Contrast Low-medium Prompts

contrasting color palettes highlighting the interplay between light and dark, saturated and muted --ar 3:2 --v 6.0

raw photo, low contrast (portrait: 1.57), (dominican woman 48-years- old :1.15)

generatestrong contrast blue and yellow backlighting

by Yangjun Cheng, bw, by Rads and Lois van Baerle, bw, (((lineart))), 2bit, (vector graphics), clear, in focus, depth of field, (((lineart))),((low detail)),(simple), high contrast, clear, 2 bits,(((vector graphics))), (((linear drawing))), ((low detail)), (simple), high contrast, clear, 2 bits, (((vector graphics)))

sweater grey, open middle

light

Monochromatic contrast,woman, blue accents.

by Yangjun Cheng, (bw), by Rads and Lois van Baerle, ((bw)), (((lineart))), 2bit, (vector graphics), clear, in focus, depth of field, (((lineart))),((low detail)),(simple), high contrast, clear, 2 bits,(((vector graphics))), (((linear drawing))), ((low detail)), (simple), high contrast, clear, 2 bits, (((vector graphics)))

drab color

dark

isolated objects, 32k --v 5.2 --ar 2:3 --s 700 --q 2

bright color grading, muted color grading, rear projection

Repair contrast this photo

make contrast stronger and blacks darker

make contrast stronger and blacks darker

bright color grading, muted color grading, rear projection

bright color grading, muted color grading, rear projection

make contrast stronger and blacks darker

make contrast stronger and blacks darker

bright color grading, muted color grading, rear projection

clara::4 gradient background::4 gradient stripes::4 —ar 94:164 —uplight

flat, low contrast, oversaturated, underexposed, overexposed, blurred, noisy, (worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch) , tooth, dull, blurry, watermark, low quality, (flash:1.2) , black and white, makeup, candle r

shadow = np.array([0x11,0x10,0x0F], np.float32) # BGR of #0F1011 mid = np.array([0x55,0x7A,0x8E], np.float32) # #8E7A55 hi = np.array([0xA1,0xD2,0xE6], np.float32) # #E6D2A1 img = cv2.imread("input.jpg") g = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY).astype(np.float32)/255.0 g = g[...,None] t1 = np.clip(g/0.5, 0, 1) t2 = np.clip((g-0.5)/0.5, 0, 1) low = shadow*(1-t1) + mid*t1 high = mid*(1-t2) + hi*t2 out = np.where(g<=0.5, low, high).astype(np.uint8) cv2.imwrite("output_casinofi.png", out)

high contrast anime style, use exact image reference