There are ways to deal with this. Some on the matching part to avoid the unskew operation itself like this: OCR and character similarity But you want to unskew so: detect the rotation angle/skew slope Obtain bounding box, then cast vertical scan lines and remember first hit point and last regress line through all of … Read more
I was able to make something very similar.. it works in all modern browsers. HTML – Pretty simple div:nth-child(1) { background: rgb(122, 206, 122); height: 140px; transform: skew(-10deg) rotate(2deg); -webkit-transform: skew(-10deg) rotate(2deg); -moz-transform: skew(-10deg) rotate(2deg); } div:nth-child(1) p { transform: skew(10deg) rotate(-2deg); -webkit-transform: skew(10deg) rotate(-2deg); -moz-transform: skew(10deg) rotate(-2deg); padding: 3% 2%; } div:nth-child(2) { border-bottom: … Read more
There is a Johnson distribution in the SuppDists package. Johnson will give you a distribution that matches either moments or quantiles. Others comments are correct that 4 moments does not a distribution make. But Johnson will certainly try. Here’s an example of fitting a Johnson to some sample data: require(SuppDists) ## make a weird dist … Read more
Yes, it’s skewed, unless your RAND_MAX happens to be a multiple of 10. If you take the numbers from 0 to RAND_MAX, and try to divide them into 10 piles, you really have only three possibilities: RAND_MAX is a multiple of 10, and the piles come out even. RAND_MAX is not a multiple of 10, … Read more
.red.box { background-color: red; transform: perspective( 600px ) rotateY( 45deg ); } Then HTML: <div class=”box red”></div> from http://desandro.github.com/3dtransforms/docs/perspective.html
So, first problem is corner order. They must be in the same order in both vectors. So, if in the first vector your order is:(top-left, bottom-left, bottom-right, top-right) , they MUST be in the same order in the other vector. Second, to have the resulting image contain only the object of interest, you must set … Read more