sdi1982’s gists

sdi1982 / SimpleParallelForLoop

Created April 25, 2021 20:22 — forked from KPB3rd/SimpleParallelForLoop

Simple Parallel For Loop C++

	// Initialize detector vector
	if (targetDetectors.size() == 0)
	{
	for (unsigned iter = 0; iter < inputImages.size(); iter++) targetDetectors.push_back(CalibTargetDetector());
	}

	// Create Output vector
	for (unsigned iter = 0; iter < inputImages.size(); iter++) targetImages.push_back(TypedObject<cv::Mat>(cv::Mat()));

	std::vector<std::thread*> threads(inputImages.size());

sdi1982 / VideoPlayer.html

Created March 30, 2021 11:08 — forked from jaydenseric/VideoPlayer.html

A simple HTML5 video player.

	<figure class="video-player">
	<video preload="none" width="1280" height="720" poster="video.jpg">
	<source src="video.webm" type="video/webm" />
	<source src="video.mp4" type="video/mp4" />
	</video>
	<button class="play-toggle">Toggle play</button>
	<button class="mute-toggle">Toggle mute</button>
	</figure>
	<script>
	// Initialize video player

sdi1982 / client.cpp

Created March 4, 2021 00:13 — forked from mendaparadarshit/client.cpp

Multiple streaming in c++ using opencv; OpenCV video streaming over TCP/IP

	/**
	* OpenCV video streaming over TCP/IP
	* Client: Receives video from server and display it
	* by Steve Tuenkam
	*/

	#include "opencv2/opencv.hpp"
	#include <sys/socket.h>
	#include <arpa/inet.h>
	#include <unistd.h>

sdi1982 / sift.cpp

Created December 28, 2020 17:41 — forked from lxc-xx/sift.cpp

OpenCV's SIFT implementation

	/*M///////////////////////////////////////////////////////////////////////////////////////
	//
	// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
	//
	// By downloading, copying, installing or using the software you agree to this license.
	// If you do not agree to this license, do not download, install,
	// copy or use the software.
	//
	//
	// License Agreement

sdi1982 / accuracy_recall_precision_f1.py

Created November 28, 2020 20:06 — forked from debonx/accuracy_recall_precision_f1.py

Accuracy, Recall, Precision and F1 score with sklearn.

	# To be reminded
	# 1) Classifying a single point can result in a true positive (truth = 1, guess = 1), a true negative (truth = 0, guess = 0), a false positive (truth = 0, guess = 1), or a false negative (truth = 1, guess = 0).
	# 2) Accuracy measures how many classifications your algorithm got correct out of every classification it made.
	# 3) Recall measures the percentage of the relevant items your classifier was able to successfully find.
	# 4) Precision measures the percentage of items your classifier found that were actually relevant.
	# 5) Precision and recall are tied to each other. As one goes up, the other will go down.
	# 6) F1 score is a combination of precision and recall.
	# 7) F1 score will be low if either precision or recall is low.

	from sklearn.metrics import accuracy_score, recall_score, precision_score, f1_score

sdi1982 / Spatial filtering in image processing

Created November 28, 2020 10:28 — forked from agaikwad123/Spatial filtering in image processing

	Clc
	I=imread('cameraman.tif');
	[m n]=size(I);
	a=im2double(I);
	for i=1:m-2
	for j=1:n-2
	v(i,j) = [a(i,j) + a(i,j+1) + a(i,j+2) + a(i+1,j) + a(i+1,j+1) + a(i+1,j+2) + a(i+2,j) + a(i+2,j+1) + a(i+2,j+2)]./9; %smoothing filter

	x(i,j) = [0a(i,j) + 1a(i,j+1) + 0a(i,j+2) + 1a(i+1,j) + -4a(i+1,j+1) + 1a(i+1,j+2) + 0a(i+2,j) + 1a(i+2,j+1) + 0*a(i+2,j+2)]; %high pass filter

sdi1982 / histogram_matching.py

Created November 28, 2020 10:27 — forked from jcjohnson/histogram_matching.py

	import argparse, os
	import numpy as np
	from scipy.misc import imread, imsave


	parser = argparse.ArgumentParser()
	parser.add_argument('--template_dir', required=True) # Low-res images
	parser.add_argument('--source_dir', required=True) # Outputs from CNN
	parser.add_argument('--output_dir', required=True)
	args = parser.parse_args()

sdi1982 / Simple Background Subtraction C++ OpenCV

Created November 6, 2020 01:29 — forked from Benjit87/Simple Background Subtraction C++ OpenCV

	/*
	http://benjithian.sg/2012/12/simple-background-subtraction/
	Simple Background Subtraction. Simple stuff.
	*/
	#include <stdio.h>
	#include <curl/curl.h>
	#include <sstream>
	#include <iostream>
	#include <vector>
	#include <opencv2/opencv.hpp>

sdi1982 / gist:d0b749ebfd511653ab1cee181c389d39

Created October 23, 2020 16:15 — forked from petigura/gist:1927518

Linear Least Squares

	def PLfit(p0,blin,x,data,model,engine=optimize.fmin_powell,err=1):
	"""
	Partial Linear Model Fitting.

	Parameters
	----------
	p0 : Initial parameters
	blin : Boolean array specifying which model parameters are fixed

	"""

sdi1982 / f1_score.py

Created October 23, 2020 16:02 — forked from SuperShinyEyes/f1_score.py

F1 score in PyTorch

	def f1_loss(y_true:torch.Tensor, y_pred:torch.Tensor, is_training=False) -> torch.Tensor:
	'''Calculate F1 score. Can work with gpu tensors

	The original implmentation is written by Michal Haltuf on Kaggle.

	Returns
	-------
	torch.Tensor
	`ndim` == 1. 0 <= val <= 1

Daniel Shin sdi1982