Image Generation DALLE 3 vs Stable Diffusion

Prompt - A picturesque countryside in autumn splendor, with rolling hills adorned in warm fall colors, a quaint farmhouse sitting amidst harvested fields, Latest 2023 Tesla Car nestled under a canopy of russet leaves.

DALLE 3

Stable Diffusion

	#EXAMPLE #1
	#!pip install openai
	from openai import OpenAI
	import os
	os.environ["OPENAI_API_KEY"] = "AAAAAAAAAAAAAAAAAAAAAAAAAAAAA"
	client = OpenAI()
	response = client.images.generate(
	model="dall-e-3",
	prompt="A picturesque countryside in autumn splendor, with rolling hills adorned in warm fall colors, a quaint farmhouse sitting amidst harvested fields, Latest 2023 Tesla Car nestled under a canopy of russet leaves.",
	size="1024x1024",
	quality="standard",
	n=1,
	)
	image_url = response.data[0].url
	image_url
	#EXAMPLE #2
	import base64
	import os
	import requests
	#https://platform.stability.ai/docs/api-reference#tag/v1engines/operation/listEngines
	#Stability-AI Stable Diffusion XL v1.0
	#engine_id = "stable-diffusion-xl-1024-v1-0"
	#Stability-AI Stable Diffusion v2.1
	engine_id = "stable-diffusion-512-v2-1"
	api_host = os.getenv('API_HOST', 'https://api.stability.ai')
	api_key = os.getenv("STABILITY_API_KEY", "AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA")
	if api_key is None:
	raise Exception("Missing Stability API key.")
	response = requests.post(
	f"{api_host}/v1/generation/{engine_id}/text-to-image",
	headers={
	"Content-Type": "application/json",
	"Accept": "application/json",
	"Authorization": f"Bearer {api_key}"
	},
	json={
	"text_prompts": [
	{
	"text": "A picturesque countryside in autumn splendor, with rolling hills adorned in warm fall colors, a quaint farmhouse sitting amidst harvested fields, Latest 2023 Tesla Car nestled under a canopy of russet leaves."
	}
	],
	"cfg_scale": 7,
	"height": 1024,
	"width": 1024,
	"samples": 1,
	"steps": 50,
	"style_preset":"photographic",
	"clip_guidance_preset":"FAST_BLUE",
	},
	)
	if response.status_code != 200:
	raise Exception("Non-200 response: " + str(response.text))
	data = response.json()
	for i, image in enumerate(data["artifacts"]):
	with open(f"v1_txt2img_{i}.png", "wb") as f:
	f.write(base64.b64decode(image["base64"]))
	from PIL import Image
	import matplotlib.pyplot as plt
	# Assuming you know the filename or you get it from the upload step
	filename = 'v1_txt2img_0.png'
	# Open the image file using PIL
	image = Image.open(filename)
	# Display the image using Matplotlib
	plt.imshow(image)
	plt.axis('off') # Hide the axis to make it look cleaner
	plt.show()

view raw texttoimage.py hosted with ❤ by GitHub

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