BloodAxe

/**
 * @brief     Image enchancement and Hough transform example
 * @author    Eugene Khvedchenya <ekhvedchenya@gmail.com>
 * @copyright computer-vision-talks.com/articles/how-to-detect-circles-in-noisy-image/
 */



#include <opencv2/opencv.hpp>

erogol

layers {
  name: "conv1A"
  type: CONVOLUTION
  bottom: "data"
  top: "conv1A"
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  convolution_param {

alesee

from torch import *
import torch.nn.functional as F
import torch.nn as nn

class RNNModel(nn.Module):
    """
    Neural Network Module with an embedding layer, a recurent module and an output linear layer
    
    Arguments:
        rnn_type(str) -- type of rnn module to use options are ['LSTM', 'GRU', 'RNN_TANH', 'RNN_RELU']

noirmist

import functools

def my_collate(batch, use_shared_memory=False):
    r"""Puts each data field into a tensor with outer dimension batch size"""

    error_msg = "batch must contain tensors, numbers, dicts or lists; found {}"
    elem_type = type(batch[0])
    if isinstance(batch[0], torch.Tensor):
        out = None
        if use_shared_memory:

rkaplan

import functools

def my_collate(batch, use_shared_memory=False):
    r"""Puts each data field into a tensor with outer dimension batch size"""

    error_msg = "batch must contain tensors, numbers, dicts or lists; found {}"
    elem_type = type(batch[0])
    if isinstance(batch[0], torch.Tensor):
        out = None
        if use_shared_memory:

Musinux

#!/bin/bash
# WARNING ! THIS WAS WRITTEN A LONG TIME AGO (2018), IT MAY NOT BE RELEVANT ANYMORE
sudo apt-get install vnc4server ubuntu-desktop
sudo apt-get install gnome-panel gnome-settings-daemon metacity nautilus gnome-terminal

stonehippo

Getting X11 GUI applications to work on OS X with Docker

$ brew install socat
$ brew cask install xquartz <--- assuming you don't already have XQuartz installed some other way
$ open -a XQuartz <--- start an XQuartz session

$ socat TCP-LISTEN:6000,reuseaddr,fork UNIX-CLIENT:\"$DISPLAY\"

Sitin

function link_fbx_sdk() {
	INTERPRETER=$1
	SITE_PACKAGES=`$INTERPRETER -c "from distutils.sysconfig import get_python_lib; print(get_python_lib())"`
	PYTHON_LIB="${2}"

	echo "[Installing] '$PYTHON_LIB' to '$SITE_PACKAGES'"

	pushd $SITE_PACKAGES
	for file in "${PYTHON_LIB}"/*
	do

graphific

VGG_ILSVRC_19_layers_train_val.prototxt
name: "VGG_ILSVRC_19_layers"
layers {
  name: "data"
  type: DATA
  include {
    phase: TRAIN
  }
 transform_param {
    crop_size: 224

tonmoay

import cv2
from matplotlib import pyplot as plt
import numpy as np


cap = cv2.VideoCapture(0) #Webcam Capture

while(True):

	ret, frame = cap.read()