| """ | |
| Built on top of this gist by @karpathy: | |
| https://gist.github.com/karpathy/00103b0037c5aaea32fe1da1af553355 | |
| stable diffusion dreaming over text prompts | |
| creates hypnotic moving videos by smoothly walking randomly through the sample space | |
| example way to run this script: | |
| $ python stable_diffusion_walk.py --prompts "['blueberry spaghetti', 'strawberry spaghetti']" --seeds 243,523 --name berry_good_spaghetti |
feat: new featurefix(scope): bug in scopefeat!: breaking change / feat(scope)!: rework APIchore(deps): update dependenciesbuild: Changes that affect the build system or external dependencies (example scopes: gulp, broccoli, npm)ci: Changes to CI configuration files and scripts (example scopes: Travis, Circle, BrowserStack, SauceLabs)chore: Changes which doesn't change source code or tests e.g. changes to the build process, auxiliary tools, libraries
| from qtpy.QtWidgets import ( | |
| QPushButton, | |
| QComboBox, | |
| QTabWidget, | |
| QHBoxLayout, | |
| QFileDialog, | |
| QDialogButtonBox, | |
| QWidget, | |
| QSlider, | |
| ) |
| import sys, asyncio, random, threading, datetime | |
| from qtpy.QtWidgets import QApplication, QProgressBar | |
| from asyncqt import QEventLoop, QThreadExecutor | |
| app = QApplication(sys.argv) | |
| loop = QEventLoop(app) | |
| asyncio.set_event_loop(loop) | |
| progress = QProgressBar() |
| /** | |
| * GROOVY SCRIPT COMPUTING ON THE FLY EDGES OF A LABEL IMAGE | |
| * ----- | |
| * - Computes a sample label image | |
| * - Computes lazily with a disk cached cell img an image which finds the border of the labels in 3D | |
| * - Displays both images in BigDataViewer | |
| * | |
| * Code to create the label image mainly copied from: | |
| * - https://imagej.net/ImgLib2_Examples#Example_8_-_Working_with_sparse_data | |
| * - And https://github.com/imglib/imglib2-cache-examples |
| # code picked up from https://github.com/keras-team/keras/blob/master/keras/backend/tensorflow_backend.py | |
| # Just used tf.nn.weighted_cross_entropy_with_logits instead of tf.nn.sigmoid_cross_entropy_with_logits with input pos_weight in calculation | |
| import tensorflow as tf | |
| from keras import backend as K | |
| """ Weighted binary crossentropy between an output tensor and a target tensor. | |
| # Arguments | |
| pos_weight: A coefficient to use on the positive examples. | |
| # Returns |
| #!/bin/bash | |
| # change the package name to the existing PyPi package you would like to build and adjust the Python versions | |
| pkg='whitebox' | |
| array=( 3.5 3.6 3.7 ) | |
| echo "Building conda package ..." | |
| cd ~ | |
| conda skeleton pypi $pkg | |
| cd $pkg |
