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Vintage Street Scene with People Walking
Vintage Street Scene with People Walking
3 years ago

8 pm.

Creado hace 3 years ago · 9 comentarios· 0 Me gusta·🪙💰 5

Stable Diffusion 2.1Stable Diffusion 2.12x

#textured#open-prompt-gang#sd21-gang
Avatar de Vincent
Resumen de creación por Vincent

Vintage Street Scene with People Walking

A vibrant vintage-style image shows people walking on a road. The artwork features detailed brushstrokes, paint drips, and warm natural lighting, reminiscent of speed painting and matte painting techniques.

Creado por Kle00 el Jun 12, 2023 usando el modelo generador de imágenes de IA Stable Diffusion 2.1.


9 comentarios

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Tremendous! 🧡💦
2023-07-21T16:26:46.803ZReply
My favorite creation I've seen on NC in days!!
View replies (3)
Wonderful style… I feel nostalgia, when I look at this 🥰🥰

Configuraciones de Creación

Prompts de texto
People walking on a road, vintage style, beautiful complex detailed artwork by Armand Guillaumin : Carne Griffiths, Friedrich Nerly, Finnian MacManus, insanely detailed matte painting, vibrant natural colors, warm lighting, masterpiece, dripping paint, sharp focus
Weight: 1
People walking on a road, vintage style,, masterpiece, airbrush speedpainting, large brush strokes, paint drips, by jeremy mann, Adrian Ghenie, natural lighting, vibrant colors, sharp
Weight: 1.2
People walking on a road, vintage style, digital art, 8k highly detailed, highly detailed vector art, detailed portrait shot, side profile artwork, painting by dan mumford
Weight: 0.5
ugly, tiling, deformed, blurry, blurred, low resolution, amateur, dull, inspired by Giger, zoomed in
Weight: -0.7
ugly, tiling, poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, blurry, bad anatomy, blurred, watermark, grainy, signature, cut off, draft
Weight: -0.3
Modelo
Stable Diffusion 2.1
CKPT

Stable Diffusion 2.1

Resolución inicial

Low

Relación de aspecto

3:4

Tiempo de ejecución

Short

Peso global del Prompt

70%

Peso del Ruido

50%

Método de muestreo

K_DPMPP_2M


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