forked from extern/easydiffusion
118 lines
3.7 KiB
Python
118 lines
3.7 KiB
Python
import json
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class Request:
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session_id: str = "session"
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prompt: str = ""
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negative_prompt: str = ""
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init_image: str = None # base64
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mask: str = None # base64
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num_outputs: int = 1
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num_inference_steps: int = 50
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guidance_scale: float = 7.5
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width: int = 512
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height: int = 512
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seed: int = 42
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prompt_strength: float = 0.8
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sampler: str = None # "ddim", "plms", "heun", "euler", "euler_a", "dpm2", "dpm2_a", "lms"
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# allow_nsfw: bool = False
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precision: str = "autocast" # or "full"
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save_to_disk_path: str = None
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turbo: bool = True
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use_full_precision: bool = False
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use_face_correction: str = None # or "GFPGANv1.3"
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use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B"
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use_stable_diffusion_model: str = "sd-v1-4"
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use_vae_model: str = None
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use_hypernetwork_model: str = None
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hypernetwork_strength: float = 1
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show_only_filtered_image: bool = False
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output_format: str = "jpeg" # or "png"
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output_quality: int = 75
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stream_progress_updates: bool = False
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stream_image_progress: bool = False
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def json(self):
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return {
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"session_id": self.session_id,
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"prompt": self.prompt,
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"negative_prompt": self.negative_prompt,
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"num_outputs": self.num_outputs,
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"num_inference_steps": self.num_inference_steps,
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"guidance_scale": self.guidance_scale,
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"width": self.width,
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"height": self.height,
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"seed": self.seed,
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"prompt_strength": self.prompt_strength,
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"sampler": self.sampler,
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"use_face_correction": self.use_face_correction,
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"use_upscale": self.use_upscale,
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"use_stable_diffusion_model": self.use_stable_diffusion_model,
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"use_vae_model": self.use_vae_model,
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"use_hypernetwork_model": self.use_hypernetwork_model,
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"hypernetwork_strength": self.hypernetwork_strength,
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"output_format": self.output_format,
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"output_quality": self.output_quality,
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}
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def __str__(self):
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return f'''
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session_id: {self.session_id}
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prompt: {self.prompt}
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negative_prompt: {self.negative_prompt}
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seed: {self.seed}
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num_inference_steps: {self.num_inference_steps}
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sampler: {self.sampler}
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guidance_scale: {self.guidance_scale}
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w: {self.width}
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h: {self.height}
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precision: {self.precision}
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save_to_disk_path: {self.save_to_disk_path}
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turbo: {self.turbo}
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use_full_precision: {self.use_full_precision}
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use_face_correction: {self.use_face_correction}
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use_upscale: {self.use_upscale}
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use_stable_diffusion_model: {self.use_stable_diffusion_model}
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use_vae_model: {self.use_vae_model}
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use_hypernetwork_model: {self.use_hypernetwork_model}
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hypernetwork_strength: {self.hypernetwork_strength}
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show_only_filtered_image: {self.show_only_filtered_image}
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output_format: {self.output_format}
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output_quality: {self.output_quality}
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stream_progress_updates: {self.stream_progress_updates}
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stream_image_progress: {self.stream_image_progress}'''
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class Image:
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data: str # base64
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seed: int
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is_nsfw: bool
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path_abs: str = None
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def __init__(self, data, seed):
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self.data = data
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self.seed = seed
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def json(self):
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return {
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"data": self.data,
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"seed": self.seed,
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"path_abs": self.path_abs,
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}
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class Response:
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request: Request
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images: list
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def json(self):
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res = {
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"status": 'succeeded',
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"request": self.request.json(),
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"output": [],
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}
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for image in self.images:
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res["output"].append(image.json())
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return res
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