def run_blend(black_image, white_image, mask): """ This function administrates the blending of the two images according to mask. Assume all images are float dtype, and return a float dtype. """ # Automatically figure out the size min_size = min(black_image.shape) depth = int(math.floor(math.log( min_size, 2))) - 4 # at least 16x16 at the highest level. gauss_pyr_mask = assignment6.gaussPyramid(mask, depth) gauss_pyr_black = assignment6.gaussPyramid(black_image, depth) gauss_pyr_white = assignment6.gaussPyramid(white_image, depth) lapl_pyr_black = assignment6.laplPyramid(gauss_pyr_black) lapl_pyr_white = assignment6.laplPyramid(gauss_pyr_white) outpyr = assignment6.blend(lapl_pyr_white, lapl_pyr_black, gauss_pyr_mask) outimg = assignment6.collapse(outpyr) outimg[ outimg < 0] = 0 # blending sometimes results in slightly out of bound numbers. outimg[outimg > 255] = 255 outimg = outimg.astype(np.uint8) return lapl_pyr_black, lapl_pyr_white, gauss_pyr_black, gauss_pyr_white, \ gauss_pyr_mask, outpyr, outimg
def run_blend(black_image, white_image, mask): """ This function administrates the blending of the two images according to mask. Assume all images are float dtype, and return a float dtype. """ # Automatically figure out the size min_size = min(black_image.shape) depth = int(math.floor(math.log(min_size, 2))) - 4 # at least 16x16 at the highest level. gauss_pyr_mask = assignment6.gaussPyramid(mask, depth) gauss_pyr_black = assignment6.gaussPyramid(black_image, depth) gauss_pyr_white = assignment6.gaussPyramid(white_image, depth) lapl_pyr_black = assignment6.laplPyramid(gauss_pyr_black) lapl_pyr_white = assignment6.laplPyramid(gauss_pyr_white) outpyr = assignment6.blend(lapl_pyr_white, lapl_pyr_black, gauss_pyr_mask) outimg = assignment6.collapse(outpyr) outimg[outimg < 0] = 0 # blending sometimes results in slightly out of bound numbers. outimg[outimg > 255] = 255 outimg = outimg.astype(np.uint8) return lapl_pyr_black, lapl_pyr_white, gauss_pyr_black, gauss_pyr_white, \ gauss_pyr_mask, outpyr, outimg
def run_blend(black_image, white_image, mask): """ This function administrates the blending of the two images according to mask. Assume all images are float dtype, and return a float dtype. """ # Automatically figure out the size min_size = min(black_image.shape) depth = int(math.floor(math.log(min_size, 2))) - 4 # at least 16x16 at the highest level gauss_pyr_mask = a6.gaussPyramid(mask, depth) gauss_pyr_black = a6.gaussPyramid(black_image, depth) gauss_pyr_white = a6.gaussPyramid(white_image, depth) lapl_pyr_black = a6.laplPyramid(gauss_pyr_black) lapl_pyr_white = a6.laplPyramid(gauss_pyr_white) outpyr = a6.blend(lapl_pyr_white, lapl_pyr_black, gauss_pyr_mask) img = a6.collapse(outpyr) return (gauss_pyr_black, gauss_pyr_white, gauss_pyr_mask, lapl_pyr_black, lapl_pyr_white, outpyr, [img])
