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POOpenCV face detection is slow on Raspberry Pi
 

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  1. POOpenCV face detection is slow on Raspberry Pi
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    <p>I am testing Raspberry Pi with OpenCV and Python coding. The video streaming works great (medium speed), but when I run face detection on the stream the CPU is pegged and refreshing the image is slow.</p> <p>Here is what I have. How can I optimize my code?</p> <pre><code>#!/usr/bin/env python import sys import cv2.cv as cv from optparse import OptionParser min_size = (20, 20) image_scale = 2 haar_scale = 1.2 min_neighbors = 2 haar_flags = 0 def detect_and_draw(img, cascade): # allocate temporary images gray = cv.CreateImage((img.width,img.height), 8, 1) small_img = cv.CreateImage((cv.Round(img.width / image_scale), cv.Round (img.height / image_scale)), 8, 1) cv.Round (img.height / image_scale)), 8, 1) # convert color input image to grayscale cv.CvtColor(img, gray, cv.CV_BGR2GRAY) # scale input image for faster processing cv.Resize(gray, small_img, cv.CV_INTER_LINEAR) cv.EqualizeHist(small_img, small_img) if(cascade): t = cv.GetTickCount() faces = cv.HaarDetectObjects(small_img, cascade, cv.CreateMemStorage(0), haar_scale, min_neighbors, haar_flags, min_size) t = cv.GetTickCount() - t print "detection time = %gms" % (t/(cv.GetTickFrequency()*1000.)) if faces: for ((x, y, w, h), n) in faces: # the input to cv.HaarDetectObjects was resized, so scale the # bounding box of each face and convert it to two CvPoints pt1 = (int(x * image_scale), int(y * image_scale)) # bounding box of each face and convert it to two CvPoints pt1 = (int(x * image_scale), int(y * image_scale)) pt2 = (int((x + w) * image_scale), int((y + h) * image_scale)) cv.Rectangle(img, pt1, pt2, cv.RGB(255, 0, 0), 3, 8, 0) cv.ShowImage("result", img) if __name__ == '__main__': parser = OptionParser(usage = "usage: %prog [options] [camera_index]") parser.add_option("-c", "--cascade", action="store", dest="cascade", type="str", help="Haar cascade file, default %default", default = "/usr/local/share/OpenCV/haarcascades") (options, args) = parser.parse_args() cascade = cv.Load(options.cascade) capture = cv.CreateCameraCapture(0) cv.NamedWindow("result", 1) if capture: frame_copy = None while True: frame = cv.QueryFrame(capture) if not frame: cv.WaitKey(0) break if not frame_copy: frame_copy = cv.CreateImage((frame.width,frame.height), cv.IPL_DEPTH_8U, frame.nChannels) if frame.origin == cv.IPL_ORIGIN_TL: cv.Copy(frame, frame_copy) else: cv.Copy(frame, frame_copy) else: cv.Flip(frame, frame_copy, 0) detect_and_draw(frame_copy, cascade) if cv.WaitKey(10) != -1: break else: image = cv.LoadImage(input_name, 1) detect_and_draw(image, cascade) cv.WaitKey(0) cv.DestroyWindow("result") </code></pre>
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    1. USMartijn Pieters
    1. UShoneyshell
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      1. POOpenCV face detection is slow on Raspberry Pi
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      1. VTUpMod
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      1. POOpenCV face detection is slow on Raspberry Pi
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      1. POOpenCV face detection is slow on Raspberry Pi
      1. USGeorge Profenza
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    1. COYour `parser.add_option` line is truncated, I think.
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      1. POOpenCV face detection is slow on Raspberry Pi
      1. USMartijn Pieters
    2. COYes, it is. But that's not the point of my question.
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      1. UShoneyshell
    3. COI never said it was. :-) Just giving you the opportunity to correct that; I've closed the string and parenthesis.
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      1. POOpenCV face detection is slow on Raspberry Pi
      1. USMartijn Pieters
 

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