WIStudent

Compiling DeepMatching's GPU version on Ubuntu 16.10

DeepMatching is an algorithm that finds corresponding points in two images. Its GPU implementation was written for Fedora 21, which makes things a bit more difficult if you want to run it on an Ubuntu system. This document contains step-by-step instructions on how to get DeepMatching running on Ubuntu 16.10. I only tested it with Ubuntu 16.10, just let me know if it works with previous versions too.

To compile the GPU version you first need to compile the Caffe version that is included that comes with the DeepMatching files. Newer versions of Caffe won't work because Caffe changed the structure of its header files.

Compiling Caffe

Before compiling Caffe we need to make sure all its dependencies are installed. From the installation guide for Ubuntu 16.04/15.10:

sudo apt-get install build-essential cmake git pkg-config

alper111

import torch
import torchvision

class VGGPerceptualLoss(torch.nn.Module):
    def __init__(self, resize=True):
        super(VGGPerceptualLoss, self).__init__()
        blocks = []
        blocks.append(torchvision.models.vgg16(pretrained=True).features[:4].eval())
        blocks.append(torchvision.models.vgg16(pretrained=True).features[4:9].eval())
        blocks.append(torchvision.models.vgg16(pretrained=True).features[9:16].eval())

CasiaFan

import subprocess as sp
import cv2 
import numpy as np
from PIL import Image
import tensorflow as tf

ffmpeg_cmd_1 = ["./ffmpeg",  "-y",  
              "-hwaccel",  "nvdec",
              "-c:v",  "h264_cuvid",
              "-vsync", "0", 

karpathy

"""
stable diffusion dreaming
creates hypnotic moving videos by smoothly walking randomly through the sample space

example way to run this script:

$ python stablediffusionwalk.py --prompt "blueberry spaghetti" --name blueberry

to stitch together the images, e.g.:
$ ffmpeg -r 10 -f image2 -s 512x512 -i blueberry/frame%06d.jpg -vcodec libx264 -crf 10 -pix_fmt yuv420p blueberry.mp4