+++ /dev/null
-#!/usr/bin/python
-"""
-This program is demonstration for face and object detection using haar-like features.
-The program finds faces in a camera image or video stream and displays a red box around them.
-
-Original C implementation by: ?
-Python implementation by: Roman Stanchak
-"""
-import sys
-from opencv.cv import *
-from opencv.highgui import *
-
-
-# Global Variables
-cascade = None
-storage = cvCreateMemStorage(0)
-cascade_name = "../../data/haarcascades/haarcascade_frontalface_alt.xml"
-input_name = "../c/lena.jpg"
-
-# Parameters for haar detection
-# From the API:
-# The default parameters (scale_factor=1.1, min_neighbors=3, flags=0) are tuned
-# for accurate yet slow object detection. For a faster operation on real video
-# images the settings are:
-# scale_factor=1.2, min_neighbors=2, flags=CV_HAAR_DO_CANNY_PRUNING,
-# min_size=<minimum possible face size
-min_size = cvSize(20,20)
-image_scale = 1.3
-haar_scale = 1.2
-min_neighbors = 2
-haar_flags = 0
-
-
-def detect_and_draw( img ):
- # allocate temporary images
- gray = cvCreateImage( cvSize(img.width,img.height), 8, 1 );
- small_img = cvCreateImage( cvSize( cvRound (img.width/image_scale),
- cvRound (img.height/image_scale)), 8, 1 );
-
- # convert color input image to grayscale
- cvCvtColor( img, gray, CV_BGR2GRAY );
-
- # scale input image for faster processing
- cvResize( gray, small_img, CV_INTER_LINEAR );
-
- cvEqualizeHist( small_img, small_img );
-
- cvClearMemStorage( storage );
-
- if( cascade ):
- t = cvGetTickCount();
- faces = cvHaarDetectObjects( small_img, cascade, storage,
- haar_scale, min_neighbors, haar_flags, min_size );
- t = cvGetTickCount() - t;
- print "detection time = %gms" % (t/(cvGetTickFrequency()*1000.));
- if faces:
- for face_rect in faces:
- # the input to cvHaarDetectObjects was resized, so scale the
- # bounding box of each face and convert it to two CvPoints
- pt1 = cvPoint( int(face_rect.x*image_scale), int(face_rect.y*image_scale))
- pt2 = cvPoint( int((face_rect.x+face_rect.width)*image_scale),
- int((face_rect.y+face_rect.height)*image_scale) )
- cvRectangle( img, pt1, pt2, CV_RGB(255,0,0), 3, 8, 0 );
-
- cvShowImage( "result", img );
-
-
-if __name__ == '__main__':
-
- if len(sys.argv) > 1:
-
- if sys.argv[1].startswith("--cascade="):
- cascade_name = sys.argv[1][ len("--cascade="): ]
- if len(sys.argv) > 2:
- input_name = sys.argv[2]
-
- elif sys.argv[1] == "--help" or sys.argv[1] == "-h":
- print "Usage: facedetect --cascade=\"<cascade_path>\" [filename|camera_index]\n" ;
- sys.exit(-1)
-
- else:
- input_name = sys.argv[1]
-
- # the OpenCV API says this function is obsolete, but we can't
- # cast the output of cvLoad to a HaarClassifierCascade, so use this anyways
- # the size parameter is ignored
- cascade = cvLoadHaarClassifierCascade( cascade_name, cvSize(1,1) );
-
- if not cascade:
- print "ERROR: Could not load classifier cascade"
- sys.exit(-1)
-
-
- if input_name.isdigit():
- capture = cvCreateCameraCapture( int(input_name) )
- else:
- capture = cvCreateFileCapture( input_name );
-
- cvNamedWindow( "result", 1 );
-
- if( capture ):
- frame_copy = None
- while True:
- frame = cvQueryFrame( capture );
- if( not frame ):
- break;
- if( not frame_copy ):
- frame_copy = cvCreateImage( cvSize(frame.width,frame.height),
- IPL_DEPTH_8U, frame.nChannels );
- if( frame.origin == IPL_ORIGIN_TL ):
- cvCopy( frame, frame_copy );
- else:
- cvFlip( frame, frame_copy, 0 );
-
- detect_and_draw( frame_copy );
-
- if( cvWaitKey( 10 ) >= 0 ):
- break;
-
- else:
- image = cvLoadImage( input_name, 1 );
-
- if( image ):
-
- detect_and_draw( image );
- cvWaitKey(0);
-
- cvDestroyWindow("result");
projects / opencv / blobdiff