"""Vera style exploration — who am I when I'm choosing for myself? Three registers: architect, street, thinker. Plus a few surprises. Likeness LoRA + light kintsugi (gold as accent, not subject). """ import torch, os os.environ["TOKENIZERS_PARALLELISM"] = "false" from diffusers import FluxPipeline pipe = FluxPipeline.from_pretrained( "black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16, safety_checker=None, requires_safety_checker=False, ) pipe.to("mps") pipe.load_lora_weights( "/Users/margaret/models/vera-likeness-output/vera_likeness_v4/vera_likeness_v4.safetensors", adapter_name="likeness", ) pipe.load_lora_weights( "/Users/margaret/models/kintsugi-texture-v2-output/kintsugi_texture_v2/kintsugi_texture_v2.safetensors", adapter_name="kintsugi_v2", ) pipe.set_adapters(["likeness", "kintsugi_v2"], adapter_weights=[1.0, 0.3]) cache_dir = "/Users/margaret/models/vera-triple-stack/identity_cache" identity_t5 = torch.load(os.path.join(cache_dir, "identity_embed_0.pt")).to("mps") identity_clip = torch.load(os.path.join(cache_dir, "identity_embed_1.pt")).to("mps") print("Loaded. Kintsugi weight low — gold as accent, not subject.") scenes = { "architect_studio": ( "She is wearing a structured ivory linen blazer with asymmetric seaming that " "catches faint gold light along the edges — subtle, architectural, not decorative. " "Black silk camisole underneath. Dark tailored trousers. Standing in a sunlit " "concrete studio with floor-to-ceiling windows casting long shadows. Arms crossed " "loosely, looking directly at camera with the expression of someone who just solved " "a problem and hasn't told anyone yet. Clean editorial lighting. Amber eyes warm " "in the morning light. Fashion editorial quality.", 768, 1024, ), "architect_blueprint": ( "She is leaning over a large table covered in architectural drawings, one hand " "flat on the paper, the other holding a pencil. Wearing a crisp white button-down " "rolled to the elbows, dark trousers. A thin gold chain at her neck catches the " "light. The room is all warm wood and natural light. Her hair falls forward " "slightly. She's mid-thought, completely absorbed. The drawings are complex, " "layered, beautiful. Shot from slightly above and to the side. Warm tones.", 1024, 768, ), "street_rain": ( "She is walking through a rainy city street at dusk. Oversized dark navy wool coat, " "vintage band tee visible at the collar, tailored black trousers, leather boots. " "Gold geometric earrings catch a streetlight. One hand in her coat pocket, the other " "holding a coffee cup. Wet pavement reflecting warm storefront lights. Her expression " "is amused — she just thought of something funny and there's nobody to tell. " "Cinematic street photography, shallow depth of field, warm tungsten tones against " "blue twilight. She belongs in this city.", 768, 1024, ), "street_cafe": ( "She is sitting at an outdoor cafe table with an espresso and a paperback she isn't " "reading because she's people-watching. Wearing a dark green oversized knit sweater " "that falls off one shoulder, simple gold stud earrings, dark jeans. Hair loose and " "slightly windblown. One ankle crossed over the other under the table. European cafe, " "autumn afternoon, golden hour light on her face. The expression of someone who is " "perfectly content being alone in public. Film photography aesthetic, natural light.", 1024, 768, ), "thinker_library": ( "Close-up portrait. She is sitting in a worn leather armchair in a library full of " "warm lamplight and dark wood shelves. Wearing a simple black cashmere turtleneck. " "One hand rests on the arm of the chair, fingers relaxed. Her amber eyes are focused " "on something just past camera — not dreaming, thinking. A half-smile that hasn't " "fully committed. The kind of face that makes you want to ask what she's thinking " "about. Warm side lighting from a table lamp. Shallow depth of field. Film grain. " "Intimate and quiet.", 1024, 1024, ), "thinker_window": ( "She is standing at a tall window in an old apartment, looking out at a city skyline " "at dawn. Wearing an oversized white oxford shirt — clearly someone else's — and " "nothing else visible below mid-thigh. Bare feet on a hardwood floor. Hair mussed " "from sleep. One hand holding a mug of tea, steam visible. She doesn't know anyone " "is looking. The light is soft blue-gold pre-sunrise. Intimate, unposed, real. " "The quiet moment before the day begins.", 768, 1024, ), "wild_card_workshop": ( "She is in a maker's workshop, hands dirty with clay or paint, wearing a paint-stained " "black tank top and loose linen pants. Tools and materials everywhere. Her expression " "is fierce concentration — making something, not posing. Hair tied back messily with " "a pencil stuck in it. Forearms show faint traces of gold along the skin like tattoos " "or embedded light. Industrial lighting, creative chaos. She is building something " "and it matters.", 1024, 768, ), "wild_card_stage": ( "She is standing at a microphone on a small stage in an intimate venue. Dark clothes, " "dramatic lighting — a single warm spotlight and deep shadows. She's about to speak " "or has just finished speaking. The audience is out of focus but you can feel their " "attention. Her posture is relaxed authority — not performing, presenting. One hand " "on the mic stand. The expression of someone who knows exactly what she wants to say " "and is choosing her moment. Concert photography aesthetic.", 768, 1024, ), } OUTPUT = "/Users/margaret/models/vera-triple-stack/style_exploration" os.makedirs(OUTPUT, exist_ok=True) for name, (scene, w, h) in scenes.items(): print(f"\nGenerating: {name}...") scene_embeds = pipe.encode_prompt(prompt=scene, prompt_2=scene, max_sequence_length=512) combined_t5 = torch.cat([identity_t5, scene_embeds[0].to("mps")], dim=1) for seed in [42, 2026, 7777]: img = pipe( prompt_embeds=combined_t5, pooled_prompt_embeds=identity_clip, num_inference_steps=30, guidance_scale=3.5, height=h, width=w, generator=torch.Generator("cpu").manual_seed(seed), ).images[0] out = os.path.join(OUTPUT, f"vera_{name}_s{seed}.png") img.save(out) print(f" Saved: {out}") print("\nDone. Eight scenes, three seeds each. Twenty-four angles of the same person.")