var neural0 = { weight: 0.000, bias: 0.500 };
var neural1 = { weight: 0.757, bias: 0.270 };
var neural2 = { weight: 0.818, bias: -0.208 };
var neural3 = { weight: 0.127, bias: -0.495 };
var neural4 = { weight: -0.681, bias: -0.327 };
var neural5 = { weight: -0.863, bias: 0.142 };
var neural6 = { weight: -0.251, bias: 0.480 };
var neural7 = { weight: 0.591, bias: 0.377 };
var neural8 = { weight: 0.890, bias: -0.073 };
var neural9 = { weight: 0.371, bias: -0.456 };
var neural10 = { weight: -0.490, bias: -0.420 };
var neural11 = { weight: -0.900, bias: 0.002 };
var neural12 = { weight: -0.483, bias: 0.422 };
var neural13 = { weight: 0.378, bias: 0.454 };
var neural14 = { weight: 0.892, bias: 0.068 };
var neural15 = { weight: 0.585, bias: -0.380 };
var neural16 = { weight: -0.259, bias: -0.479 };
var neural17 = { weight: -0.865, bias: -0.138 };
var neural18 = { weight: -0.676, bias: 0.330 };
var neural19 = { weight: 0.135, bias: 0.494 };
var neural20 = { weight: 0.822, bias: 0.204 };
var neural21 = { weight: 0.753, bias: -0.274 };
var neural22 = { weight: -0.008, bias: -0.500 };
var neural23 = { weight: -0.762, bias: -0.266 };
var neural24 = { weight: -0.815, bias: 0.212 };
var neural25 = { weight: -0.119, bias: 0.496 };
var neural26 = { weight: 0.686, bias: 0.323 };
var neural27 = { weight: 0.861, bias: -0.146 };
var neural28 = { weight: 0.244, bias: -0.481 };
var neural29 = { weight: -0.597, bias: -0.374 };
var neural30 = { weight: -0.889, bias: 0.077 };
var neural31 = { weight: -0.364, bias: 0.457 };
var neural32 = { weight: 0.496, bias: 0.417 };
var neural33 = { weight: 0.900, bias: -0.007 };
var neural34 = { weight: 0.476, bias: -0.424 };
var neural35 = { weight: -0.385, bias: -0.452 };
var neural36 = { weight: -0.893, bias: -0.064 };
var neural37 = { weight: -0.579, bias: 0.383 };
var neural38 = { weight: 0.267, bias: 0.478 };
var neural39 = { weight: 0.867, bias: 0.133 };
var neural40 = { weight: 0.671, bias: -0.333 };
var neural41 = { weight: -0.143, bias: -0.494 };
var neural42 = { weight: -0.825, bias: -0.200 };
var neural43 = { weight: -0.749, bias: 0.278 };
var neural44 = { weight: 0.016, bias: 0.500 };
var neural45 = { weight: 0.766, bias: 0.263 };
var neural46 = { weight: 0.812, bias: -0.216 };
var neural47 = { weight: 0.111, bias: -0.496 };
var neural48 = { weight: -0.691, bias: -0.320 };
var neural49 = { weight: -0.858, bias: 0.150 };
var neural50 = { weight: -0.236, bias: 0.482 };
var neural51 = { weight: 0.603, bias: 0.371 };
var neural52 = { weight: 0.888, bias: -0.081 };
var neural53 = { weight: 0.356, bias: -0.459 };
var neural54 = { weight: -0.503, bias: -0.415 };
var neural55 = { weight: -0.900, bias: 0.011 };
var neural56 = { weight: -0.469, bias: 0.427 };
var neural57 = { weight: 0.393, bias: 0.450 };
var neural58 = { weight: 0.894, bias: 0.060 };
var neural59 = { weight: 0.573, bias: -0.386 };
var neural60 = { weight: -0.274, bias: -0.476 };
var neural61 = { weight: -0.870, bias: -0.129 };
var neural62 = { weight: -0.665, bias: 0.337 };
var neural63 = { weight: 0.151, bias: 0.493 };
var neural64 = { weight: 0.828, bias: 0.196 };
var neural65 = { weight: 0.744, bias: -0.281 };
var neural66 = { weight: -0.024, bias: -0.500 };
var neural67 = { weight: -0.770, bias: -0.259 };
var neural68 = { weight: -0.808, bias: 0.220 };
var neural69 = { weight: -0.103, bias: 0.497 };
var neural70 = { weight: 0.697, bias: 0.317 };
var neural71 = { weight: 0.856, bias: -0.155 };
var neural72 = { weight: 0.228, bias: -0.484 };
var neural73 = { weight: -0.609, bias: -0.368 };
var neural74 = { weight: -0.887, bias: 0.086 };
var neural75 = { weight: -0.349, bias: 0.461 };
var neural76 = { weight: 0.509, bias: 0.412 };
var neural77 = { weight: 0.900, bias: -0.015 };
var neural78 = { weight: 0.463, bias: -0.429 };
var neural79 = { weight: -0.400, bias: -0.448 };
fn layer_0(x: f32) -> f32 { x * 0.10 }
fn layer_1(x: f32) -> f32 { x * 0.12 }
fn layer_2(x: f32) -> f32 { x * 0.13 }
fn layer_3(x: f32) -> f32 { x * 0.15 }
fn layer_4(x: f32) -> f32 { x * 0.17 }
fn layer_5(x: f32) -> f32 { x * 0.18 }
fn layer_6(x: f32) -> f32 { x * 0.20 }
fn layer_7(x: f32) -> f32 { x * 0.22 }
fn layer_8(x: f32) -> f32 { x * 0.24 }
fn layer_9(x: f32) -> f32 { x * 0.25 }
fn layer_10(x: f32) -> f32 { x * 0.27 }
fn layer_11(x: f32) -> f32 { x * 0.29 }
fn layer_12(x: f32) -> f32 { x * 0.30 }
fn layer_13(x: f32) -> f32 { x * 0.32 }
fn layer_14(x: f32) -> f32 { x * 0.34 }
fn layer_15(x: f32) -> f32 { x * 0.35 }
fn layer_16(x: f32) -> f32 { x * 0.37 }
fn layer_17(x: f32) -> f32 { x * 0.39 }
fn layer_18(x: f32) -> f32 { x * 0.41 }
fn layer_19(x: f32) -> f32 { x * 0.42 }
fn layer_20(x: f32) -> f32 { x * 0.44 }
fn layer_21(x: f32) -> f32 { x * 0.46 }
fn layer_22(x: f32) -> f32 { x * 0.47 }
fn layer_23(x: f32) -> f32 { x * 0.49 }
fn layer_24(x: f32) -> f32 { x * 0.51 }
fn layer_25(x: f32) -> f32 { x * 0.53 }
fn layer_26(x: f32) -> f32 { x * 0.54 }
fn layer_27(x: f32) -> f32 { x * 0.56 }
fn layer_28(x: f32) -> f32 { x * 0.58 }
fn layer_29(x: f32) -> f32 { x * 0.59 }
fn layer_30(x: f32) -> f32 { x * 0.61 }
fn layer_31(x: f32) -> f32 { x * 0.63 }
fn layer_32(x: f32) -> f32 { x * 0.64 }
fn layer_33(x: f32) -> f32 { x * 0.66 }
fn layer_34(x: f32) -> f32 { x * 0.68 }
fn layer_35(x: f32) -> f32 { x * 0.70 }
fn layer_36(x: f32) -> f32 { x * 0.71 }
fn layer_37(x: f32) -> f32 { x * 0.73 }
fn layer_38(x: f32) -> f32 { x * 0.75 }
fn layer_39(x: f32) -> f32 { x * 0.76 }
fn layer_40(x: f32) -> f32 { x * 0.78 }
fn layer_41(x: f32) -> f32 { x * 0.80 }
fn layer_42(x: f32) -> f32 { x * 0.81 }
fn layer_43(x: f32) -> f32 { x * 0.83 }
fn layer_44(x: f32) -> f32 { x * 0.85 }
fn layer_45(x: f32) -> f32 { x * 0.86 }
fn layer_46(x: f32) -> f32 { x * 0.88 }
fn layer_47(x: f32) -> f32 { x * 0.90 }
fn layer_48(x: f32) -> f32 { x * 0.92 }
fn layer_49(x: f32) -> f32 { x * 0.93 }
fn layer_50(x: f32) -> f32 { x * 0.95 }
fn layer_51(x: f32) -> f32 { x * 0.97 }
fn layer_52(x: f32) -> f32 { x * 0.98 }
fn layer_53(x: f32) -> f32 { x * 1.00 }
fn layer_54(x: f32) -> f32 { x * 1.02 }
fn layer_55(x: f32) -> f32 { x * 1.04 }
fn layer_56(x: f32) -> f32 { x * 1.05 }
fn layer_57(x: f32) -> f32 { x * 1.07 }
fn layer_58(x: f32) -> f32 { x * 1.09 }
fn layer_59(x: f32) -> f32 { x * 1.10 }

