demo reconnaissance images

reconnaissance images/object_detection/data/pascal_label_map.pbtxt

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+item {
+  id: 1
+  name: 'aeroplane'
+}
+
+item {
+  id: 2
+  name: 'bicycle'
+}
+
+item {
+  id: 3
+  name: 'bird'
+}
+
+item {
+  id: 4
+  name: 'boat'
+}
+
+item {
+  id: 5
+  name: 'bottle'
+}
+
+item {
+  id: 6
+  name: 'bus'
+}
+
+item {
+  id: 7
+  name: 'car'
+}
+
+item {
+  id: 8
+  name: 'cat'
+}
+
+item {
+  id: 9
+  name: 'chair'
+}
+
+item {
+  id: 10
+  name: 'cow'
+}
+
+item {
+  id: 11
+  name: 'diningtable'
+}
+
+item {
+  id: 12
+  name: 'dog'
+}
+
+item {
+  id: 13
+  name: 'horse'
+}
+
+item {
+  id: 14
+  name: 'motorbike'
+}
+
+item {
+  id: 15
+  name: 'person'
+}
+
+item {
+  id: 16
+  name: 'pottedplant'
+}
+
+item {
+  id: 17
+  name: 'sheep'
+}
+
+item {
+  id: 18
+  name: 'sofa'
+}
+
+item {
+  id: 19
+  name: 'train'
+}
+
+item {
+  id: 20
+  name: 'tvmonitor'
+}

reconnaissance images/object_detection/data/pet_label_map.pbtxt

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+item {
+  id: 1
+  name: 'Abyssinian'
+}
+
+item {
+  id: 2
+  name: 'american_bulldog'
+}
+
+item {
+  id: 3
+  name: 'american_pit_bull_terrier'
+}
+
+item {
+  id: 4
+  name: 'basset_hound'
+}
+
+item {
+  id: 5
+  name: 'beagle'
+}
+
+item {
+  id: 6
+  name: 'Bengal'
+}
+
+item {
+  id: 7
+  name: 'Birman'
+}
+
+item {
+  id: 8
+  name: 'Bombay'
+}
+
+item {
+  id: 9
+  name: 'boxer'
+}
+
+item {
+  id: 10
+  name: 'British_Shorthair'
+}
+
+item {
+  id: 11
+  name: 'chihuahua'
+}
+
+item {
+  id: 12
+  name: 'Egyptian_Mau'
+}
+
+item {
+  id: 13
+  name: 'english_cocker_spaniel'
+}
+
+item {
+  id: 14
+  name: 'english_setter'
+}
+
+item {
+  id: 15
+  name: 'german_shorthaired'
+}
+
+item {
+  id: 16
+  name: 'great_pyrenees'
+}
+
+item {
+  id: 17
+  name: 'havanese'
+}
+
+item {
+  id: 18
+  name: 'japanese_chin'
+}
+
+item {
+  id: 19
+  name: 'keeshond'
+}
+
+item {
+  id: 20
+  name: 'leonberger'
+}
+
+item {
+  id: 21
+  name: 'Maine_Coon'
+}
+
+item {
+  id: 22
+  name: 'miniature_pinscher'
+}
+
+item {
+  id: 23
+  name: 'newfoundland'
+}
+
+item {
+  id: 24
+  name: 'Persian'
+}
+
+item {
+  id: 25
+  name: 'pomeranian'
+}
+
+item {
+  id: 26
+  name: 'pug'
+}
+
+item {
+  id: 27
+  name: 'Ragdoll'
+}
+
+item {
+  id: 28
+  name: 'Russian_Blue'
+}
+
+item {
+  id: 29
+  name: 'saint_bernard'
+}
+
+item {
+  id: 30
+  name: 'samoyed'
+}
+
+item {
+  id: 31
+  name: 'scottish_terrier'
+}
+
+item {
+  id: 32
+  name: 'shiba_inu'
+}
+
+item {
+  id: 33
+  name: 'Siamese'
+}
+
+item {
+  id: 34
+  name: 'Sphynx'
+}
+
+item {
+  id: 35
+  name: 'staffordshire_bull_terrier'
+}
+
+item {
+  id: 36
+  name: 'wheaten_terrier'
+}
+
+item {
+  id: 37
+  name: 'yorkshire_terrier'
+}

reconnaissance images/object_detection/filevideostream.py

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+# import the necessary packages
+from threading import Thread
+import sys
+import cv2
+
+# import the Queue class from Python 3
+if sys.version_info >= (3, 0):
+	from queue import Queue
+
+# otherwise, import the Queue class for Python 2.7
+else:
+	from Queue import Queue
+
+class FileVideoStream:
+	def __init__(self, path, queueSize=128):
+		# initialize the file video stream along with the boolean
+		# used to indicate if the thread should be stopped or not
+		self.stream = cv2.VideoCapture(path)
+		self.stopped = False
+
+		# initialize the queue used to store frames read from
+		# the video file
+		self.Q = Queue(maxsize=queueSize)
+
+	def start(self):
+		# start a thread to read frames from the file video stream
+		t = Thread(target=self.update, args=())
+		t.daemon = True
+		t.start()
+		return self
+
+	def update(self):
+		# keep looping infinitely
+		while True:
+			# if the thread indicator variable is set, stop the
+			# thread
+			if self.stopped:
+				return
+
+			# otherwise, ensure the queue has room in it
+			if not self.Q.full():
+				# read the next frame from the file
+				(grabbed, frame) = self.stream.read()
+
+				# if the `grabbed` boolean is `False`, then we have
+				# reached the end of the video file
+				if not grabbed:
+					self.stop()
+					return
+
+				# add the frame to the queue
+				self.Q.put(frame)
+
+	def read(self):
+		# return next frame in the queue
+		return self.Q.get()
+
+	def more(self):
+		# return True if there are still frames in the queue
+		return self.Q.qsize() > 0
+
+	def stop(self):
+		# indicate that the thread should be stopped
+		self.stopped = True

reconnaissance images/object_detection/fps.py

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+# import the necessary packages
+import datetime
+
+class FPS:
+	def __init__(self):
+		# store the start time, end time, and total number of frames
+		# that were examined between the start and end intervals
+		self._start = None
+		self._end = None
+		self._numFrames = 0
+
+	def start(self):
+		# start the timer
+		self._start = datetime.datetime.now()
+		return self
+
+	def stop(self):
+		# stop the timer
+		self._end = datetime.datetime.now()
+
+	def update(self):
+		# increment the total number of frames examined during the
+		# start and end intervals
+		self._numFrames += 1
+
+	def elapsed(self):
+		# return the total number of seconds between the start and
+		# end interval
+		return (self._end - self._start).total_seconds()
+
+	def fps(self):
+		# compute the (approximate) frames per second
+		return self._numFrames / self.elapsed()