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https://github.com/vladmandic/automatic
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Executable
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#!/bin/env python
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import io
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import json
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import base64
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import logging
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from PIL import Image
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from util import Map, log
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from sdapi import postsync
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template = 'photo of "{name}", {suffix}, high detailed, skin texture, facing camera, 135mm, shot on dslr, 4k, modelshoot style'
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opt = {
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'prompt': None,
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'negative_prompt': '',
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'init_images': [],
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'sampler_name': 'DPM2 Karras',
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'batch_size': 1,
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'n_iter': 1,
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'steps': 30,
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'cfg_scale': 6,
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'width': 512,
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'height': 512,
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'restore_faces': False
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}
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def encode(f):
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img = Image.open(f)
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with io.BytesIO() as stream:
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img.save(stream, 'JPEG')
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values = stream.getvalue()
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encoded = base64.b64encode(values).decode()
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return encoded
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def img2img(name: str, suffix: str):
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opt['prompt'] = template.format(name = name, suffix = suffix)
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log.info({ 'preview prompt': opt['prompt'] })
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log.info({ 'preview options': opt })
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opt['init_images'].append(encode('sillouethe.jpg'))
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data = postsync('/sdapi/v1/img2img', opt)
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if 'error' in data:
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log.error({ 'preview': data['error'], 'reason': data['reason'] })
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return
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info = Map(json.loads(data['info']))
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log.debug({ 'preview info': info })
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if not 'images' in data:
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log.error({ 'preview': 'no images' })
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return
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obj = data.copy()
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del obj['images']
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log.info({ 'preview response': obj })
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for b64 in data['images']:
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image = Image.open(io.BytesIO(base64.b64decode(b64.split(",",1)[0])))
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image.save('test.jpg')
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if __name__ == "__main__":
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# log.setLevel(logging.DEBUG)
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log.info({ 'preview': 'start' })
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img2img('hanna', 'person, woman, girl, model')
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