The steps are taken from this video and document with some small changes.
- 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
""" | |
Module Docstring. | |
author:name | |
date:date | |
""" | |
import argparse | |
import logging |
# Single underscore | |
class Example(): | |
_private_variable = 10 | |
def __init__(self): | |
self._private_variable = 20 | |
example_object = Example() | |
print(example_object._private_variable) | |
# Double underscores |
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
Ctrl+Shift+P
.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 |
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: |
sudo mkdir -p /<example_dir>/
sudo mv <my_executable_dir> /<example_dir>/
sudo ln -s /<example_dir>/<my_example_dir>/<executable> /usr/local/bin/<executable_name>