Datasets:

nyanko7
/

image-samples

Modalities:

image-samples / sample_novelai.py

Squashed

bc1ecc4 verified about 2 years ago

3.75 kB

import random
import io
import zipfile
import numpy as np
from PIL.PngImagePlugin import PngInfo
from PIL import Image
from curl_cffi import requests
from tqdm import tqdm

jwt_token = ""
random_seed = random.randint(0, 2**32 - 1)

# Define the API URL
url = "https://image.novelai.net/ai/generate-image"

# Set the headers
headers = {
    "Authorization": f"Bearer {jwt_token}",
    "Accept": "application/json, text/plain, */*",
    "Content-Type": "application/json",
    "Origin": "https://novelai.net",
    "Referer": "https://novelai.net/"
}

QUALITY_TAGS = "best quality, amazing quality, very aesthetic, absurdres"

# Define the payload
def generate(prompt="1girl, best quality, amazing quality, very aesthetic, absurdres"):
    # neg_prompt = "nsfw, lowres, {bad}, error, fewer, extra, missing, worst quality, jpeg artifacts, bad quality, watermark, unfinished, displeasing, chromatic aberration, signature, extra digits, artistic error, username, scan, [abstract]"
    payload = {
        "action": "generate",
        "input": f'{prompt}, best quality, amazing quality, very aesthetic, absurdres',
        "model": "nai-diffusion-3",
        "parameters": {
            "width": 832,
            "height": 1216,
            "scale": 5,
            "sampler": "k_euler_ancestral",
            "steps": 28,
            "n_samples": 1,
            "ucPreset": 0,
            "qualityToggle": True,
            "add_original_image": False,
            "cfg_rescale": 0,
            "controlnet_strength": 1,
            "dynamic_thresholding": False,
            "legacy": False,
            "noise_schedule": "karras",
            "seed": 8888,
            "sm": False,
            "sm_dyn": False,
            "uncond_scale": 1,
            "negative_prompt":"nsfw, lowres, bad, error, fewer, extra, missing, worst quality, jpeg artifacts, bad quality, watermark, unfinished, displeasing, chromatic aberration, signature, extra digits, artistic error, username, scan, [abstract], lowres, bad, error, fewer, extra, missing, worst quality, jpeg artifacts, bad quality, unfinished, displeasing, chromatic aberration, signature, extra digits, artistic error, username, scan, [abstract], chibi,doll, +_+",
            "legacy_v3_extend": False,
        }
    }

    # Send the POST request
    response = requests.post(url, impersonate="safari15_5", json=payload, headers=headers, timeout=120)
    
    # Save the response content (assuming it's a zip file)
    # with open('images.zip', 'wb') as f:
    #     f.write(response.content)
    
    zipfile_in_memory = io.BytesIO(response.content)
    with zipfile.ZipFile(zipfile_in_memory, 'r') as zip_ref:
        # Extract the list of file names
        file_names = zip_ref.namelist()

        # Check if there are files in the zip
        if file_names:
            # Open the first file as an image
            with zip_ref.open(file_names[0]) as file:
                # Display the image
                return Image.open(io.BytesIO(file.read())), payload

def process_image_and_save(image, path):
    metadata = PngInfo()

    image = image.convert('RGBA')
    image = Image.fromarray(np.array(image)[:,:,:3])
    image.save(path, pnginfo=metadata, quality=95, format="WEBP")
    print(path)

# read prompts for testing
with open("prompts.csv") as f:
    prompts = f.readlines()
    
# warmup
generate("abcd")

# generate images
for i, prompt in tqdm(enumerate(prompts), total=len(prompts)):
    try:
        image, payload = generate(prompt.strip())
        image = image.convert('RGBA')
        image = Image.fromarray(np.array(image)[:,:,:3])
        fn = f"naiv3/{i+1}.webp"
        image.save(fn, quality=95, format="WEBP")
    except Exception as e:
        print(e)
        continue

	import random
	import io
	import zipfile
	import numpy as np
	from PIL.PngImagePlugin import PngInfo
	from PIL import Image
	from curl_cffi import requests
	from tqdm import tqdm

	jwt_token = ""
	random_seed = random.randint(0, 2**32 - 1)

	# Define the API URL
	url = "https://image.novelai.net/ai/generate-image"

	# Set the headers
	headers = {
	"Authorization": f"Bearer {jwt_token}",
	"Accept": "application/json, text/plain, /",
	"Content-Type": "application/json",
	"Origin": "https://novelai.net",
	"Referer": "https://novelai.net/"
	}

	QUALITY_TAGS = "best quality, amazing quality, very aesthetic, absurdres"

	# Define the payload
	def generate(prompt="1girl, best quality, amazing quality, very aesthetic, absurdres"):
	# neg_prompt = "nsfw, lowres, {bad}, error, fewer, extra, missing, worst quality, jpeg artifacts, bad quality, watermark, unfinished, displeasing, chromatic aberration, signature, extra digits, artistic error, username, scan, [abstract]"
	payload = {
	"action": "generate",
	"input": f'{prompt}, best quality, amazing quality, very aesthetic, absurdres',
	"model": "nai-diffusion-3",
	"parameters": {
	"width": 832,
	"height": 1216,
	"scale": 5,
	"sampler": "k_euler_ancestral",
	"steps": 28,
	"n_samples": 1,
	"ucPreset": 0,
	"qualityToggle": True,
	"add_original_image": False,
	"cfg_rescale": 0,
	"controlnet_strength": 1,
	"dynamic_thresholding": False,
	"legacy": False,
	"noise_schedule": "karras",
	"seed": 8888,
	"sm": False,
	"sm_dyn": False,
	"uncond_scale": 1,
	"negative_prompt":"nsfw, lowres, bad, error, fewer, extra, missing, worst quality, jpeg artifacts, bad quality, watermark, unfinished, displeasing, chromatic aberration, signature, extra digits, artistic error, username, scan, [abstract], lowres, bad, error, fewer, extra, missing, worst quality, jpeg artifacts, bad quality, unfinished, displeasing, chromatic aberration, signature, extra digits, artistic error, username, scan, [abstract], chibi,doll, +_+",
	"legacy_v3_extend": False,
	}
	}

	# Send the POST request
	response = requests.post(url, impersonate="safari15_5", json=payload, headers=headers, timeout=120)

	# Save the response content (assuming it's a zip file)
	# with open('images.zip', 'wb') as f:
	# f.write(response.content)

	zipfile_in_memory = io.BytesIO(response.content)
	with zipfile.ZipFile(zipfile_in_memory, 'r') as zip_ref:
	# Extract the list of file names
	file_names = zip_ref.namelist()

	# Check if there are files in the zip
	if file_names:
	# Open the first file as an image
	with zip_ref.open(file_names[0]) as file:
	# Display the image
	return Image.open(io.BytesIO(file.read())), payload

	def process_image_and_save(image, path):
	metadata = PngInfo()

	image = image.convert('RGBA')
	image = Image.fromarray(np.array(image)[:,:,:3])
	image.save(path, pnginfo=metadata, quality=95, format="WEBP")
	print(path)

	# read prompts for testing
	with open("prompts.csv") as f:
	prompts = f.readlines()

	# warmup
	generate("abcd")

	# generate images
	for i, prompt in tqdm(enumerate(prompts), total=len(prompts)):
	try:
	image, payload = generate(prompt.strip())
	image = image.convert('RGBA')
	image = Image.fromarray(np.array(image)[:,:,:3])
	fn = f"naiv3/{i+1}.webp"
	image.save(fn, quality=95, format="WEBP")
	except Exception as e:
	print(e)
	continue