Suraj Pattar saratrajput

## launch_executable_from_anywhere_ubuntu.md

      
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                saratrajput
                / launch_executable_from_anywhere_ubuntu.md
            
            
              Created
              March 3, 2023 05:25
            
              
                Create executable for AppImage or executable to launch from any directory in Ubuntu
              
          
Move the directory or AppImage to a desired location.

sudo mkdir -p /<example_dir>/
sudo mv <my_executable_dir> /<example_dir>/


Create a symlink in a directory which is in the PATH.

sudo ln -s /<example_dir>/<my_example_dir>/<executable> /usr/local/bin/<executable_name>


## check_gpu_availability.py
import subprocess

def check_gpu_availability(threshold=50):
    # Run the nvidia-smi command to get GPU information
    cmd = "nvidia-smi --query-gpu=index,memory.used,memory.total --format=csv,noheader"
    gpu_info = subprocess.check_output(cmd, shell=True).decode().strip().split("\n")

    # Parse the GPU information into a list of dictionaries
    gpu_list = []
    for gpu in gpu_info:

## opencv_code_snippets.py
import cv2
import numpy as np
import matplotlib.pyplot as plt


# To add a colored mask over a image
def add_colored_mask(image, mask):
    color = (0, 0, 255)  # Red.
    image_colored = np.zeros(image.shape, image.dtype)
    image_colored[:,:] = color

## automatic_print_removal_instruction.md

      
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                saratrajput
                / automatic_print_removal_instruction.md
            
            
              Created
              August 4, 2022 23:45
            
              
                Automatic Print Removal GCODES
              
          
    Automatic Print Removal GCODES

These instructions are to remove the printed at the end of the print. The printed model is assumed to be placed at the center of the platform.
Printer: Anycubic Mega.

Original End Code

M104 S0 ; turn off extruder
M140 S0 ; turn off bed
M84 ; disable motors
M107


## instructions_to_activate_opencv_cpp_intellisense.md

      
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                saratrajput
                / instructions_to_activate_opencv_cpp_intellisense.md
            
            
              Created
              August 2, 2022 07:17
            
              
                OpenCV C++ Intellisense for VSCode on Ubuntu 20
              
          
First locate OpenCV files on your machine.


If locate is not installed, install it with: sudo apt install mlocate.
You might get results like:

locate opencv.hpp                                                                                                                                                                             (py37_test) 
/usr/include/boost/compute/interop/opencv.hpp
/usr/include/opencv4/opencv2/opencv.hpp


In VSCode, Press Ctrl+Shift+P.


## access_private_variables_in_python.py
# Single underscore
class Example():
    _private_variable = 10
    def __init__(self):
        self._private_variable = 20

example_object = Example()
print(example_object._private_variable)

# Double underscores

## python_template.py
"""
Module Docstring.

author:name
date:date
"""


import argparse
import logging

## mujoco_py_install_instructions.md

      
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                saratrajput
                / mujoco_py_install_instructions.md
            
            
              Created
              January 27, 2022 08:26
            
              
                Mujoco and Mujoco-py Installation Instructions
              
          
    Mujoco and Mujoco-py Installation Instructions

The steps are taken from this video and document with some small changes.
Steps


Install Anaconda. Download it from this link.

cd Downloads/
sudo chmod +x Anaconda3-2021.11-Linux-x86_64.sh
./Anaconda3-2021.11-Linux-x86_64.sh
	import subprocess

	def check_gpu_availability(threshold=50):
	# Run the nvidia-smi command to get GPU information
	cmd = "nvidia-smi --query-gpu=index,memory.used,memory.total --format=csv,noheader"
	gpu_info = subprocess.check_output(cmd, shell=True).decode().strip().split("\n")

	# Parse the GPU information into a list of dictionaries
	gpu_list = []
	for gpu in gpu_info:
	import cv2
	import numpy as np
	import matplotlib.pyplot as plt


	# To add a colored mask over a image
	def add_colored_mask(image, mask):
	color = (0, 0, 255) # Red.
	image_colored = np.zeros(image.shape, image.dtype)
	image_colored[:,:] = color
	# Single underscore
	class Example():
	_private_variable = 10
	def __init__(self):
	self._private_variable = 20

	example_object = Example()
	print(example_object._private_variable)

	# Double underscores
	"""
	Module Docstring.

	author:name
	date:date
	"""


	import argparse
	import logging