jens
5b73cd0e1d
git-svn-id: http://moon:8086/svn/software/trunk/projects/opencv@310 b431acfa-c32f-4a4a-93f1-934dc6c82436
94 lines
2.7 KiB
Python
Executable File
94 lines
2.7 KiB
Python
Executable File
# import the necessary packages
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from __future__ import print_function
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from PiVideoStream import PiVideoStream
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from imutils.video import FPS
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from picamera.array import PiRGBArray
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from picamera import PiCamera
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import numpy as np
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import argparse
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import imutils
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import time
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import cv2
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# construct the argument parse and parse the arguments
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ap = argparse.ArgumentParser()
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ap.add_argument("-n", "--num-frames", type=int, default=100,
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help="# of frames to loop over for FPS test")
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ap.add_argument("-d", "--display", type=int, default=-1,
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help="Whether or not frames should be displayed")
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args = vars(ap.parse_args())
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# created a *threaded *video stream, allow the camera sensor to warmup,
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# and start the FPS counter
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print("[INFO] sampling THREADED frames from `picamera` module...")
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vs = PiVideoStream(resolution=(640,480), framerate=30).start()
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time.sleep(2.0)
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fps = FPS().start()
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# Setup SimpleBlobDetector parameters.
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params = cv2.SimpleBlobDetector_Params()
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# Change thresholds
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params.minThreshold = 10;
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params.maxThreshold = 200;
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# Filter by Area.
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params.filterByArea = True
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params.minArea = 200
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# Filter by Circularity
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params.filterByCircularity = True
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params.minCircularity = 0.5
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# Filter by Convexity
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params.filterByConvexity = False
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params.minConvexity = 0.87
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# Filter by Inertia
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params.filterByInertia = False
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params.minInertiaRatio = 0.01
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# Create a detector with the parameters
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ver = (cv2.__version__).split('.')
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if int(ver[0]) < 3 :
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detector = cv2.SimpleBlobDetector(params)
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else :
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detector = cv2.SimpleBlobDetector_create(params)
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# loop over some frames...this time using the threaded stream
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while fps._numFrames < args["num_frames"]:
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# grab the frame from the threaded video stream
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frame = vs.read()
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# Detect blobs.
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keypoints = detector.detect(frame)
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# Draw detected blobs as red circles.
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# cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS ensures the size of the circle corresponds to the size of blob
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im_with_keypoints = cv2.drawKeypoints(frame, keypoints, np.array([]), (0,0,255), cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
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# Show keypoints
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cv2.imshow("Keypoints", im_with_keypoints)
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cv2.waitKey(1)
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# check to see if the frame should be displayed to our screen
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if args["display"] > 0:
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if frame != None:
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cv2.imshow("Frame", frame)
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key = cv2.waitKey(10) & 0xFF
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# update the FPS counter
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fps.update()
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# stop the timer and display FPS information
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fps.stop()
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vs.stop()
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print("[INFO] elasped time: {:.2f}".format(fps.elapsed()))
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print("[INFO] approx. FPS: {:.2f}".format(fps.fps()))
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print("[INFO] Camera : elasped time: {:.2f}".format(vs.getfps().elapsed()))
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print("[INFO] Camera: approx. FPS: {:.2f}".format(vs.getfps().fps()))
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# do a bit of cleanup
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cv2.destroyAllWindows()
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