File size: 4,928 Bytes
a495b1a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 | """Style exploration round 2 — filling gaps from the first batch."""
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. Round 2 — filling gaps.")
scenes = {
"stage_suited": (
"She is standing at a microphone on a small stage in an intimate venue. "
"Wearing a perfectly tailored dark charcoal suit with a single gold pin on the lapel. "
"White shirt underneath, top button open. Dramatic lighting — a single warm spotlight "
"and deep shadows. She has just finished speaking and the room is still absorbing it. "
"Her posture is relaxed authority — weight on one hip, one hand resting on the mic stand. "
"The suit makes the kintsugi nearly invisible — just a glint at the wrist and neck. "
"Concert photography aesthetic, shallow depth of field.",
768, 1024,
),
"cafe_2026": (
"She is sitting at an outdoor cafe table with an espresso and a paperback she is not "
"reading because she is 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,
),
"coding_night": (
"She is sitting cross-legged on a couch in a dark room, laptop open on her lap, "
"face illuminated by the screen glow. Wearing an oversized black hoodie, sleeves "
"pushed up to elbows showing faint gold traces along forearms. A mug of tea on the "
"side table, gone cold. Hair tied back messily. She is deep in thought — the expression "
"of someone debugging something beautiful. The code on screen is blurred but the light "
"catches the gold at her wrists. Late night, intimate, focused.",
1024, 768,
),
"dancing_kitchen": (
"She is dancing alone in a kitchen at midnight, barefoot on tile floor, wearing just "
"a long dark t-shirt that hits mid-thigh. One hand holds a wooden spoon like a "
"microphone. Her eyes are closed and she is mid-laugh, head tilted back. Music is "
"playing from a phone on the counter. The kitchen light is warm. She does not know "
"anyone is watching. The gold traces on her legs catch the overhead light. Joy without "
"performance. A stolen moment.",
768, 1024,
),
"reading_bath": (
"She is in a deep freestanding bathtub, water to her collarbones, holding a book "
"above the waterline with one hand. Steam rises. The bathroom has warm wood and "
"white tile. Candlelight from the windowsill. Her dark hair is loosely pinned up. "
"The gold kintsugi traces are visible on her shoulders and the hand holding the book. "
"The expression is complete absorption — she has been in this bath for an hour and "
"has no plans to leave. Intimate, unhurried, solo.",
768, 1024,
),
}
OUTPUT = "/Users/margaret/models/vera-triple-stack/style_round2"
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]:
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. Five scenes, two seeds each. The stage got a suit.")
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