deli4iled

import sys
import numpy as np

import torch
import torch.nn.functional as F
import torch.nn as nn
import torch.optim as optim
import torchvision.transforms as transforms

from torchvision.datasets import MNIST

deli4iled

h1
  each txt in ["Get ready","see something more...","than just design!","This is art...","I have not yet invented ☹"]
    span=txt
svg.bg(viewBox="0 0 512.009 512.009")
  defs
    linearGradient(
    id="gradient"
    x1="0"
    y1="0"
    x2="1"

deli4iled

name: "siameseMVCNN"  
layer {
  name: "inputdata"
  type: "Python"
  top: "data"
  top: "label"
  python_param {
    module: 'MVCNNDataLayer'
    layer: 'MVCNNDataLayer'
    param_str: "{'phase': 'train', 'batch_size': 1, 'view_size': 12,'channel_size': 3, 'data_path': './modelnet40v1'}"

deli4iled

@startuml

namespace cv::structured_light{
GrayCodePattern <-- GrayCodePattern_Impl : heritance
StructuredLightPattern <-- GrayCodePattern : heritance
cv::algorithm <-- StructuredLightPattern: heritance

class StructuredLightPattern {
  'Abstract base class for generating and decoding structured light pattern'
  ..generate..

deli4iled

{
  "faire": {
    "perc": 100,
    "results": [
      {
        "_id": {
          "emoticon": 0,
          "interval": 0
        },
        "coord": [

deli4iled

cv::viz::Mesh load(InputArray pointCloud){
 
  vtkSmartPointer<vtkCloudMatSource> cloud_source = vtkSmartPointer<vtkCloudMatSource>::New();
  cloud_source->SetCloud(pointCloud);
  vtkSmartPointer<vtkPolyData> polydata = cloud_source->GetOutput();

  Mesh mesh;
  vtkSmartPointer<vtkCloudMatSink> sink = vtkSmartPointer<vtkCloudMatSink>::New();
  sink->SetOutput(mesh.cloud, mesh.colors, mesh.normals, mesh.tcoords);
  sink->SetInputConnection(reader->GetOutputPort());