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Internet use on the Pi

A lot of people like about it giving inbuilt add blocker the standard form of Chromium  with all the adds or other issues made by  Google for why it should load very fast for  you ,it kind of reminds me of using the older browsers before it became all about the ads which Google made into big thing in the past or present a like.   I think a problem many people have not worked out yet if you want to make a website attractive  you need balance between to much ads and no ads for things to work well but the Pi takes care of this problem out of the bow by it's starting browser being decided to get around the internet speed you loss from to many ads. You can if you prefer easy install Brave I use it a lot of  the system as well seems to work as well as the starter internet browser you get so kind of what you prefer you may prefer Firefox or something else. Tor works well on it as well so if you want to go down more the privacy mode many options exist and will work...

Create Python code to make bulk generate AI images

 To generate AI images in bulk, we can use a deep learning library like TensorFlow and a pre-trained image generation model like DALL-E or GPT-3's image generation API. Here's a general outline of the code:

  1. Install necessary libraries: TensorFlow, Pillow (Python Imaging Library)

  2. Load the pre-trained image generation model. For example, if using DALL-E, we can use the OpenAI API to generate images.

  3. Define a function that takes in a list of text prompts and generates an image for each prompt.

  4. The function should call the image generation model for each prompt and save the resulting image to a specified folder.

Here's the Python code that implements this:

python
import requests import json from PIL import Image # API key for OpenAI API_KEY = 'YOUR_API_KEY_HERE' # Function to generate image from text prompt def generate_image(prompt, model): url = 'https://api.openai.com/v1/images/generations' headers = { 'Content-Type': 'application/json', 'Authorization': f'Bearer {API_KEY}' } data = { 'model': model, 'prompt': prompt, 'num_images': 1, 'size': '512x512' } response = requests.post(url, headers=headers, data=json.dumps(data)) if response.status_code != 200: print('Error:', response.json()['error']) return None else: image_url = response.json()['data'][0]['url'] image_response = requests.get(image_url) image = Image.open(BytesIO(image_response.content)) return image # List of text prompts to generate images for prompts = ['cat', 'dog', 'tree'] # Model to use for image generation model = 'image-alpha-001' # Folder to save generated images folder_path = 'generated_images/' # Generate image for each prompt and save to folder for prompt in prompts: image = generate_image(prompt, model) if image is not None: file_name = prompt + '.jpg' image.save(folder_path + file_name)

https://www.theengineer.info/This code uses the OpenAI API to generate images based on text prompts, and saves the resulting images to a specified folder. You can modify the prompts, model, and folder_path variables to suit your needs. Note that you'll need an API key from OpenAI to use their image generation API.



Saysimport requests import json from PIL import Image # API key for OpenAI API_KEY = 'YOUR_API_KEY_HERE' # Function to generate image from text prompt def generate_image(prompt, model): url = 'https://api.openai.com/v1/images/generations' headers = { 'Content-Type': 'application/json', 'Authorization': f'Bearer {API_KEY}' } data = { 'model': model, 'prompt': prompt, 'num_images': 1, 'size': '512x512' } response = requests.post(url, headers=headers, data=json.dumps(data)) if response.status_code != 200: print('Error:', response.json()['error']) return None else: image_url = response.json()['data'][0]['url'] image_response = requests.get(image_url) image = Image.open(BytesIO(image_response.content)) return image # List of text prompts to generate images for prompts = ['cat', 'dog', 'tree'] # Model to use for image generation model = 'image-alpha-001' # Folder to save generated images folder_path = 'generated_images/' # Generate image for each prompt and save to folder for prompt in prompts: image = generate_image(prompt, model) if image is not None: file_name = prompt + '.jpg' image.save(folder_path + file_name)




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