jedypod

kiding

import UIKit
import MobileCoreServices.UTCoreTypes

if #available(iOS 14.1, *) {
    let input = Bundle.main.url(forResource: "IMG_0037", withExtension: "HEIC")!
    let output = FileManager().temporaryDirectory.appendingPathComponent("IMG_0037.GAIN_MAP.BMP")
    let source = CGImageSourceCreateWithURL(input as CFURL, nil)!

    // urn:com:apple:photo:2020:aux:hdrgainmap
    let dataInfo = CGImageSourceCopyAuxiliaryDataInfoAtIndex(source, 0, kCGImageAuxiliaryDataTypeHDRGainMap)! as Dictionary

MrLixm

import logging

import colour
import numpy as np
from oiio import OpenImageIO as oiio

# ---------------------------------------------------------


def lerp(x, y, a):

zachlewis

import PyOpenColorIO as ocio
import numpy as np
import colour as colour
from six import string_types

__version__ = "2020.11.08.0"



OUTPUT = "/tmp/test_config.ocio2"

sobotka

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

import numpy
import math


# Return value as scalar or array. Shamelessly borrowed from
# Colour-science.org.
def as_numeric(obj, as_type=numpy.float64):

alexjc

Specific Papers

• https://arxiv.org/abs/1505.07376

  Texture Synthesis Using Convolutional Neural Networks
• https://arxiv.org/abs/1508.06576

  A Neural Algorithm of Artistic Style
• https://arxiv.org/abs/1603.03417

  Texture Networks: Feed-forward Synthesis of Textures and Stylized Images
• https://arxiv.org/abs/1701.02096

  Improved Texture Networks: Maximizing Quality and Diversity in Feed-forward Texture Synthesis

sobotka

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

import PyOpenColorIO
import numpy
import colour
from colour import (
    io,
    adaptation,
    models

AmericanEnglish

How to compile TensorFlow 2.0 from source in an HPC environment that uses EasyBuild for CentOS7

Some background about why another Gist on compiling tensorflow without root

If you're like me and you don't have root access to a HPC system and your system adminstrators use EasyBuild combined with Lmod you are going to be in for a bad time. Our CentOS7 did not ship out of the box capable of compiling tensorflow 2.0 from source with no problems. I scoured several closed and recently opened issues to write a script that enables the creation of a fully functional .whl for tensorflow 2.0. Note that on our cluster we have only two different sets of GPUs. One set has compute capability 7.0 (V100) and compute capability 3.5 (K20m). So many issues came up

1. because Bazel can't handle symlinks for gcc leading to errors like

tvst

"""Hack to add per-session state to Streamlit.

Usage
-----

>>> import SessionState
>>>
>>> session_state = SessionState.get(user_name='', favorite_color='black')
>>> session_state.user_name
''

zalo

import numpy as np
import cv2
import face_alignment

# Initialize the chip resolution
chipSize = 300
chipCorners = np.float32([[0,0],
                          [chipSize,0],
                          [0,chipSize],
                          [chipSize,chipSize]])