def test_blend_collapse(): """ This script will perform a unit test on your blend and collapse functions and output any errors for debugging. """ lapl_pyr11 = [ np.array([[0., 0., 0., 0.], [0., 0., 0., 0.], [0., 0., 0., 0.]]), np.array([[0., 0.], [0., 0.]]) ] lapl_pyr12 = [ np.array([[149.77, 122.46, 121.66, 178.69], [138.08, 107.74, 106.84, 170.21], [149.77, 122.46, 121.66, 178.69]]), np.array([[124.95, 169.58], [124.95, 169.57]]) ] lapl_pyr21 = [ np.array([[149., 118.4, 99.2, 94.3, 99.2, 118.4, 149.], [137.2, 103.3, 81.9, 76.5, 81.9, 103.3, 137.2], [148.1, 117.4, 97.9, 93.1, 97.9, 117.4, 148.1], [-63.1, -81.3, -92.8, -95.6, -92.8, -81.3, -63.1], [-18.5, -23.8, -27.2, -28., -27.2, -23.8, -18.5]]), np.array([[70.4, 107.1, 104.5, 82.3], [76.7, 115.4, 113.1, 87.3], [-23.3, -29.4, -31., -16.3]]), np.array([[67.7, 100.3], [34., 50.4]]) ] lapl_pyr22 = [ np.array([[-5., -25.2, -56.4, 149.8, 110.3, 116.2, 144.8], [-6.5, -32.5, -72.6, 119.5, 68.6, 76.2, 113.], [-7.2, -36., -80.3, 105.2, 48.9, 57.2, 98.], [-6.5, -32.5, -72.6, 119.5, 68.6, 76.2, 113.], [-5., -25.2, -56.4, 149.8, 110.3, 116.2, 144.8]]), np.array([[-20.9, 4.8, 102.6, 84.1], [-23.2, 22.3, 167.9, 133.1], [-20.9, 4.8, 102.6, 84.1]]), np.array([[17.6, 90.8], [17.6, 90.8]]) ] mask_pyr1 = [ np.array([[0., 0., 1., 1.], [0., 0., 1., 1.], [0., 0., 1., 1.]]), np.array([[0.03, 0.46], [0.03, 0.46]]) ] mask_pyr2 = [ np.array([[0., 0., 0., 0., 1., 1., 1.], [0., 0., 0., 0., 1., 1., 1.], [0., 0., 0., 0., 1., 1., 1.], [0., 0., 0., 0., 1., 1., 1.], [0., 0., 0., 0., 1., 1., 1.]]), np.array([[0., 0., 0.5, 0.5], [0., 0., 0.7, 0.7], [0., 0., 0.5, 0.5]]), np.array([[0., 0.3], [0., 0.3]]) ] out_pyr1 = [ np.array([[149.77, 122.46, 0., 0.], [138.08, 107.74, 0., 0.], [149.77, 122.46, 0., 0.]]), np.array([[120.58, 92.42], [120.58, 92.42]]) ] out_pyr2 = [ np.array([[-5., -25.2, -56.4, 149.8, 99.2, 118.4, 149.], [-6.5, -32.5, -72.6, 119.5, 81.9, 103.3, 137.2], [-7.2, -36., -80.3, 105.2, 97.9, 117.4, 148.1], [-6.5, -32.5, -72.6, 119.5, -92.8, -81.3, -63.1], [-5., -25.2, -56.4, 149.8, -27.2, -23.8, -18.5]]), np.array([[-20.9, 4.8, 103.5, 83.2], [-23.2, 22.3, 129.5, 101.], [-20.9, 4.8, 35.8, 33.9]]), np.array([[17.6, 93.6], [17.6, 78.7]]) ] outimg1 = np.array([[244.91, 218.31, 77.39, 41.59], [243.79, 214.24, 85.99, 46.21], [244.91, 218.31, 77.39, 41.59]]) outimg2 = np.array([[0.1, 0.1, -0.1, 253.7, 241.3, 254., 256.], [-0.3, -0.5, -2.7, 244.4, 250.3, 263.3, 263.2], [-0.6, -1.4, -6., 233.4, 267.8, 278.2, 274.6], [-0.9, -2.1, -8.7, 224.1, 42.2, 46.1, 37.3], [-1., -2.4, -9.6, 221.2, 61.5, 59.5, 47.5]]) if __name__ == "__main__": print 'Evaluating blend.' for left_pyr, right_pyr, mask_pyr, out_pyr in ((lapl_pyr11, lapl_pyr12, mask_pyr1, out_pyr1), (lapl_pyr21, lapl_pyr22, mask_pyr2, out_pyr2)): usr_out = assignment6.blend(left_pyr, right_pyr, mask_pyr) if not type(usr_out) == type(out_pyr): if __name__ == "__main__": print "Error- output layer has type {}. Expected type is {}.".format( type(usr_out), type(out_pyr)) return False if not len(usr_out) == len(out_pyr): if __name__ == "__main__": print "Error- blend out has len {}. Expected len is {}.".format( len(usr_out), len(out_pyr)) return False for usr_layer, true_layer, left_layer, right_layer, mask_layer in zip( usr_out, out_pyr, left_pyr, right_pyr, mask_pyr): if not type(usr_layer) == type(true_layer): if __name__ == "__main__": print "Error- blend out has type {}. Expected type is {}.".format( type(usr_layer), type(true_layer)) return False if not usr_layer.shape == true_layer.shape: if __name__ == "__main__": print "Error- blend output layer has shape {}. Expected shape is {}.".format( usr_layer.shape, true_layer.shape) return False if not usr_layer.dtype == true_layer.dtype: if __name__ == "__main__": print "Error- blend output layer has dtype {}. Expected dtype is {}.".format( usr_layer.dtype, true_layer.dtype) return False if not np.all(np.abs(usr_layer - true_layer) < 1): if __name__ == "__main__": print "Error- blend output layer has value:\n{}\nExpected value:\n{}\nInput left:\n{}\nInput right:\n{}\nInput mask:\n{}".format( usr_layer, true_layer, left_layer, right_layer, mask_layer) return False if __name__ == "__main__": print "blend passed.