mythrex

{
  "embeddings": [
    {
      "tensorName": "p_companion_embeddings",
      "tensorShape": [
        8424, 
        360
      ],
      "tensorPath": "https://raw.githubusercontent.com/mythrex/p_companion_embedding/main/embeddings_l3_small.tsv",
      "metadataPath": "https://raw.githubusercontent.com/mythrex/p_companion_embedding/main/embeddings_l3_meta_data.txt"

mythrex

def run_bash(cmd_to_run:str, skip_flag:int=1, print_output:int=0):
    if skip_flag == 1:
        start = time()
        print(cmd_to_run)
        p = Popen(cmd_to_run, shell=True, stdout=PIPE)
        p.wait()
        if print_output == 1:
            print(p.communicate()[0])
        print('Time taken: {} seconds.\n'.format(round(time() - start)))
    else:

mythrex

import requests
from bs4 import BeautifulSoup as bs
from tqdm.auto import tqdm
from joblib import Parallel, delayed

def get_title(url):
    r = requests.get(url)
    soup = bs(r.content, 'lxml')
    return soup.title.string

mythrex

for i in **/*.mp4; do
  sum=$(echo -n "$i" | md5sum)
  mv -- "$i" "${sum%% *}.${i##*.}"
done

mythrex

ffmpeg -ss 00:00:30 -i orginalfile -t 00:00:05 -vcodec copy -acodec copy newfile

mythrex

wget --no-check-certificate 'https://docs.google.com/uc?export=download&id=FILEID' -O FILENAME

wget --load-cookies /tmp/cookies.txt "https://docs.google.com/uc?export=download&confirm=$(wget --quiet --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=FILEID' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\1\n/p')&id=FILEID" -O "VOCtrainval_06-Nov-2007.tar" && rm -rf /tmp/cookies.txt

mythrex

import argparse
from PIL import Image
import os

parser = argparse.ArgumentParser(description='Resize Image')

parser.add_argument('-path',
                    '--path',
                    help='Enter Image Path',
                    required=True)

mythrex

{
  "embeddings": [
    {
      "tensorName": "Deep Dream over text.",
      "tensorShape": [
        78,
        100
      ],
      "tensorPath": "https://raw.githubusercontent.com/mythrex/deep_dream_textual_data/master/embeddings/embeddings_neg.tsv",
      "metadataPath": "https://raw.githubusercontent.com/mythrex/deep_dream_textual_data/master/embeddings/vocab_neg'.tsv"

mythrex

def dream(input, model, iterations, lr):
    """ Updates the image to maximize outputs for n iterations """
    model.eval()
    out, orig_embeddings, hidden = model(input)
    model.train()
    losses = []
    embeddings_steps = []
    embeddings = torch.autograd.Variable(
        orig_embeddings.mean(1), requires_grad=True)
    embeddings_steps.append(embeddings.clone())

mythrex

{
  "embeddings": [
    {
      "tensorName": "Deep Dream over text.",
      "tensorShape": [
        78,
        100
      ],
      "tensorPath": "https://raw.githubusercontent.com/mythrex/deep_dream_textual_data/master/embeddings/embeddings_pos.tsv",
      "metadataPath": "https://raw.githubusercontent.com/mythrex/deep_dream_textual_data/master/embeddings/vocab_pos.tsv"