grayson

Okay, I read the tutorial. It did not help. The error is in the BeautifulSoup module which is built in. Idk the problem.

Well, I guess I will ask Mit than. (though nobody responds to my emails)

Here is what it says "module object is not callable" I never wrote a sequence of letters or anything that has to do with 'module' BeautifulSoup("img", "html.parser")

Hello! just so you know, you are very important to this community! if you want, check my posts to see what I did wrong to avoid future uh-oh's

no, I know what I am using. I called a module and It came out with a module error. I dont understand

I just need every English word put into one variable. Than with beautifulsoup I can look it up. Also, can you find why I am having syntax errors? I am relatively new to coding. Not saying I can't pull this off tho

import requests import bs4 as BeautifulSoup import tensorflow as ts import numpy as np import matplotlib as plt from keras.models import Sequential from keras.layers import Dense webiste = requests.get('https://pixabay.com/') soup = BeautifulSoup('img', "html.parser") percentage =(75) def data_dictionary ( aardvark = soup.find_all('aardvark'), abacus = soup.find_all('abacus'), abalone = soup.find_all('abalone'), ablaze = soup.find_all('ablaze'), a_bomb = soup.find_all('atomic bomb'), abomination = soup.find_all('abomination'), abstract = soup.find_all('abstract'), acid = soup.find_all('acid'), acorn = soup.find_all('acorn'), acoustic_guitar = soup.find_all('acoustic guitar'), acrobat = soup.find_all('acrobat'), actor = soup.find_all('actor') ): model = Sequential() model.add(Dense(units=64, activation='relu', input_dim=8)) # Input layer with 8 input features model.add(Dense(units=32, activation='relu')) # Hidden layer model.add(Dense(units=1, activation='sigmoid')) # Output layer model.compile(optimizer=data_dictionary, loss='binary_crossentropy', metrics=['accuracy']) print("IGNORE THIS MESSAGE") print(percentage) I haven't seen anything but syntax errors in who knows how long also, yes, I am manually typing every word in the dictionary

oh okay. Anyways, all I need to know is how to use beautiful soup and tensorflow together to sort out words. I also need a database with every (non-innapopriate) word in the dictionary. All it needs to do is let you be able to define every word at once. If you need to know why, just read the main post

from requests from bs4 import BeautifulSoup Goofy ahh invalid syntax 😑

Yh, kinda like that. But it is designed to put conjunctions and stuff after the tag. It finds the most optimal keywords to get similar results with.

Okay, well I need a way to simultaniously research every word in the dictionary. And If I am using pytorch, Can I just put the url in? how does it train off the images (I will e using pixabay)

Well, I am also using beautifull soup. I will show you the code so far: import requests from bs4 import BeautifulSoup import numpy as np import os import openai import nltk from nltk.tokenize import word_tokenize from nltk.corpus import stopwords from nltk.stem import PorterStemmer from PIL import Image print('type your img url in caps!') img_url = input() library = requests.get("https://pixabay.com/") soup = BeautifulSoup(library.content, 'html.parser') the_good_stuff = soup.content Junk = soup.find_all('img') image = Image.open(img_url) image_metadata = Junk.info print(image_metadata)

and how to fix this: Traceback (most recent call last): File "my directory", line 18, in <module> image = Image.open(img_url) ^^^^^^^^^^^^^^^^^^^ File "my directory", line 3218, in open fp = builtins.open(filename, "rb") ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ OSError: [Errno 22] Invalid argument: my directory of course, I cant show my actual directories

I just need a stable diffusion tutorial

I don't know if anyone knows this, but I have a little bit of knowlege in python and html. I was wondering if I could find a way to access a gallery of pictures with just one word describing them and with links. I need something like tihe "requests" python API but it puts the name into its database. I will than use numpy to store the pictures through links and convert them with this tool. Okay, now to the part Where You get to know what I am actually doing. I am creating a reverse stable diffusion software that turns images (whether they are ai generated or not) into prompts. Now, I am going through that proccess, and than I will use stable diffusion to merge the picture with a randomly generated image of every single word in the dictionary (other than the inapropriate stuff) than, based on how much it matches, based on percentage, it will add that word into the library of words that it will use. After it finds enough matches, It will give you those words, and with a grammar api, It will make it make sense and not something like "boy, pig, fish" you get what I am saying. I just need some help to finifsh this.

I know. I just realized I have to not count the original colors. Just the mixtures. So it would really be 2n-(n+1)

I was wondering. Why do hallucinations happen. I have heard people ay they have seen god (No, this isn't about religion) and I have heard they are other things, Such as dreams or hallucinations. But why do they happen. And is there a way to force it upon yourself? (Lucid dream during the day)

Oh, that is good! I was hoping I could find a way to shorten it. And no, I don't want to count the zero. Just because these are imaginary number doesn't mean they aren;t physical Uh, oh. I put in three and it came out seven. It should be 4 Nevermind I'm just stupid

That is good. But an easier way to write it down on a calculator is nCr(4, 2). than you would have to do everything else (Sorry, bad explaining. You have to find the triple mixtures and so on). so it would be: nCr(4, 1)+nCr(4, 2)+nCr(4, 3)+nCr(4, 4) = 15 I mean binomial coefficients

Thank you.

I see I have become a nuisance in the science world. I guess I will just stick to math

I guess I will keep posting math ideas that have nothing wrong and people still dislike because who knows why

Unfortunately not everyone has a degree and has to learn stuff by themselves.

Yes, and the only true wisdom is knowing that you know nothing. everything is possible

A man who knows extreme science but can't understand a simple metaphor. Interesting