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import time | |
from flask import Flask, jsonify | |
from opentelemetry import trace | |
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter | |
from opentelemetry.instrumentation.flask import FlaskInstrumentor | |
from opentelemetry.sdk.resources import Resource | |
from opentelemetry.sdk.trace import TracerProvider | |
from opentelemetry.sdk.trace.export import SimpleSpanProcessor |
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// ==UserScript== | |
// @name I see cute girls online | |
// @namespace ISCG | |
// @version 0.000000001 | |
// @description ... | |
// @author made by fredgy-kun | |
// @match https://*.aibooru.online/posts* | |
// @match https://*.aibooru.online/media_assets* | |
// @match https://*.aibooru.online/ | |
// @exclude https://*.aibooru.online/posts/* |
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import discord | |
from PIL import Image | |
import io | |
import json | |
import httpx | |
bot = discord.Bot() | |
@bot.slash_command() |
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// ==UserScript== | |
// @name Look Into The Deep ai | |
// @namespace LITD | |
// @version 1.0 | |
// @description ... | |
// @author made by fredgy-kun | |
// @match https://aibooru.online/uploads/* | |
// @match https://aibooru.online/posts/* | |
// @connect deepdanbooru.donmai.us | |
// @grant GM.xmlHttpRequest |
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import uuid | |
from apscheduler.events import EVENT_JOB_EXECUTED, EVENT_JOB_ERROR | |
from apscheduler.jobstores.sqlalchemy import SQLAlchemyJobStore | |
from flask import Flask | |
from flask_apscheduler import APScheduler | |
app = Flask(__name__) | |
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import time | |
from io import BytesIO | |
import pyvips | |
from PIL import Image # Pillow-SIMD | |
def figure_size(ih, iw, oh, ow): | |
if oh / ih >= ow / oh: | |
return int(iw * (oh / ih)), oh |
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<!DOCTYPE html> | |
<html lang="en"> | |
<head> | |
<meta charset="UTF-8"> | |
<meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
<meta http-equiv="X-UA-Compatible" content="ie=edge"> | |
<title>8Ball Pool by Fred & Rui</title> | |
<link rel="stylesheet" href="./css/main.css"> | |
<style> |
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article > div > div.css-1dbjc4n.r-16y2uox.r-1wbh5a2.r-1ny4l3l.r-1udh08x.r-1j3t67a > div > div.css-1dbjc4n.r-18u37iz > div.css-1dbjc4n.r-1iusvr4.r-16y2uox.r-1777fci.r-1mi0q7o > div:nth-child(2) > div:nth-child(2) > div > div > div > div > a > div > div.r-1p0dtai.r-1pi2tsx.r-1d2f490.r-u8s1d.r-ipm5af.r-13qz1uu > div > img{ | |
position: static !important; | |
opacity: unset !important; | |
} | |
article > div > div.css-1dbjc4n.r-16y2uox.r-1wbh5a2.r-1ny4l3l.r-1udh08x.r-1j3t67a > div > div.css-1dbjc4n.r-18u37iz > div.css-1dbjc4n.r-1iusvr4.r-16y2uox.r-1777fci.r-1mi0q7o > div:nth-child(2) > div:nth-child(2) > div > div > div > div > a > div > div.r-1p0dtai.r-1pi2tsx.r-1d2f490.r-u8s1d.r-ipm5af.r-13qz1uu > div > div{ | |
display: none !important; | |
} | |
article > div > div.css-1dbjc4n.r-16y2uox.r-1wbh5a2.r-1ny4l3l.r-1udh08x.r-1j3t67a > div > div.css-1dbjc4n.r-18u37iz > div.css-1dbjc4n.r-1iusvr4.r-16y2uox.r-1777fci.r-1mi0q7o > div:nth-child(2) > div:nth-child(2) > div > div > div > div > a > div > div.r-1p0dtai.r-1pi2tsx.r-1d2f4 |
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import pprint | |
import tensorflow as tf | |
import keras | |
import tensorflow_hub as hub | |
import numpy as np | |
import PIL.Image as Image | |
model_url = "https://tfhub.dev/google/imagenet/nasnet_mobile/classification/4" | |
IMAGE_SHAPE = (224, 224) | |
classifier = tf.keras.Sequential([hub.KerasLayer(model_url, input_shape=IMAGE_SHAPE + (3,))]) |
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import tensorflow as tf | |
from typing import Any, Union | |
import six | |
import math | |
import numpy as np | |
from skimage.transform import AffineTransform | |
from skimage import transform | |
import pprint | |
model = tf.keras.models.load_model("C:\\deepdanbooru-v3-20200101-sgd-e30\\model-resnet_custom_v3.h5") |
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