Please use the script below as a shell command and save to /usr/local/bin/lark in the execution environment
#!/usr/bin/env bash
action=$1
url=$2| I want you to help me make requests (prompts) for the Stable Diffusion neural network. | |
| Stable diffusion is a text-based image generation model that can create diverse and high-quality images based on your requests. In order to get the best results from Stable diffusion, you need to follow some guidelines when composing prompts. | |
| Here are some tips for writing prompts for Stable diffusion1: | |
| 1) Be as specific as possible in your requests. Stable diffusion handles concrete prompts better than abstract or ambiguous ones. For example, instead of “portrait of a woman” it is better to write “portrait of a woman with brown eyes and red hair in Renaissance style”. | |
| 2) Specify specific art styles or materials. If you want to get an image in a certain style or with a certain texture, then specify this in your request. For example, instead of “landscape” it is better to write “watercolor landscape with mountains and lake". | |
| 3) Specify specific artists for reference. If you want to get an image similar to the work of some |
| Stable Diffusion is an AI art generation model similar to DALLE-2. | |
| Here are some prompts for generating art with Stable Diffusion. | |
| Example: | |
| - A ghostly apparition drifting through a haunted mansion's grand ballroom, illuminated by flickering candlelight. Eerie, ethereal, moody lighting. | |
| - portait of a homer simpson archer shooting arrow at forest monster, front game card, drark, marvel comics, dark, smooth | |
| - pirate, deep focus, fantasy, matte, sharp focus | |
| - red dead redemption 2, cinematic view, epic sky, detailed, low angle, high detail, warm lighting, volumetric, godrays, vivid, beautiful | |
| - a fantasy style portrait painting of rachel lane / alison brie hybrid in the style of francois boucher oil painting, rpg portrait |
| #!/bin/bash | |
| text=$1 | |
| if [[ $# -eq 0 ]]; then | |
| # read from pipe | |
| read -t 1 text | |
| fi | |
| if [[ ${text} == "" ]]; then |
| package com.xinghui.notificationlistenerservicedemo; | |
| import android.app.ActivityManager; | |
| import android.app.Service; | |
| import android.content.ComponentName; | |
| import android.content.Context; | |
| import android.content.Intent; | |
| import android.content.pm.PackageManager; | |
| import android.os.IBinder; | |
| import android.os.Process; |
| /* | |
| * Copyright (C) 2014 The Android Open Source Project | |
| * | |
| * Licensed under the Apache License, Version 2.0 (the "License"); | |
| * you may not use this file except in compliance with the License. | |
| * You may obtain a copy of the License at | |
| * | |
| * http://www.apache.org/licenses/LICENSE-2.0 | |
| * | |
| * Unless required by applicable law or agreed to in writing, software |
| public class MainActivity extends Activity { | |
| @Override | |
| protected void onCreate(Bundle savedInstanceState) { | |
| super.onCreate(savedInstanceState); | |
| setContentView(R.layout.layoutfab); | |
| //Outline | |
| int size = getResources().getDimensionPixelSize(R.dimen.fab_size); | |
| Outline outline = new Outline(); |
(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.