satojkovic satojkovic

## overall_result.csv

          
            Classes
            Without ensemble
            With ensemble
            Diff

            
              Overall
              46.4
              52.0
              +5.6

## result.csv

          
            Classes
            Without ensemble
            With ensemble
            Diff

            
              tench
              0.5
              13.5
              +13.0

            
              English springer
              43.0
              50.4
              +7.4

            
              cassette player
              39.1
              42.2
              +3.1

            
              chain saw
              22.5
              58.2
              +35.7

            
              church
              20.1
              19.3
              -0.8

            
              French horn
              76.1
              79.3
              +3.2

            
              garbage truck
              91.2
              92.5
              +1.3

            
              gas pump
              11.7
              12.2
              +0.5

            
              golf ball
              72.8
              67.0
              -5.8

## scenic_sam.ipynb

      
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## plates.py
def plates(stack, i, num_used, N, P, K):
    # Brute force: O(K^N)
    if i >= N:
        return -1
    current_total = -1
    for n in range(K + 1):
        if num_used + n > P:
            break
        elif num_used + n == P:
            current_total = max(current_total, sum(stack[i][:n]))

## algorithms_openpose.md

      
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                satojkovic
                / algorithms_openpose.md
            
            
              Created
              March 20, 2019 13:52
                — forked from alesolano/algorithms_openpose.md
            
              
                OpenPose TensorFlow Alogrithms
              
          
    All code is highly based on Ildoo Kim's code (https://github.com/ildoonet/tf-openpose) and derived from the OpenPose Library (https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/LICENSE)

  
## cudnn_version.cpp
#include <cudnn.h>
#include <iostream>

int main(int argc, char** argv) {
    std::cout << "CUDNN_VERSION: " << CUDNN_VERSION << std::endl;
    return 0;
}

## http_ex.go
package main

import (
	"fmt"
	"net/http"
)

type String string

type Struct struct {

## test.py
# http://stackoverflow.com/questions/24685436/efficient-way-to-cluster-colors-using-k-nearest

import numpy as np
import cv2

def nearest(i, j, src, knn, colors):
    sample = np.reshape(src, (-1, 3)).astype(np.float32)
    retval, result, neighbors, dist = knn.find_nearest(sample, 1)
    return colors[result[0, 0]]

## dfs.cpp
#include <cstdio>
#include <string>

int n = 4;
int k = 15;
int a[] = {1, 2, 4, 7};

bool dfs(int i, int sum)
{
  printf("i == %d, sum == %d\n", i, sum);

## cv_view.py
#-*- coding: utf-8 -*-

import cv2
from collections import defaultdict


class ImageFlip(object):
    def __init__(self):
        self._observers = []
Classes	Without ensemble	With ensemble	Diff
tench	0.5	13.5	+13.0
English springer	43.0	50.4	+7.4
cassette player	39.1	42.2	+3.1
chain saw	22.5	58.2	+35.7
church	20.1	19.3	-0.8
French horn	76.1	79.3	+3.2
garbage truck	91.2	92.5	+1.3
gas pump	11.7	12.2	+0.5
golf ball	72.8	67.0	-5.8
	def plates(stack, i, num_used, N, P, K):
	# Brute force: O(K^N)
	if i >= N:
	return -1
	current_total = -1
	for n in range(K + 1):
	if num_used + n > P:
	break
	elif num_used + n == P:
	current_total = max(current_total, sum(stack[i][:n]))
	#include <cudnn.h>
	#include <iostream>

	int main(int argc, char** argv) {
	std::cout << "CUDNN_VERSION: " << CUDNN_VERSION << std::endl;
	return 0;
	}
	package main

	import (
	"fmt"
	"net/http"
	)

	type String string

	type Struct struct {
	# http://stackoverflow.com/questions/24685436/efficient-way-to-cluster-colors-using-k-nearest

	import numpy as np
	import cv2

	def nearest(i, j, src, knn, colors):
	sample = np.reshape(src, (-1, 3)).astype(np.float32)
	retval, result, neighbors, dist = knn.find_nearest(sample, 1)
	return colors[result[0, 0]]
	#include <cstdio>
	#include <string>

	int n = 4;
	int k = 15;
	int a[] = {1, 2, 4, 7};

	bool dfs(int i, int sum)
	{
	printf("i == %d, sum == %d\n", i, sum);
	#-- coding: utf-8 --

	import cv2
	from collections import defaultdict


	class ImageFlip(object):
	def __init__(self):
	self._observers = []