Slight improvement to SymbolDetector FPS in threaded env

playgrounds/symbol_detect_test.py

@@ -1,4 +1,19 @@
 from src.detector.SymbolDetector import SymbolDetector
-
+from imutils.video import FPS
 detector = SymbolDetector()
-detector.detect()
+detector.start()
+fps = FPS().start()
+
+frame_count = 0
+
+while frame_count < 100:
+    frame = detector.get_frame()
+    symbol_match = detector.detect(frame)
+    if symbol_match is not None:
+        print('Symbol Match ID: ' + str(symbol_match))
+    fps.update()
+    frame_count = frame_count + 1
+
+fps.stop()
+print('Elapsed Time: ' + str(fps.elapsed()))
+print('Frames per Sec: ' + str(fps.fps()))

requirements.txt

@@ -0,0 +1,25 @@
+Pillow==2.6.1
+PyBluez==0.22
+RPi.GPIO==0.6.3
+RTIMULib==7.2.1
+chardet==2.3.0
+colorama==0.3.2
+gpiozero==1.4.0
+html5lib==0.999
+imutils==0.5.3
+mcpi==0.1.1
+numpy==1.8.2
+pgzero==1.1
+picamera==1.10
+pifacecommon==4.2.1
+pifacedigitalio==3.1.0
+pygame==1.9.2a0
+pyserial==2.6
+python-apt==0.9.3.12
+python-debian==0.1.27
+requests==2.4.3
+sense-hat==2.2.0
+six==1.8.0
+spidev==3.0
+urllib3==1.9.1
+wheel==0.24.0

src/config.py

@@ -23,7 +23,7 @@
 # Image Recognition Settings
 CAMERA_RES_WIDTH = 540
 CAMERA_RES_HEIGHT = 480
-CAMERA_FRAMERATE = 30
+CAMERA_FRAMERATE = 32
 
 MIN_CONTOUR_AREA = 1800 # Assuming at a distance of 20 - 25cm
 MAX_CONTOUR_AREA = 6800 # Assuming min distance of 10 - 15cm

src/detector/Symbol.py

@@ -13,6 +13,7 @@ def __init__(self):
         self.img = []
         self.id = 0
         self.name = ''
+        self.contour = None
 
 def load_symbols(filepath):
     '''
@@ -26,5 +27,11 @@ def load_symbols(filepath):
         symbols[i].id = SYMBOL_ID_MAP[symbol]
         filename = '{}.jpg'.format(symbol)
         symbols[i].img = cv.imread(filepath + '/' + filename)
+
+        train_symbol_gray = cv.cvtColor(symbols[i].img, cv.COLOR_BGR2GRAY)
+        _, train_symbol_thresh = cv.threshold(train_symbol_gray, 127, 255, 0)
+        _, train_symbol_ctrs, _ = cv.findContours(train_symbol_thresh, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
+        train_symbol_ctrs = sorted(train_symbol_ctrs, key=cv.contourArea, reverse=True)
+        symbols[i].contour = train_symbol_ctrs[0]
 
     return symbols

src/detector/SymbolDetector.py

@@ -35,7 +35,7 @@ def __init__(self, width=CAMERA_RES_WIDTH, height=CAMERA_RES_HEIGHT, framerate=C
     def start(self):
         self.video_stream.start()
         time.sleep(3)
-        log.info('Detecting for Symbols')
+        log.info('Detecting for Symbols')    
 
     def get_frame(self):
         return self.video_stream.read()
@@ -63,13 +63,7 @@ def detect(self, image):
 
             match_results = []
             for train_symbol in self.train_symbols:
-                train_symbol_gray = cv.cvtColor(train_symbol.img, cv.COLOR_BGR2GRAY)
-                _, train_symbol_thresh = cv.threshold(train_symbol_gray, 127, 255, 0)
-                _, train_symbol_ctrs, _ = cv.findContours(train_symbol_thresh, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
-                train_symbol_ctrs = sorted(train_symbol_ctrs, key=cv.contourArea, reverse=True)
-                train_symbol_ctr = train_symbol_ctrs[0]
-
-                match_score = cv.matchShapes(symbol_contour, train_symbol_ctr, 1, 0.0)
+                match_score = cv.matchShapes(symbol_contour, train_symbol.contour, 1, 0.0)
                 match_results.append({
                     'score': match_score,
                     'contour': symbol_contour,