set firstpass w/h to 0 by default and rever to old behavior when any are 0
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@ -501,17 +501,15 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
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class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
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sampler = None
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firstphase_width = 0
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firstphase_height = 0
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firstphase_width_truncated = 0
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firstphase_height_truncated = 0
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def __init__(self, enable_hr=False, denoising_strength=0.75, firstphase_width=512, firstphase_height=512, **kwargs):
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def __init__(self, enable_hr=False, denoising_strength=0.75, firstphase_width=0, firstphase_height=0, **kwargs):
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super().__init__(**kwargs)
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self.enable_hr = enable_hr
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self.denoising_strength = denoising_strength
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self.firstphase_width = firstphase_width
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self.firstphase_height = firstphase_height
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self.truncate_x = 0
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self.truncate_y = 0
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def init(self, all_prompts, all_seeds, all_subseeds):
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if self.enable_hr:
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@ -520,6 +518,32 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
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else:
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state.job_count = state.job_count * 2
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if self.firstphase_width == 0 or self.firstphase_height == 0:
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desired_pixel_count = 512 * 512
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actual_pixel_count = self.width * self.height
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scale = math.sqrt(desired_pixel_count / actual_pixel_count)
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self.firstphase_width = math.ceil(scale * self.width / 64) * 64
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self.firstphase_height = math.ceil(scale * self.height / 64) * 64
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firstphase_width_truncated = int(scale * self.width)
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firstphase_height_truncated = int(scale * self.height)
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else:
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self.extra_generation_params["First pass size"] = f"{self.firstphase_width}x{self.firstphase_height}"
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width_ratio = self.width / self.firstphase_width
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height_ratio = self.height / self.firstphase_height
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if width_ratio > height_ratio:
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firstphase_width_truncated = self.firstphase_width
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firstphase_height_truncated = self.firstphase_width * self.height / self.width
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else:
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firstphase_width_truncated = self.firstphase_height * self.width / self.height
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firstphase_height_truncated = self.firstphase_height
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self.truncate_x = int(self.firstphase_width - firstphase_width_truncated) // opt_f
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self.truncate_y = int(self.firstphase_height - firstphase_height_truncated) // opt_f
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def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength):
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self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, self.sampler_index, self.sd_model)
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@ -528,23 +552,10 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
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samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning)
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return samples
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self.extra_generation_params["First pass size"] = f"{self.firstphase_width}x{self.firstphase_height}"
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x = create_random_tensors([opt_C, self.firstphase_height // opt_f, self.firstphase_width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self)
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samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning)
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truncate_x = 0
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truncate_y = 0
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width_ratio = self.width/self.firstphase_width
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height_ratio = self.height/self.firstphase_height
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if width_ratio > height_ratio:
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truncate_y = int((self.width - self.firstphase_width) / width_ratio / height_ratio / opt_f)
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elif width_ratio < height_ratio:
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truncate_x = int((self.height - self.firstphase_height) / width_ratio / height_ratio / opt_f)
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samples = samples[:, :, truncate_y//2:samples.shape[2]-truncate_y//2, truncate_x//2:samples.shape[3]-truncate_x//2]
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samples = samples[:, :, self.truncate_y//2:samples.shape[2]-self.truncate_y//2, self.truncate_x//2:samples.shape[3]-self.truncate_x//2]
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decoded_samples = decode_first_stage(self.sd_model, samples)
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@ -567,8 +567,8 @@ def create_ui(wrap_gradio_gpu_call):
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enable_hr = gr.Checkbox(label='Highres. fix', value=False)
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with gr.Row(visible=False) as hr_options:
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firstphase_width = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass width", value=512)
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firstphase_height = gr.Slider(minimum=64, maximum=1024, step=64, label="First pass height", value=512)
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firstphase_width = gr.Slider(minimum=0, maximum=1024, step=64, label="First pass width", value=0)
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firstphase_height = gr.Slider(minimum=0, maximum=1024, step=64, label="First pass height", value=0)
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denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7)
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with gr.Row(equal_height=True):
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