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:
Install necessary libraries: TensorFlow, Pillow (Python Imaging Library)
Load the pre-trained image generation model. For example, if using DALL-E, we can use the OpenAI API to generate images.
Define a function that takes in a list of text prompts and generates an image for each prompt.
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:
pythonimport 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.
![Python code 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)](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi-Sul6EXZn2_cRpOv8CJLrNiDvsv3A2BEsqw2WgsWuYsMN8wRrHNZMJvY2K4U6c3i53M2BSKogSSr_y-VcbOU6vcdFtZcZnEoTUI4t8b97vdo0bskhPQoaKIREjHiMAKfoVaOoJ6HVlchrd4m48afQkgUiWb8AvU7bnVSe1MHW1LuNcxyCpwL9RCKN/w320-h178-rw/Screenshot%20on%202023-04-03%20at%2012_59_02.png)
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