Version: v3.0
Input
Output
This example was created by evevalentine2017
Finished in 555.6 seconds
Setting up the model...
Preparing inputs...
Processing...
Full prompt: cinematic film still, a female soldier, wearing an military fatigues with a helmet, tactical gear, standing in a military base ,look up, serious expression, depth of field, telephoto lens, short hair,profile,looking up,(full body focus),half closed-eyes, central composition, soldiers in the background, .shallow depth of field, highly detailed, high budget, bokeh, cinemascope, depressing, epic, gorgeous, film grain, grainy,
Full negative prompt: ((horse head:2)), fire, light, day, sunny, bad anatomy, bad proportions, ugly face, poorly drawn face, bad hands, blurry, cropped, error, extra digit, fewer digits, jpeg artifacts, lowres, low quality, missing arms, missing fingers, missing fingers, normal quality, signature, text, username, watermark, worst quality
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Decoding latents in cuda:0...
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0: 640x640 3 faces, 7.7ms
Speed: 3.6ms preprocess, 7.7ms inference, 24.0ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
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0: 640x640 1 hand, 7.2ms
Speed: 3.1ms preprocess, 7.2ms inference, 1.9ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
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0: 640x640 3 faces, 7.7ms
Speed: 3.1ms preprocess, 7.7ms inference, 1.6ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
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0: 640x640 (no detections), 7.6ms
Speed: 3.1ms preprocess, 7.6ms inference, 0.8ms postprocess per image at shape (1, 3, 640, 640)
[-] ADetailer: nothing detected on image 2 with 2nd settings.
0: 640x640 3 faces, 8.1ms
Speed: 3.0ms preprocess, 8.1ms inference, 1.5ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
done in 0.79s
Move latents to cpu...
done in 0.0s
0: 640x640 (no detections), 7.0ms
Speed: 3.2ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 640, 640)
[-] ADetailer: nothing detected on image 3 with 2nd settings.
Uploading outputs...
Finished.
This example was created by evevalentine2017
Finished in 555.6 seconds
Setting up the model...
Preparing inputs...
Processing...
Full prompt: cinematic film still, a female soldier, wearing an military fatigues with a helmet, tactical gear, standing in a military base ,look up, serious expression, depth of field, telephoto lens, short hair,profile,looking up,(full body focus),half closed-eyes, central composition, soldiers in the background, .shallow depth of field, highly detailed, high budget, bokeh, cinemascope, depressing, epic, gorgeous, film grain, grainy,
Full negative prompt: ((horse head:2)), fire, light, day, sunny, bad anatomy, bad proportions, ugly face, poorly drawn face, bad hands, blurry, cropped, error, extra digit, fewer digits, jpeg artifacts, lowres, low quality, missing arms, missing fingers, missing fingers, normal quality, signature, text, username, watermark, worst quality
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Decoding latents in cuda:0...
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Move latents to cpu...
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0: 640x640 3 faces, 7.7ms
Speed: 3.6ms preprocess, 7.7ms inference, 24.0ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
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0: 640x640 1 hand, 7.2ms
Speed: 3.1ms preprocess, 7.2ms inference, 1.9ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
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0: 640x640 3 faces, 7.7ms
Speed: 3.1ms preprocess, 7.7ms inference, 1.6ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
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0: 640x640 (no detections), 7.6ms
Speed: 3.1ms preprocess, 7.6ms inference, 0.8ms postprocess per image at shape (1, 3, 640, 640)
[-] ADetailer: nothing detected on image 2 with 2nd settings.
0: 640x640 3 faces, 8.1ms
Speed: 3.0ms preprocess, 8.1ms inference, 1.5ms postprocess per image at shape (1, 3, 640, 640)
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89%|████████▉ | 17/19 [00:31<00:03, 1.73s/it]
95%|█████████▍| 18/19 [00:32<00:01, 1.67s/it]
100%|██████████| 19/19 [00:33<00:00, 1.35s/it]
100%|██████████| 19/19 [00:33<00:00, 1.77s/it]
Decoding latents in cuda:0...
done in 0.79s
Move latents to cpu...
done in 0.0s
0: 640x640 (no detections), 7.0ms
Speed: 3.2ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 640, 640)
[-] ADetailer: nothing detected on image 3 with 2nd settings.
Uploading outputs...
Finished.