dfaker

import subprocess as sp
import whisper

#replace this with the path to the video.
sourcefile = r'Z:\completeTorrents\Ai Uehara MEGAPACK\SHKD525.FHD\SHKD525.FHD.wmv'

start_time_minutes = 0.0

model = whisper.load_model("small")
slice_size = 30

dfaker

import torch
import modules.scripts as scripts
import gradio as gr
from modules.script_callbacks import on_cfg_denoiser
from modules import processing


class Script(scripts.Script):
    def title(self):

dfaker

import cv2
import os
import numpy as np

import sys

print("""
Pass a folder of images as a prameter:

script.py Z:\\somefolder\\somewhere

dfaker

onUiUpdate(function(){
	gradioApp().querySelectorAll('button img').forEach(function(e){
		if(!e.classList.contains('downsized')){
			if(e.naturalHeight != e.clientHeight || e.naturalWidth != e.clientWidth){
				var canvas = document.createElement("canvas");
				var ar =  e.naturalHeight/e.naturalWidth
				canvas.width = e.clientWidth;
				canvas.height = e.clientHeight*ar;
				var ctx = canvas.getContext("2d");
				ctx.drawImage(e, 0, 0, e.clientWidth, e.clientHeight*ar);

dfaker

import inspect
from modules.processing import Processed, process_images
import gradio as gr
import modules.scripts as scripts
import k_diffusion.sampling
import torch


class Script(scripts.Script):

dfaker

import numpy as np
import torch

def lerp(theta0, theta1, alpha):
    return (1 - alpha) * theta0 + alpha * theta1

def slerp(theta0, theta1, alpha):
    theta0 = theta0
    theta1 = theta1
    # Copy the vectors to reuse them later

dfaker

import cv2
import sys
import os
import subprocess as sp
import numpy as np
import time


baseFolder = os.path.split(__file__)[0]

dfaker

import csv
csvname = 'frames\\coords.csv'

data = []
with open(csvname,'r', newline='') as csvfile:
  reader = csv.DictReader(csvfile)
  for row in reader:
    data.append( row )

dfaker

import sys
import os
import mimetypes
import random

import mpv
import cv2
import numpy as np

import subprocess as sp

dfaker

import sys
import os
import mimetypes
import random

import mpv
import cv2
import numpy as np

import subprocess as sp