depth

From one angle my shrubs look like this: From the other, they look like this: My theory is that when looking at the shrubs from the first angle, all the blocks behind the shrub have already been drawn, so when it comes to draw the shrub, it just draws them overtop. From the other angle, however, it's basically trying to draw the shrub first, and then when it goes to draw the block behind the shrub, it checks the depth buffer and sees that there's something already blocking the view of the block, so it doesn't render it, causing the navy blue squares (my clear color). I really have no idea how

There has been previous questions ( here , here and here ) related to my question, however my question has a different aspect to it, which I have not seen in any of the previously asked questions. I have acquired a dataset for my research using Kinect Depth sensor. This dataset is in the format of .png images for both depth and rgb stream at a specific instant. To give you more idea below are the frames: EDIT: I am adding the edge detection output here. Sobel Edge detection output for: RGB Image Depth Image Now what I am trying to do is align these two frames to give me a combined RGBZ image.

①题目 给定一个二叉树，找出其最小深度。 最小深度是从根节点到最近叶子节点的最短路径上的节点数量。 说明: 叶子节点是指没有子节点的节点。 示例: 给定二叉树 [3,9,20,null,null,15,7], 返回它的最小深度 2. ②思路 使用深度优先搜索 ③代码 1 class Solution { 2 public int minDepth(TreeNode root) { 3 if (root == null) { 4 return 0; 5 } 6 if ((root.left == null) && (root.right == null)) { 7 return 1; //当“当前结点”为叶子结点时，返回1,退出本次递归，并且跳过了17行min_depth的自加。 8 } 9 10 int min_depth = Integer.MAX_VALUE; //因为要求最小深度，所以一开始把它设置为最大的int整数，这与530题题解的第三行异曲同工，也与783的低4行类似。 11 if (root.left != null) { 12 min_depth = Math.min(minDepth(root.left), min_depth); 13 } 14 if (root.right != null) { 15 min_depth = Math.min(minDepth

Supposing we have this dict: d = {'a':1, 'b': {'c':{}}} What would be the most straightforward way of knowing the nesting depth of it? You'll have to traverse the dictionary. You could do so with a queue; the following should be safe from circular references: from collections import deque def depth(d): queue = deque([(id(d), d, 1)]) memo = set() while queue: id_, o, level = queue.popleft() if id_ in memo: continue memo.add(id_) if isinstance(o, dict): queue += ((id(v), v, level + 1) for v in o.values()) return level Note that because we visit all dictionary values in breath-first order, the

I am currently trying to generate 3D points given stereo image pair in OpenCV. This has been done quite a bit as far as I can search. I know the extrinsic parameters of the stereo setup which I'm going to assume is in frontal parallel configuration (really, it isn't that bad!). I know the focal length, baseline, and I'm going to assume the principal point as the center of the image (I know, I know...). I calculate a psuedo-decent disparity map using StereoSGBM and hand coded the Q matrix following O'Reilly's Learning OpenCV book which specifies: Q = [ 1 0 0 -c_x 0 1 0 -c_y 0 0 0 f 0 0 -1/T_x

其实我写的有点害怕，因为我不知道我做的对不对，电脑的GPU不行，只跑出了两个epoch的结果就跑不动了，我也不知道是不是程序真的有问题，嗯，我就是一个傻狗屌丝女。先将inception_v3原来的模型放进来用来获取logits。 from __future__ import absolute_import from __future__ import division from __future__ import print_function import tensorflow as tf from VGG16 import inception_utils slim = tf.contrib.slim trunc_normal = lambda stddev: tf.truncated_normal_initializer(0.0, stddev) def inception_v3_base(inputs, final_endpoint='Mixed_7c', min_depth=16, depth_multiplier=1.0, scope=None): end_points = {} if depth_multiplier <= 0: raise ValueError('depth_multiplier is not greater than zero.') depth =