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Introduction into A.I

  https://youtu.be/n3_nRWTWGmw

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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