\n" print "Evaluating collapse." for pyr, img in ((out_pyr1, outimg1), (out_pyr2, outimg2)): if __name__ == "__main__": print "input:\n{}".format(pyr) usr_out = assignment6.collapse(pyr) if not type(usr_out) == type(img): if __name__ == "__main__": print "Error- collapse out has type {}. Expected type is {}.".format( type(usr_out), type(img)) return False if not usr_out.shape == img.shape: if __name__ == "__main__": print "Error- collapse out has shape {}. Expected shape is {}.".format( usr_out.shape, img.shape) return False if not usr_out.dtype == img.dtype: if __name__ == "__main__": print "Error- collapse out has dtype {}. Expected dtype is {}.".format( usr_out.dtype, img.dtype) return False if not np.all(np.abs(usr_out - img) < 1): if __name__ == "__main__": print "Error- collapse out has value:\n{}\nExpected value:\n{}".format( usr_out, img) return False if __name__ == "__main__": print "collapse passed." if __name__ == "__main__": print "All unit tests successful." return True
def test_blend_collapse(): """ This script will perform a unit test on your blend and collapse functions and output any errors for debugging. """ lapl_pyr11 =[np.array([[ 0., 0., 0., 0.], [ 0., 0., 0., 0.], [ 0., 0., 0., 0.]]), np.array([[ 0., 0.], [ 0., 0.]])] lapl_pyr12 =[np.array([[ 149.77, 122.46, 121.66, 178.69], [ 138.08, 107.74, 106.84, 170.21], [ 149.77, 122.46, 121.66, 178.69]]), np.array([[ 124.95, 169.58], [ 124.95, 169.57]])] lapl_pyr21 =[np.array([[ 149. , 118.4, 99.2, 94.3, 99.2, 118.4, 149. ], [ 137.2, 103.3, 81.9, 76.5, 81.9, 103.3, 137.2], [ 148.1, 117.4, 97.9, 93.1, 97.9, 117.4, 148.1], [ -63.1, -81.3, -92.8, -95.6, -92.8, -81.3, -63.1], [ -18.5, -23.8, -27.2, -28. , -27.2, -23.8, -18.5]]), np.array([[ 70.4, 107.1, 104.5, 82.3], [ 76.7, 115.4, 113.1, 87.3], [ -23.3, -29.4, -31. , -16.3]]), np.array([[ 67.7, 100.3], [ 34. , 50.4]])] lapl_pyr22 =[np.array([[ -5. , -25.2, -56.4, 149.8, 110.3, 116.2, 144.8], [ -6.5, -32.5, -72.6, 119.5, 68.6, 76.2, 113. ], [ -7.2, -36. , -80.3, 105.2, 48.9, 57.2, 98. ], [ -6.5, -32.5, -72.6, 119.5, 68.6, 76.2, 113. ], [ -5. , -25.2, -56.4, 149.8, 110.3, 116.2, 144.8]]), np.array([[ -20.9, 4.8, 102.6, 84.1], [ -23.2, 22.3, 167.9, 133.1], [ -20.9, 4.8, 102.6, 84.1]]), np.array([[ 17.6, 90.8], [ 17.6, 90.8]])] mask_pyr1 =[np.array([[ 0., 0., 1., 1.], [ 0., 0., 1., 1.], [ 0., 0., 1., 1.]]), np.array([[ 0.03, 0.46], [ 0.03, 0.46]])] mask_pyr2 = [np.array([[ 0., 0., 0., 0., 1., 1., 1.], [ 0., 0., 0., 0., 1., 1., 1.], [ 0., 0., 0., 0., 1., 1., 1.], [ 0., 0., 0., 0., 1., 1., 1.], [ 0., 0., 0., 0., 1., 1., 1.]]), np.array([[ 0. , 0. , 0.5, 0.5], [ 0. , 0. , 0.7, 0.7], [ 0. , 0. , 0.5, 0.5]]), np.array([[ 0. , 0.3], [ 0. , 0.3]])] out_pyr1 =[np.array([[ 149.77, 122.46, 0. , 0. ], [ 138.08, 107.74, 0. , 0. ], [ 149.77, 122.46, 0. , 0. ]]), np.array([[ 120.58, 92.42], [ 120.58, 92.42]])] out_pyr2 = [np.array([[ -5. , -25.2, -56.4, 149.8, 99.2, 118.4, 149. ], [ -6.5, -32.5, -72.6, 