Hi guys, Please remove me from this mailing list. On Apr 3, 2017 5:18 PM, "Serge Shakhov via scikit-image" < scikit-image@python.org> wrote:
> Hi Stefan, > > Thanks for your reply. > My experience with scikit-image just started with this script, I'm not > experienced at all. > Here is the test script: > > import skimage.transform > import matplotlib.pyplot as plt > from PIL import Image > from skimage import data > from skimage.transform import resize > from skimage.transform import rescale > import numpy as np > import os > from skimage import io > > srcIm = data.checkerboard() > src = np.array([[(0,0),(100,0),(110,0)],[(0,110),(100,110),(110,110)]]) > dst = np.array([[(0,0),(50,0),(70,0)],[(0,20),(60,50),(100,100)]]) > > src = src.astype(float) > dst = dst.astype(float) > > #revert to 1D list > src = src.reshape(((src.shape[0]*src.shape[1]),2), order='F') > dst = dst.reshape(((dst.shape[0]*dst.shape[1]),2), order='F') > > #Perform transform > piecewiseAffine = skimage.transform.PiecewiseAffineTransform() > piecewiseAffine.estimate(src,dst) > dstArr = skimage.transform.warp(srcIm, piecewiseAffine, order=1, > mode='constant', cval=0, clip=False, preserve_range=False) > > #Visualise result > dstArr = np.array(dstArr * 255., dtype=np.uint8) > > dstIm = Image.fromarray(dstArr) > dstIm.show() > > Could you help me and point to what I have to modify here? > > If I reverse the piecewiseAffine.estimate(src,dst) > -->> piecewiseAffine.estimate(dst, src) > I can get the opposite transformation and it's not cropped, but not the > one I need. > > Thanks. > > > Best regards, > Serge Shakhov. > > > On Tuesday, 4 April 2017, 3:56, Stefan van der Walt <stef...@berkeley.edu> > wrote: > > > Hi Serge > > On Sun, Apr 2, 2017, at 15:30, Serge Shakhov via scikit-image wrote: > > But I didn't find an answer. > I'm doing 2D piecewise affine transformation with skimage.transform. > PiecewiseAffineTransform > Result image is heavily cropped. > I tried to play with output_shape, mode and clip parameters but without > any effect, image is still cropped. > Could anyone point me what am I doing wrong? > > > I thought we had this implemented, but I guess not yet. You can see how > here: > > https://github.com/scikit-image/skimage-tutorials/blob/ > master/lectures/adv3_panorama-stitching.ipynb > > Specifically: > > *from* *skimage.transform* *import* SimilarityTransform > *# Shape of middle image, our registration target*r, c = image.shape > *# Note that transformations take coordinates in (x, y) format,**# not (row, > column), in order to be consistent with most literature*corners = > np.array([[0, 0], > [0, r], > [c, 0], > [c, r]]) > *# Warp the image corners to their new positions*warped_corners = > my_tf(corners) > *# The overall output shape will be max - min*corner_min = np.min(corners, > axis=0)corner_max = np.max(corners, axis=0)output_shape = (corner_max - > corner_min) > *# Ensure integer shape with np.ceil and dtype conversion*output_shape = > np.ceil(output_shape[::-1]).astype(int) > > > That calculates the shape you want. You now need to modify the transform > to output an image inside of this shape: > > *from* *skimage.transform* *import* warp > *# This in-plane offset is the only necessary transformation for the middle > image*offset = SimilarityTransform(translation=-corner_min) > > shifted_transform = (my_tf + offset).inversepano0_warped = warp(image, > shifted_transform, order=3, > output_shape=output_shape, cval=-1) > > > Let us know how that goes! > > Stéfan > > > _______________________________________________ > scikit-image mailing list > scikit-image@python.org > https://mail.python.org/mailman/listinfo/scikit-image > > > > > _______________________________________________ > scikit-image mailing list > scikit-image@python.org > https://mail.python.org/mailman/listinfo/scikit-image > >
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