lukicdarkoo

# Installation:
#
#     pip3 install bpy
#
# Usage:
#
#    python3 decimate.py /path/to/meshes/* --ratio 0.025
#

import bpy

lukicdarkoo

# Converts rotation and translation VRML fields.
# It takes the clipboard content, applies transforms, and pastes the transformed VRML to the clipboard.
#
# Dependencies:
#
#   pip3 install clipboard numpy transforms3d
#   sudo apt install xclip
#
# GNOME SHORTCUT
# In GNOME, you can run the script as a keyboard shortcut.

lukicdarkoo

Server Configuration

Install VirtualGL and TurboVNC

# Install VirtualGL
wget https://nav.dl.sourceforge.net/project/virtualgl/3.1/virtualgl_3.1_amd64.deb
sudo apt install ./virtualgl_3.1_amd64.deb

# Install TurboVNC

lukicdarkoo

all:
	g++ -shared -fPIC MyPlugin.cpp -o myplugin.so
	g++ main.cpp -o main -ldl

lukicdarkoo

import gym
import numpy as np
import torch
import torch.nn
from torch.nn.functional import smooth_l1_loss, relu, softmax


class ActorCriticNet(torch.nn.Module):
    def __init__(self, n_states=4, n_hidden=128, n_actions=2):
        super().__init__()

lukicdarkoo

#include <Python.h>

typedef struct {
  PyObject_HEAD char *arr;
  int len;
} ArrayCuckoo;

static int ArrayCuckoo_init(ArrayCuckoo *self, PyObject *args, PyObject *kwds) {
  self->len = 2;
  self->arr = (char *)malloc(self->len * sizeof(char));

lukicdarkoo

{
    "configurations": [
        {
            "name": "ROS2 Foxy",
            "browse": {
                "databaseFilename": "",
                "limitSymbolsToIncludedHeaders": true
            },
            "includePath": [
                "/home/lukic/webots/include/controller/cpp",

lukicdarkoo

# This script prepares your machine for computer vision challenges (with NVIDIA).
# Tested with Ubuntu 20.04 LTS and NVIDIA GeForce GTX 1070 (Aorus Gaming Box enclosure).
# Reddit post: https://www.reddit.com/r/eGPU/comments/io94qq/linux_aorus_gaming_box_for_robotics_and_computer/
#
# The script does the following:
# * Installs NVIDIA driver
# * Installs NVIDIA CUDA Toolkit (`nvcc`)
# * Installs NVIDIA CUDA Deep Neural Network library (cuDNN)
# * Installs OpenCV with CUDA support (WIP)
# * Installs TensorFlow with CUDA support

lukicdarkoo

#VRML_SIM R2020b utf8
WorldInfo {
  info [
    "The model of the e-puck 2 robot"
  ]
  title "e-puck simulation"
  coordinateSystem "NUE"
}
Viewpoint {
  orientation 0.04913069345659068 0.9922428678493876 0.11419398479121845 3.8679

lukicdarkoo

"""
Converts LabelMe annotations to annotations compatible with YOLO.
The script does the following:
- cleans (!) the output directory and prepare it for training,
- splits the dataset on validation and training,
- converts all LabelMe annoations (*.json) to YOLO annoations (*.txt) and
- creates YOLO metadata (`.data`, `.names`, `train.txt` and `valid.txt`)
"""

import os