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View valgrind-deepstream
==1549== Memcheck, a memory error detector
==1549== Copyright (C) 2002-2017, and GNU GPL'd, by Julian Seward et al.
==1549== Using Valgrind-3.13.0 and LibVEX; rerun with -h for copyright info
==1549== Command: ./deepstream-test3-app file:///home/stiv/lpr/data/mp4-2/mgm15-2.mp4
==1549== Warning: noted but unhandled ioctl 0x30000001 with no size/direction hints.
==1549== This could cause spurious value errors to appear.
==1549== See README_MISSING_SYSCALL_OR_IOCTL for guidance on writing a proper wrapper.
==1549== Warning: noted but unhandled ioctl 0x27 with no size/direction hints.
==1549== This could cause spurious value errors to appear.
stiv-yakovenko / Vagrantfile
Created Aug 15, 2019
Install ubuntu 18.04/xwindows with vagrant
View Vagrantfile
Vagrant.configure(2) do |config|
# Ubuntu 15.10 = "bento/ubuntu-18.04"
config.vm.provider "virtualbox" do |vb|
# Display the VirtualBox GUI when booting the machine
vb.gui = true
# Install xfce and virtualbox additions
smooth = 1.
intersection = tf.reduce_sum(flat_logits * flat_labels)
dice_score = (2 * intersection + smooth) / (
tf.reduce_sum(flat_labels) + tf.reduce_sum(flat_logits) + smooth)
dice_loss = 1 - dice_score
cross_entropy_loss = tf.reduce_mean(
tf.nn.softmax_cross_entropy_with_logits_v2(logits=flat_logits, labels=flat_labels))
loss = dice_loss + cross_entropy_loss
import tensorflow as tf
import numpy as np
from PIL import Image
batch_size = 32
loaded_graph = tf.Graph()
with tf.Session(graph=loaded_graph) as sess:
tf.saved_model.loader.load(sess, [tf.saved_model.tag_constants.TRAINING], "./models/roofs_not_roofs/")
im = np.array("./test_pic/b2_DJI_0145_02_05.png"), np.float32)[None,...]/256
x = loaded_graph.get_tensor_by_name('x:0')
View no_deadlocks.txt
This file has been truncated, but you can view the full file.
Attaching to process ID 20365, please wait...
Debugger attached successfully.
Server compiler detected.
JVM version is 25.181-b13
Deadlock Detection:
No deadlocks found.
Thread 28025: (state = BLOCKED)
* Copyright (c) 2016, Cloudera, Inc. All Rights Reserved.
* Cloudera, Inc. licenses this file to you under the Apache License,
* Version 2.0 (the "License"). You may not use this file except in
* compliance with the License. You may obtain a copy of the License at
* This software is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
View rule110
import numpy as np
import matplotlib.pyplot as plt
import torch
from torch.autograd import Variable
def triangle(x,y,z,v0):
v=(y + y * y + y * y * y - 3. * (1. + x) * y * z + z * (1. + z + z * z)) / 3.
return (v-v0)*(v-v0)
def eval():
View stereo_problem.cpp
#include <string>
#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/highgui/highgui.hpp"
using namespace cv;
using namespace std;
struct View {
View aruco_detect
// aruco_detect.cpp : Defines the entry point for the console application.
#include "aruco.h"
#include <iostream>
#include <opencv2/highgui.hpp>
#include <opencv2/calib3d.hpp>
#include <opencv2/imgproc.hpp>
#include <string>
#include <stdexcept>
View gist:e4448db2596c6ea5152afe6ee586c93e
pub fn sum(&self) -> i16 {
let mut r = 0i16;
for (_, v) in &self.0 {
r += *v as i16;
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