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