +++++
 samples/python2/video_threaded.py | 73 ++++++++++++++++++++++++++-----
 2 files changed, 74 insertions(+), 10 deletions(-)

diff --git a/samples/python2/common.py b/samples/python2/common.py
index 7319ceb7d4..54e23d60d8 100644
--- a/samples/python2/common.py
+++ b/samples/python2/common.py
@@ -126,6 +126,17 @@ def Timer(msg):
     finally:
         print "%.2f ms" % ((clock()-start)*1000)
 
+class StatValue:
+    def __init__(self, smooth_coef = 0.5):
+        self.value = None
+        self.smooth_coef = smooth_coef
+    def update(self, v):
+        if self.value is None:
+            self.value = v
+        else:
+            c = self.smooth_coef
+            self.value = c * self.value + (1.0-c) * v
+
 class RectSelector:
     def __init__(self, win, callback):
         self.win = win
diff --git a/samples/python2/video_threaded.py b/samples/python2/video_threaded.py
index 85d9b6a3d6..6f92d06638 100644
--- a/samples/python2/video_threaded.py
+++ b/samples/python2/video_threaded.py
@@ -1,29 +1,82 @@
+'''
+Multithreaded video processing sample.
+Usage:
+   video_threaded.py {<video device number>|<video file name>}
+
+   Shows how python threading capabilities can be used 
+   to organize parallel captured frame processing pipeline 
+   for smoother playback.
+   
+Keyboard shortcuts:
+
+   ESC - exit
+   space - switch between multi and single threaded processing
+'''
+
+
 import numpy as np
 import cv2
 
 from multiprocessing.pool import ThreadPool
 from collections import deque
 
+from common import clock, draw_str, StatValue
+import video
+            
+
+class DummyTask:
+    def __init__(self, data):
+        self.data = data
+    def ready(self):
+        return True
+    def get(self):
+        return self.data
 
 if __name__ == '__main__':
-    def process_frame(frame):
+    import sys
+    
+    print __doc__
+
+    try: fn = sys.argv[1]
+    except: fn = 0
+    cap = video.create_capture(fn)
+   
+    
+    def process_frame(frame, t0):
         # some intensive computation...
         frame = cv2.medianBlur(frame, 19)
         frame = cv2.medianBlur(frame, 19)
-        frame = cv2.medianBlur(frame, 19)
-        return frame
+        return frame, t0
 
-    threadn = 8
-    cap = cv2.VideoCapture(0)
+    threadn = cv2.getNumberOfCPUs()
     pool = ThreadPool(processes = threadn)
     pending = deque()
+
+    threaded_mode = True
+
+    latency = StatValue()
+    frame_interval = StatValue()
+    last_frame_time = clock()
     while True:
         while len(pending) > 0 and pending[0].ready():
-            res = pending.popleft().get()
-            cv2.imshow('result', res)
-        if len(pending) < threadn+1:
+            res, t0 = pending.popleft().get()
+            latency.update(clock() - t0)
+            draw_str(res, (20, 20), "threaded      :  " + str(threaded_mode))
+            draw_str(res, (20, 40), "latency        :  %.1f ms" % (latency.value*1000))
+            draw_str(res, (20, 60), "frame interval :  %.1f ms" % (frame_interval.value*1000))
+            cv2.imshow('threaded video', res)
+        if len(pending) < threadn:
             ret, frame = cap.read()
-            task = pool.apply_async(process_frame, (frame.copy(),))
+            t = clock()
+            frame_interval.update(t - last_frame_time)
+            last_frame_time = t
+            if threaded_mode:
+                task = pool.apply_async(process_frame, (frame.copy(), t))
+            else:
+                task = DummyTask(process_frame(frame, t))
             pending.append(task)
-        if cv2.waitKey(1) == 27:
+        ch = cv2.waitKey(1)
+        if ch == ord(' '):
+            threaded_mode = not threaded_mode
+        if ch == 27:
             break