priteshgohil

#!/bin/bash

#title           :images2pdf.sh
#description     :Best image compression ever.
#author		 :Pritesh Gohil
#date            :08 Jan 2021
#version         :0.1    
#usage		 :bash images2pdf.sh -i ../Desktop/img_dir/
#notes           :Install ImageMagick and ghostscript packages.
#bash_version    :5.0.16(1)-release

priteshgohil

#include <opencv2/opencv.hpp>
#include <iostream>

int main(int, char**) {
    // open the first webcam plugged in the computer
    cv::VideoCapture camera(0); // in linux check $ ls /dev/video0
    if (!camera.isOpened()) {
        std::cerr << "ERROR: Could not open camera" << std::endl;
        return 1;
    }

priteshgohil

#!/usr/bin/env python
# -*- coding: utf-8 -*-

# Copyright 2016 Massachusetts Institute of Technology
# Tutorial : http://wiki.ros.org/rosbag/Code%20API#Python_API
"""
    Extract images from a rosbag.
    How to use: In terminal, cd DIRECTORY_OF_THIS_FILE and then type following
                python bag_to_images.py --bag_file camera_odom_compressed.bag --output_dir output/ --image_topic '/camera/image_raw'
                python bag_to_images.py --bag_file my_rosbag_file.bag --output_dir output/ --image_topic '/eGolf/front_cam/image_raw'

priteshgohil

#!/usr/bin/env python
"""
    Author: Pritesh Gohil
    
    Import or run this script to extract frames from a single video or
    video directory using OpenCV
    Requirement: numpy, cv2, tqdm

    How to use:
    Single Video

priteshgohil

Short cmd	Full cmd	Description
a	args	Print all arguments with its value in current function
b	break	Add breapoint at specific line or function
c	continue	Continue execution of program until next breakpoint
cl	clear	Clear all the soft breakpoints
l	list	Print next 11 line of code aroung the current line
l .	list .	Go back to the current debug point

priteshgohil

import cv2
import random
import numpy as np

'''
    Draw AABB in given image with labels
    Inputs: img - image file path or cv2 image
          : boxes_list - 2d list or 2d array of BBox (4 columns) with bounding boxes with top-left (x_min, y_min) and bottom right (x_max, y_max) pixel value. PS: maintain order xyxy
          : label list - list(str) or 1-d array having name of the labels. Use cls = [classes[l] for l in list(labels)] # index to str labels
    Return: CV2 image in BGR format

priteshgohil

import time
import statistics
import numpy as np

def mean_normal(list_data):
    """
        Calculate mean of python list normaly
        input: list of int or float
        output: mean value
    """