使用SLIC(Simple Linear Iterative Clustering)算法对图像进行分割,n_segments参数指定了期望的分割数目,compactness参数则控制了颜色接近度和空间接近度的平衡。 使用mark_boundaries函数创建一个叠加了分割边界的图像,并将其存储在变量out中。 使用plt.subplot(121)创建一个子图,标题为"n_segments=60",并显示叠加了分割...
image = np.ascontiguousarray(image * ratio) labels = _slic_cython(image, segments, step, max_iter, spacing, slic_zero) #把过小过小的处理一下 if enforce_connectivity: segment_size = depth * height * width / n_segments min_size = int(min_size_factor * segment_size) max_size = int(...
一.python中的slic函数defslic(image, n_segments=100, compactness=10., max_iter=10, sigma=0, spacing=None, multichannel=True, convert2lab=None, enforce_connectivity=True, min_size_factor=0 python series便利 ci 3D 2d 转载 boyboy 2023-09-20 11:57:46 ...
segments = slic(image_rgb, n_segments=num_segments, compactness=compactness) # 创建一个与图像大小相同的数组,用于可视化超像素分割结果 mask = np.zeros_like(image) # 将每个像素标记为对应的超像素颜色 for segment in np.unique(segments): mask[segments == segment] = np.mean(image[segments == se...
segments= slic(img_as_float(image), n_segments=25, sigma=5)#n_segments分割块数越大越细#show the output of SLICfig = plt.figure('Superpixels') ax= fig.add_subplot(1, 1, 1) ax.imshow(mark_boundaries(img_as_float(cv2.cvtColor(image, cv2.COLOR_BGR2RGB)), segments)) ...
n_segments:int 可选 分割输出图像中的(近似)标签数。 compactness:浮点数,可选 平衡颜色接近度和空间接近度。较高的值赋予空间接近度更多的权重,使超像素形状更加方形/立方体。在 SLICO 模式下,这是初始紧凑性。该参数很大程度上取决于图像对比度和图像中对象的形状。我们建议在对数范围内探索可能的值,例如 0.01...
seg_spaced =slic(img, n_segments=2, sigma=0, spacing=[1,500,1], compactness=1.0, multichannel=False) assert_equal(seg_non_spaced, result_non_spaced) assert_equal(seg_spaced, result_spaced) 开发者ID:andreydung,项目名称:scikit-image,代码行数:15,代码来源:test_slic.py ...
labels = segmentation.slic(img, compactness=30, n_segments=400) # labels 转 graph g = graph.RAG(labels) # 算邻接矩阵adj = adj_matrix(g).todense() img_with_boundaries = segmentation.mark_boundaries(img, labels, color=[1,0,0])
我在同一张图片上使用opencv和skimage的SLIC(Simple Linear Iterative Clustering)超像素算法,但得到了不同的结果,skimage slic的结果更好,如下图所示。第一个是opencv SLIC,第二个是skimage SLIC。我有几个问题希望有人可以帮忙。 为什么opencv有参数“region_size”,而skimage是“n_segments”?
This then forms the basis for a slice-by-slice framework that segments subsequent slices before incorporating them into the training set on the fly. The proposed method was compared with its offline counterpart that is with no retraining, and with two other widely used interactive methods. ...