Version: v2.0
Input
Output
This example was created by evevalentine2017
Finished in 91.0 seconds
Setting up the model...
Preparing inputs...
Processing...
Loading VAE weight: models/VAE/sdxl_vae.safetensors
Full prompt: Cinematic, epic, professional photography, maximum hyperrealism, photorealism, action packed, portrait of a 33 year old british man with long chesnut hair and a detailed beard, green eyes, (bags under eyes, and a tired, old look on his face), detailed eyes, detailed iris, expressive face, expressive eyes, (realistic face, perfect eyes, perfect face:1.1), 16K, high quality, photorealistic, realism, art photography, Nikon D850, 16k, sharp focus, masterpiece, breathtaking, atmospheric perspective, diffusion, pore correlation, skin imperfections, DSLR, 80mm Sigma f2, depth of field, intricate natural lighting, film grain, background Cinematic Hollywood Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy, OverallDetail, <lora:add-detail-xl:1.0>
Full negative prompt: cartoon, anime, render, cg, 3D, desaturated, text, watermark, low-quality, signature, moir pattern, downsampling, aliasing, distorted, blurry, glossy, blur, jpeg artifacts, compression artifacts, poorly drawn, low-resolution, bad, distortion, twisted, excessive, exaggerated pose, exaggerated limbs, grainy, symmetrical, duplicate, error, pattern, beginner, pixelated, fake, hyper, glitch, overexposed, high-contrast, bad-contrast, epiCNegative
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Decoding latents in cuda:0...
done in 1.76s
Move latents to cpu...
done in 0.02s
0: 640x480 1 face, 170.9ms
Speed: 2.8ms preprocess, 170.9ms inference, 27.8ms postprocess per image at shape (1, 3, 640, 480)
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Decoding latents in cuda:0...
done in 0.56s
Move latents to cpu...
done in 0.0s
0: 640x480 1 face, 10.2ms
Speed: 2.6ms preprocess, 10.2ms inference, 1.8ms postprocess per image at shape (1, 3, 640, 480)
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Decoding latents in cuda:0...
done in 0.56s
Move latents to cpu...
done in 0.0s
0: 640x480 1 face, 8.4ms
Speed: 2.5ms preprocess, 8.4ms inference, 1.4ms postprocess per image at shape (1, 3, 640, 480)
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Decoding latents in cuda:0...
done in 0.56s
Move latents to cpu...
done in 0.0s
Uploading outputs...
Finished.
This example was created by evevalentine2017
Finished in 91.0 seconds
Setting up the model...
Preparing inputs...
Processing...
Loading VAE weight: models/VAE/sdxl_vae.safetensors
Full prompt: Cinematic, epic, professional photography, maximum hyperrealism, photorealism, action packed, portrait of a 33 year old british man with long chesnut hair and a detailed beard, green eyes, (bags under eyes, and a tired, old look on his face), detailed eyes, detailed iris, expressive face, expressive eyes, (realistic face, perfect eyes, perfect face:1.1), 16K, high quality, photorealistic, realism, art photography, Nikon D850, 16k, sharp focus, masterpiece, breathtaking, atmospheric perspective, diffusion, pore correlation, skin imperfections, DSLR, 80mm Sigma f2, depth of field, intricate natural lighting, film grain, background Cinematic Hollywood Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy, OverallDetail, <lora:add-detail-xl:1.0>
Full negative prompt: cartoon, anime, render, cg, 3D, desaturated, text, watermark, low-quality, signature, moir pattern, downsampling, aliasing, distorted, blurry, glossy, blur, jpeg artifacts, compression artifacts, poorly drawn, low-resolution, bad, distortion, twisted, excessive, exaggerated pose, exaggerated limbs, grainy, symmetrical, duplicate, error, pattern, beginner, pixelated, fake, hyper, glitch, overexposed, high-contrast, bad-contrast, epiCNegative
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Decoding latents in cuda:0...
done in 1.76s
Move latents to cpu...
done in 0.02s
0: 640x480 1 face, 170.9ms
Speed: 2.8ms preprocess, 170.9ms inference, 27.8ms postprocess per image at shape (1, 3, 640, 480)
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Decoding latents in cuda:0...
done in 0.56s
Move latents to cpu...
done in 0.0s
0: 640x480 1 face, 10.2ms
Speed: 2.6ms preprocess, 10.2ms inference, 1.8ms postprocess per image at shape (1, 3, 640, 480)
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Decoding latents in cuda:0...
done in 0.56s
Move latents to cpu...
done in 0.0s
0: 640x480 1 face, 8.4ms
Speed: 2.5ms preprocess, 8.4ms inference, 1.4ms postprocess per image at shape (1, 3, 640, 480)
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Decoding latents in cuda:0...
done in 0.56s
Move latents to cpu...
done in 0.0s
Uploading outputs...
Finished.