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import os

# This guide can only be run with the jax backend.
os.environ["KERAS_BACKEND"] = "jax"

from typing import Union
import keras
import keras.ops as kops
from keras import Model, Input, Layer

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import os
import gc
import cv2
import glob
import shutil
import random
import numpy as np
import matplotlib.pyplot as plt
from tqdm import tqdm

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An example of a diff code block:

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"""
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

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• Image Inpainting | Papers With Code
• Deep Image Prior - Wikipedia
• Inpainting - Wikipedia
• Introduction to image inpainting with deep learning on Weights & Biases
• Image inpainting with OpenCV and Python - PyImageSearch
• Image Inpainting — OpenCV-Python Tutorials 1 documentation
• Guide to Image Inpainting: Using machine learning to edit and correct defects in photos | by Jamshed Khan | Heartbeat
• [

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• Image Super-Resolution | Papers With Code
• Enhancing your photos through artificial intelligence
• Super-resolution imaging - Wikipedia
• [1904.07523] A Deep Journey into Super-resolution: A survey
• [1808.03344] Deep Learning for Single Image Super-Resolution: A Brief Review
• [1902.06068] Deep Learning for Image Super-resolution: A Survey
• An Introduction to Super Resolution using Deep Learning | by Bharath Raj | BeyondMinds | Medium
• [Deep learning based super resolution, without using a GAN | by C

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• Image Colorization: A Survey and Dataset
• Decrappification, DeOldification, and Super Resolution · fast.ai
• Black and white image colorization with OpenCV and Deep Learning - PyImageSearch
• Image Colorization using Convolutional Autoencoders | by Eryk Lewinson | Towards Data Science
• Colorizing Black & White images with Deep Learning | by Jair Ribeiro | Towards AI | Medium
• Colorizing B&W Photos with Neural Networks
• [Image Colorization with Deep Convolutional Neural Networks | SpringerLink](https://link.sprin

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"""
Usage:

# Create train data:
python generate_tfrecord.py -  --csv_input = <PATH_TO_ANNOTATIONS_FOLDER > /train_labels.csv - -output_path = <PATH_TO_ANNOTATIONS_FOLDER > /train.record

# Create test data:
python generate_tfrecord.py -  --csv_input = <PATH_TO_ANNOTATIONS_FOLDER > /test_labels.csv - -output_path = <PATH_TO_ANNOTATIONS_FOLDER > /test.record
"""

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