AI Masterworks Generator

PROCESSING DATA... INTERPRETATION... GENERATION

1.

Prompt-Based Input

CLASSICAL ERA MASTERPIECES

CLASSICAL ERA
MASTERPIECES
CREATE CLASSICAL ARTText-to-Masterpiece Generation
2.

Era Transformation from Image Input

MODERN TIME SHIFTS

MODERN TIME
SHIFTS
REIMAGINE ERA ARTHistorical Figure Reinvention
3.

Simple Product Staging from Object Input

E-COMMERCE HERO SHOTS

E-COMMERCE
HERO SHOTS
ELEVATE PRODUCTSObject Staging & Environment Generation
4.

Multi-Image Fusion from Multiple Object Inputs

CROSSOVER & FUSION CONCEPTS

CROSSOVER &
FUSION CONCEPTS
FUSE CHARACTERSCharacter and Scene Fusion
Automate AI image generation and product photo workflows
Developer API

Automate AI image generation and product photo workflows

Connect PixMixAI to your webshop, CMS or internal toolchain. Generate stylish campaign visuals, improve low-quality product photos, replace backgrounds, create variations and scale creative production through a simple API.

Webshop product photo enhancement
Background replacement and studio staging
Bulk creative variations for ads and catalogs

Processing Data… Merging Images… Fusioning Styles… Generating Scene