te')); return $arr; } /* 遍历用户所有主题 * @param $uid 用户ID * @param int $page 页数 * @param int $pagesize 每页记录条数 * @param bool $desc 排序方式 TRUE降序 FALSE升序 * @param string $key 返回的数组用那一列的值作为 key * @param array $col 查询哪些列 */ function thread_tid_find_by_uid($uid, $page = 1, $pagesize = 1000, $desc = TRUE, $key = 'tid', $col = array()) { if (empty($uid)) return array(); $orderby = TRUE == $desc ? -1 : 1; $arr = thread_tid__find($cond = array('uid' => $uid), array('tid' => $orderby), $page, $pagesize, $key, $col); return $arr; } // 遍历栏目下tid 支持数组 $fid = array(1,2,3) function thread_tid_find_by_fid($fid, $page = 1, $pagesize = 1000, $desc = TRUE) { if (empty($fid)) return array(); $orderby = TRUE == $desc ? -1 : 1; $arr = thread_tid__find($cond = array('fid' => $fid), array('tid' => $orderby), $page, $pagesize, 'tid', array('tid', 'verify_date')); return $arr; } function thread_tid_delete($tid) { if (empty($tid)) return FALSE; $r = thread_tid__delete(array('tid' => $tid)); return $r; } function thread_tid_count() { $n = thread_tid__count(); return $n; } // 统计用户主题数 大数量下严谨使用非主键统计 function thread_uid_count($uid) { $n = thread_tid__count(array('uid' => $uid)); return $n; } // 统计栏目主题数 大数量下严谨使用非主键统计 function thread_fid_count($fid) { $n = thread_tid__count(array('fid' => $fid)); return $n; } ?>image - Canny detection contours and extract points from edges in Julia - Stack Overflow

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    image - Canny detection contours and extract points from edges in Julia - Stack Overflow

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    I have a such task: in image find for each pore (or blob) perimeter of contour. So, each contour I have to consider polygon (approximation) with some step value (distance between points) (for example min step is 20 um).

    For getting edges I prefer Canny algorithm.

    using Images, ImageMorphology, ImageEdgeDetection, Contour, Clustering, 
PolygonOps, ImageView, ImageSegmentation, TestImages, IndirectArrays, 
LinearAlgebra, FileIO, ImageFeatures
using ImageEdgeDetection: Percentile


# Load image (may be binary or grayscale)
function load_image()
    img = testimage("blobs")
    imgg = Gray.(img);
    return imgg
end


# Apply morphological operations -- detect edges
function preprocess_image(img,scale)
    img = erode(dilate(img))  # Opening to remove noise
    alg = Canny(spatial_scale=scale, high=Percentile(80), low=Percentile(20))
    edges = detect_edges(img, alg)
    return img, edges
end


img = load_image()
img1, edges = preprocess_image(img,0.85)
mosaicview(img1,Float64.(edges); nrow=1)

    My question is: how to get points from every edge (respective each segmented object in image) and approximate using Richard's interpolation, or another polygonal approximation with custom step?

    I am using Julia v 1.10. Contour.jl some functions are deprecated...

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