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View GitHub Profile
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;
extern crate rand;
use std::collections::HashMap;
use std::cell::RefCell;
use std::collections::*;
pub struct Aliases {
pub idx_to_name:HashMap< i16,String>,
pub name_to_idx:HashMap< String,i16>
pub struct Polynome {
View is_this_crapmake_log?
CMake Deprecation Warning at CMakeLists.txt:81 (cmake_policy):
The OLD behavior for policy CMP0020 will be removed from a future version
of CMake.
The cmake-policies(7) manual explains that the OLD behaviors of all
policies are deprecated and that a policy should be set to OLD only under
specific short-term circumstances. Projects should be ported to the NEW
behavior and not rely on setting a policy to OLD.
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