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from utils import get_image_paths, load_images, stack_images
from training_data import get_training_data
import random
import numpy
import cv2
from keras.models import Model
from keras.layers import Input, Dense, Flatten, Reshape, concatenate, Add, add, Dropout
@dfaker
dfaker / imageGapsScanner.py
Last active February 5, 2018 01:43
imageGapsScanner
import numpy
import argparse
import os
import json
from tqdm import tqdm
import cv2
def main(args):
if not os.path.exists(args.input_dir_a[0]):
raise Exception("Folder A {} does not exist".format(args.input_dir_a[0]))
@dfaker
dfaker / interest.py
Last active September 30, 2019 20:31
import os
import glob
import subprocess as sp
import itertools
import sys
"""
import sys
import os
import mimetypes
import random
import mpv
import cv2
import numpy as np
import subprocess as sp
@dfaker
dfaker / selwebm.py
Created April 20, 2020 20:02
Webm Generation
import sys
import os
import mimetypes
import random
import mpv
import cv2
import numpy as np
import subprocess as sp
@dfaker
dfaker / processPrecomputedCrops.py
Created June 21, 2020 18:58
Crop rect detection head for vgg19
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
dfaker / synthHelper.py
Last active June 5, 2024 21:07
ebsynth helper
import cv2
import sys
import os
import subprocess as sp
import numpy as np
import time
baseFolder = os.path.split(__file__)[0]
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
dfaker / alternate_sampler_noise_schedules.py
Last active April 3, 2024 09:16
Alternate sampler noise schedules for stable-diffusion-webui
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):
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);