119.5, 81.9, 103.3, 137.2], [ -7.2, -36. , -80.3, 105.2, 97.9, 117.4, 148.1], [ -6.5, -32.5, -72.6, 119.5, -92.8, -81.3, -63.1], [ -5. , -25.2, -56.4, 149.8, -27.2, -23.8, -18.5]]), np.array([[ -20.9, 4.8, 103.5, 83.2], [ -23.2, 22.3, 129.5, 101. ], [ -20.9, 4.8, 35.8, 33.9]]), np.array([[ 17.6, 93.6], [ 17.6, 78.7]])] outimg1 = np.array([[ 244.91, 218.31, 77.39, 41.59], [ 243.79, 214.24, 85.99, 46.21], [ 244.91, 218.31, 77.39, 41.59]]) outimg2 = np.array([[ 0.1, 0.1, -0.1, 253.7, 241.3, 254. , 256. ], [ -0.3, -0.5, -2.7, 244.4, 250.3, 263.3, 263.2], [ -0.6, -1.4, -6. , 233.4, 267.8, 278.2, 274.6], [ -0.9, -2.1, -8.7, 224.1, 42.2, 46.1, 37.3], [ -1. , -2.4, -9.6, 221.2, 61.5, 59.5, 47.5]]) if __name__ == "__main__": print 'Evaluating blend.' for left_pyr, right_pyr, mask_pyr, out_pyr in ((lapl_pyr11, lapl_pyr12, mask_pyr1, out_pyr1), (lapl_pyr21, lapl_pyr22, mask_pyr2, out_pyr2)): usr_out = assignment6.blend(left_pyr, right_pyr, mask_pyr) if not type(usr_out) == type(out_pyr): if __name__ == "__main__": print "Error- output layer has type {}. Expected type is {}.".format( type(usr_out), type(out_pyr)) return False if not len(usr_out) == len(out_pyr): if __name__ == "__main__": print "Error- blend out has len {}. Expected len is {}.".format( len(usr_out), len(out_pyr)) return False for usr_layer, true_layer, left_layer, right_layer, mask_layer in zip(usr_out, out_pyr, left_pyr, right_pyr, mask_pyr): if not type(usr_layer) == type(true_layer): if __name__ == "__main__": print "Error- blend out has type {}. Expected type is {}.".format( type(usr_layer), type(true_layer)) return False if not usr_layer.shape == true_layer.shape: if __name__ == "__main__": print "Error- blend output layer has shape {}. Expected shape is {}.".format( usr_layer.shape, true_layer.shape) return False if not usr_layer.dtype == true_layer.dtype: if __name__ == "__main__": print "Error- blend output layer has dtype {}. Expected dtype is {}.".format( usr_layer.dtype, true_layer.dtype) return False if not np.all(np.abs(usr_layer - true_layer) < 1): if __name__ == "__main__": print "Error- blend output layer has value:\n{}\nExpected value:\n{}\nInput left:\n{}\nInput right:\n{}\nInput mask:\n{}".format( usr_layer, true_layer, left_layer, right_layer, mask_layer) return False if __name__ == "__main__": print "blend passed.\n" print "Evaluating collapse." for pyr, img in ((out_pyr1, outimg1),(out_pyr2, outimg2)): if __name__ == "__main__": print "input:\n{}".format(pyr) usr_out = assignment6.collapse(pyr) if not type(usr_out) == type(img): if __name__ == "__main__": print "Error- collapse out has type {}. Expected type is {}.".format( type(usr_out), type(img)) return False if not usr_out.shape == img.shape: if __name__ == "__main__": print "Error- collapse out has shape {}. Expected shape is {}.".format( usr_out.shape, img.shape) return False if not usr_out.dtype == img.dtype: if __name__ == "__main__": print "Error- collapse out has dtype {}. Expected dtype is {}.".format( usr_out.dtype, img.dtype) return False if not np.all(np.abs(usr_out - img) < 1): if __name__ == "__main__": print "Error- collapse out has value:\n{}\nExpected value:\n{}".format( usr_out, img) return False if __name__ == "__main__": print "collapse passed." if __name__ == "__main__": print "All unit tests successful." return True