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| import os | |
| import logging | |
| import numpy as np | |
| import cv2 | |
| from dotenv import load_dotenv | |
| from huggingface_hub import InferenceClient, HfFolder | |
| from PIL import Image | |
| load_dotenv() | |
| # Acquire token | |
| hf_token = os.getenv("HUGGING_FACE_HUB_TOKEN") or HfFolder.get_token() | |
| if not hf_token: | |
| print("❌ No Hugging Face token found. Signature generation will fail.") | |
| CLIENT = None | |
| else: | |
| print("✅ Using Hugging Face token for signature generation.") | |
| CLIENT = InferenceClient(token=hf_token) | |
| MODEL_ID = "stabilityai/stable-diffusion-xl-base-1.0" | |
| def generate_signatures(name: str, num_variations: int = 3) -> list: | |
| """Generates multiple signature variations for a given name.""" | |
| if CLIENT is None: | |
| return [] | |
| prompts = [ | |
| f"A clean, elegant, handwritten signature of the name '{name}' on a plain white background. Cursive, professional.", | |
| f"Calligraphy signature of '{name}'. Black ink on white paper. Minimalist, artistic.", | |
| f"A doctor's signature for '{name}'. Quick, scribbled, but legible. Official-looking script." | |
| ] | |
| images = [] | |
| for i in range(num_variations): | |
| prompt = prompts[i % len(prompts)] | |
| logging.info(f"Generating signature variation {i+1} for '{name}'…") | |
| try: | |
| pil_img = CLIENT.text_to_image( | |
| prompt, | |
| model=MODEL_ID, | |
| negative_prompt=( | |
| "photograph, text, multiple signatures, watermark, blurry, colorful, background" | |
| ), | |
| guidance_scale=8.0 | |
| ) | |
| np_img = np.array(pil_img) | |
| cv_img = cv2.cvtColor(np_img, cv2.COLOR_RGB2BGR) | |
| images.append(cv_img) | |
| except Exception as e: | |
| logging.error(f"❌ Signature generation failed: {e}") | |
| return images | |