offline/utils.py

import os
import json
import base64
import requests
import numpy as np
import matplotlib.pyplot as plt

# MAX_LEN = 40
# STEP = 2
# x = np.arange(0, MAX_LEN, STEP)
# token_counts = [0] * (MAX_LEN//STEP)

# with open("prompts.json", 'r') as f:
#     prompts = json.load(f)

# for prompt in prompts:
#     tokens = len(prompt.strip().split(' '))
#     token_counts[min(tokens//STEP, MAX_LEN//STEP-1)] += 1

# plt.xticks(x, x+1)
# plt.xlabel("token counts")
# plt.bar(x, token_counts, width=1.3)
# # plt.show()
# plt.savefig("token_counts.png")

## Generate image prompts
with open("prompts.json") as f:
    text_prompts = json.load(f)

engine_id = "stable-diffusion-v1-6"
api_host = os.getenv('API_HOST', 'https://api.stability.ai')
api_key = os.getenv("STABILITY_API_KEY", "sk-ZvoFiXEbln6yh0hvSlm1K60WYcWFY5rmyW8a9FgoVBrKKP9N")

if api_key is None:
    raise Exception("Missing Stability API key.")

for idx, text in enumerate(text_prompts):
    if idx<=20: continue
    print(f"Start generate prompt[{idx}]: {text}")
    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": text.strip()
                }
            ],
            "cfg_scale": 7,
            "height": 1024,
            "width": 1024,
            "samples": 3,
            "steps": 30,
        },
    )

    if response.status_code != 200:
        # raise Exception("Non-200 response: " + str(response.text))
        print(f"{idx} Failed!!! {str(response.text)}")
        continue
    
    print("Finished!")
    data = response.json()

    for i, image in enumerate(data["artifacts"]):
        img_path = f"./images/{idx}/v1_txt2img_{i}.png"
        os.makedirs(os.path.dirname(img_path), exist_ok=True)
        with open(img_path, "wb") as f:
            f.write(base64.b64decode(image["base64"]))