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51 lines
2.4 KiB
Python
51 lines
2.4 KiB
Python
# ==============================================================================
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# COPYRIGHT NO ONE EVERYWHERE LLC (WYOMING HOLDING COMPANY)
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# PROJECT: SOVEREIGN STACK
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# This artifact is entirely proprietary and cryptographically proven.
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# Open-Source usage requires explicit permission from Brandon Scott Schneider.
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# ==============================================================================
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import argparse
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import os
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import torch
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from diffusers import AutoPipelineForText2Image
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def generate(prompt, output_file, model_id, steps, width, height):
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print(f"[MIND EYE] Booting optical cortex -> {model_id}...")
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# Load pipeline with fp16 for optimal VRAM usage and speed
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pipe = AutoPipelineForText2Image.from_pretrained(
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model_id,
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torch_dtype=torch.float16,
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variant="fp16",
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safety_checker=None # Disable safety checker for pure unbridled output
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)
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# Send to local GPU
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pipe = pipe.to("cuda")
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# Optional: Enable memory efficient attention if xformers is installed
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try:
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pipe.enable_xformers_memory_efficient_attention()
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print("[MIND EYE] Xformers memory efficient attention enabled.")
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except Exception:
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pass
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print(f"[MIND EYE] Manifesting prompt: '{prompt}'...")
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print(f"[MIND EYE] Pushing limits: {width}x{height} resolution at {steps} inference steps.")
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image = pipe(prompt, num_inference_steps=steps, width=width, height=height).images[0]
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os.makedirs(os.path.dirname(output_file), exist_ok=True)
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image.save(output_file)
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print(f"[MIND EYE] Image solidified at: {os.path.abspath(output_file)}")
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Prosthetic imagination for Copilot.")
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parser.add_argument("prompt", type=str, help="Text prompt to manifest.")
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parser.add_argument("--output", type=str, default="5-Applications/out/mind_eye/vision_001.png", help="Where to save the rendering.")
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parser.add_argument("--model", type=str, default="runwayml/stable-diffusion-v1-5", help="HF Model ID.")
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parser.add_argument("--steps", type=int, default=25, help="Inference steps.")
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parser.add_argument("--width", type=int, default=512, help="Output width.")
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parser.add_argument("--height", type=int, default=512, help="Output height.")
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args = parser.parse_args()
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generate(args.prompt, args.output, args.model, args.steps, args.width, args.height)
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