# LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
# NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import pyvision as pv
from pyvision.edge.canny import canny # An interface to the OpenCV Canny.
'''
This code is from part 1 of the PyVision Quick Start Guide.
'''
if __name__ == '__main__':
# (1) Load an image from a file.
im = pv.Image(pv.__path__[0] + "/data/nonface/NONFACE_16.jpg")
# (2) Rescale the image
im = pv.AffineScale(0.5, (320, 240)).transformImage(im)
# (3) Run the canny function to locate the edges.
edge_im1 = canny(im)
# (4) Run the canny function with different defaults.
edge_im2 = canny(im, threshold1=100, threshold2=250)
# (5) Save the results to a log.
ilog = pv.ImageLog("../..")
ilog.log(im, label="Source")
ilog.log(edge_im1, label="Canny1")
ilog.log(edge_im2, label="Canny2")
# (6) Display the results.
ilog.show()
import sys
if __name__ == '__main__':
ilog = ImageLog('../..')
source_name = os.path.join(pyvision.__path__[0],'data','misc','p5240019.jpg')
im = Image(source_name)
im = AffineScale(0.25,(320,240)).transformImage(im)
im.show()
ilog.log(im)
mat = im.asMatrix2D()
high = mat > 180
low = mat < 50
mask = high#+low
edges = canny(im,100,200)
ilog.log(edges)
ilog.log(Image(1.0*mask))
e = edges.asPIL().convert('RGB')
m = Image(1.0*mask).asPIL()
i = im.asPIL()
logo = Image(composite(i,e,m))
ilog.log(logo)
#sys.exit()
sm = Image(im.asPIL().resize((320,240),LINEAR))
detector = DetectorDOG()
points = detector.detect(sm)
# Rescale the image
im = pv.AffineScale(0.5, (320, 240)).transformImage(im)
ilog.log(im, label="Source")
# Try a range of sigmas
for sigma in arange(1.0, 5.1, 0.5):
# Perform a Gaussian Blur
mat = im.asMatrix2D()
mat = gaussian_filter(mat, sigma)
blur = pv.Image(mat)
blur.annotateLabel(pv.Point(10, 10), "Sigma: " + str(sigma))
ilog.log(blur, label="Blur")
#Try a range of thresholds
for thresh in arange(50, 150, 10):
# Run the canny function with different defaults.
edge = canny(blur, threshold1=thresh / 2, threshold2=thresh)
# Annotate the edge image
edge.annotateLabel(pv.Point(10, 10), "Sigma: " + str(sigma))
edge.annotateLabel(pv.Point(10, 20), "Thresh: " + str(thresh))
# Save the results to a log.
ilog.log(edge, label="Canny")
# Display the results.
ilog.show()
im = pv.AffineScale(0.5,(320,240)).transformImage(im)
ilog.log(im,label="Source")
# Try a range of sigmas
for sigma in arange(1.0,5.1,0.5):
# Perform a Gaussian Blur
mat = im.asMatrix2D()
mat = gaussian_filter(mat,sigma)
blur = pv.Image(mat)
blur.annotateLabel(pv.Point(10,10),"Sigma: " + str(sigma))
ilog.log(blur,label="Blur")
#Try a range of thresholds
for thresh in arange(50,150,10):
# Run the canny function with different defaults.
edge = canny(blur,threshold1=thresh/2,threshold2=thresh)
# Annotate the edge image
edge.annotateLabel(pv.Point(10,10),"Sigma: " + str(sigma))
edge.annotateLabel(pv.Point(10,20),"Thresh: " + str(thresh))
# Save the results to a log.
ilog.log(edge,label="Canny")
# Display the results.
ilog.show()
import pyvision as pv
from pyvision.edge.canny import canny # An interface to the OpenCV Canny.
'''
This code is from part 1 of the PyVision Quick Start Guide.
'''
if __name__ == '__main__':
# (1) Load an image from a file.
im = pv.Image(pv.__path__[0]+"/data/nonface/NONFACE_16.jpg")
# (2) Rescale the image
im = pv.AffineScale(0.5,(320,240)).transformImage(im)
# (3) Run the canny function to locate the edges.
edge_im1 = canny(im)
# (4) Run the canny function with different defaults.
edge_im2 = canny(im,threshold1=100,threshold2=250)
# (5) Save the results to a log.
ilog = pv.ImageLog("../..")
ilog.log(im,label="Source")
ilog.log(edge_im1,label="Canny1")
ilog.log(edge_im2,label="Canny2")
# (6) Display the results.
ilog.show()