Daniel Manzke manzke

Example usage of MODNet (https://github.com/ZHKKKe/MODNet) for Background Removal in CPU Mode. I've adopted their interference code.

Get weights gdown --id 1mcr7ALciuAsHCpLnrtG_eop5-EYhbCmz -O pretrained/modnet_photographic_portrait_matting.ckpt

	# pip install --upgrade PyPDF2
	# python analyze_pdf.py <pdf_file>

	import sys
	import PyPDF2
	from PyPDF2.generic import IndirectObject, DictionaryObject, ArrayObject, NameObject
	import struct

	def analyze_pdf(file_path):
	findings = []

	# script to create movie from multiple png files
	# taken in choronoligcal order

	# start at 0
	count=0
	# take all files named shot - something ordered by date
	for f in `ls fakes*.jpg`
	do
	# get the index in 0000 format
	printf -v counts "%06d" $count

	import logging
	import matplotlib.pyplot as plt
	import numpy as np
	import os
	import tensorflow as tf
	import tensorflow_datasets as tfds
	tf.keras.backend.clear_session()
	from tensorflow.keras.layers import Conv2D, Conv2DTranspose, \
	Dense, Layer, Reshape, InputLayer, Flatten
	from tqdm import tqdm

	import os
	import logging
	import matplotlib.pyplot as plt
	import numpy as np
	import tensorflow as tf
	import tensorflow_datasets as tfds
	tf.keras.backend.clear_session()
	from tensorflow.keras.layers import Conv2D, Conv2DTranspose, \
	Dense, Layer, Reshape, InputLayer, Flatten
	from tensorflow import keras

	# import the necessary packages
	import tensorflow as tf
	from tensorflow import keras
	from tensorflow.keras import layers
	from tensorflow.keras.models import Model
	from tensorflow.keras.applications.efficientnet import EfficientNetB3, EfficientNetB4, EfficientNetB5, preprocess_input

	'''
	EfficientNetB0 - (224, 224, 3)
	EfficientNetB1 - (240, 240, 3)