linrock

""" This simulates converting 24-bit RGB values to YUV, then back to 24-bit RGB.
    Using BT.709 transfer functions:
    https://en.wikipedia.org/wiki/Rec._709

    It demonstrates that converting to 30-bit YUV then back to 24-bit RGB is lossy.
    Using 10 bits per YUV value appears to be lossless.

    Converting RGB (24-bit) -> YUV (64-bit floats per channel, normalized [0-1]) -> RGB (24-bit)
      Found 0 inaccurate conversions out of 16581375 RGB values

hiorws

import numpy as np
import cv2
import sys

cap = cv2.VideoCapture(0)

face_cascade = cv2.CascadeClassifier('<PATH_TO_CASCADES_FOLDER>/haarcascade_frontalface_default.xml')

while(True):
    # Capture frame-by-frame

justanhduc

import neuralnet_pytorch as nnt
import torch as T
from torch_scatter import scatter_add


def pointcloud2voxel_fast(pc: T.Tensor, voxel_size: int, grid_size=1., filter_outlier=True):
    b, n, _ = pc.shape
    half_size = grid_size / 2.
    valid = (pc >= -half_size) & (pc <= half_size)
    valid = T.all(valid, 2)

kaz3w

sudo rm /var/lib/ubuntu-release-upgrader/release-upgrade-available
sudo /usr/lib/ubuntu-release-upgrader/release-upgrade-motd

luncliff

CMake를 왜 쓰는거죠?
좋은 툴은 Visual Studio 뿐입니다. 그 이외에는 전부 사도(邪道)입니다 사도! - 작성자

주의

• 이 문서는 CMake를 주관적으로 서술합니다
• 이 문서를 통해 CMake를 시작하기엔 적합하지 않습니다
  https://cgold.readthedocs.io/en/latest/ 3.1 챕터까지 따라해본 이후 기본사항들을 속성으로 익히는 것을 돕기위한 보조자료로써 작성되었습니다

godber

#!/usr/bin/env python
# -*- coding: utf-8 -*-

'''Generates 3D Histogram of Wallaby image and renders to screen using vispy

Requires:

vispy
scipy
numpy

JonathonReinhart

#!/usr/bin/env python3
from __future__ import print_function
from tempfile import TemporaryFile
from binascii import hexlify

from ctypes import *

class StructHelper(object):
    def __get_value_str(self, name, fmt='{}'):
        val = getattr(self, name)

InnerPeace-Wu

import tensorflow as tf

#aplly exponential decay on learning rate
global_step = tf.Variable(0, trainable=False)
stater_learning_rate = lr #for start
learning_rate = tf.train.exponential_decay(starter_learning_rate, global_step, 
                                           decay_steps, decay_rate, staircase=True)

optimizer = tf.train.AdamOptimizer(learning_rate)

kanhua

This gist demonstrates how to setup a python project that process a numpy array from C language.

To compile the project, run

make all

To test it, run

make test

allieus

네이버 블로그 크롤링

• 파이썬3 에서 동작합니다.
• requests, beautifulsoup4 라이브러리가 필요합니다.

pip install requests beautifulsoup4

AskDjango