update hdr

modules/processing.py

@@ -121,7 +121,7 @@ class StableDiffusionProcessing:
     """
     The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing
     """
-    def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, latent_sampler: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, image_cfg_scale: float = None, clip_skip: int = 1, width: int = 512, height: int = 512, full_quality: bool = True, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, diffusers_guidance_rescale: float = 0.7, hdr_clamp: bool = False, hdr_boundary: float = 4.0, hdr_threshold: float = 3.5, hdr_center: bool = False, hdr_channel_shift: float = 0.8, hdr_full_shift: float = 0.8, hdr_maximize: bool = False, hdr_max_boundry: float = 4.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None): # pylint: disable=unused-argument
+    def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, latent_sampler: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, image_cfg_scale: float = None, clip_skip: int = 1, width: int = 512, height: int = 512, full_quality: bool = True, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, diffusers_guidance_rescale: float = 0.7, hdr_clamp: bool = False, hdr_boundary: float = 4.0, hdr_threshold: float = 3.5, hdr_center: bool = False, hdr_channel_shift: float = 0.8, hdr_full_shift: float = 0.8, hdr_maximize: bool = False, hdr_max_center: float = 0.6, hdr_max_boundry: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None): # pylint: disable=unused-argument
 
         self.outpath_samples: str = outpath_samples
         self.outpath_grids: str = outpath_grids
@@ -211,6 +211,7 @@ class StableDiffusionProcessing:
         self.hdr_channel_shift = hdr_channel_shift
         self.hdr_full_shift = hdr_full_shift
         self.hdr_maximize = hdr_maximize
+        self.hdr_max_center = hdr_max_center
         self.hdr_max_boundry = hdr_max_boundry
 
 

modules/processing_correction.py

@@ -11,11 +11,12 @@ from modules import shared
 debug = shared.log.info if os.environ.get('SD_HDR_DEBUG', None) is not None else lambda *args, **kwargs: None
 
 
-def soft_clamp_tensor(input_tensor, threshold=3.5, boundary=4):
+def soft_clamp_tensor(input_tensor, threshold=0.8, boundary=4):
     # shrinking towards the mean; will also remove outliers
-    if max(abs(input_tensor.max()), abs(input_tensor.min())) < 4:
+    if max(abs(input_tensor.max()), abs(input_tensor.min())) < boundary or threshold == 0:
         return input_tensor
     channel_dim = 1
+    threshold *= boundary
     max_vals = input_tensor.max(channel_dim, keepdim=True)[0]
     max_replace = ((input_tensor - threshold) / (max_vals - threshold)) * (boundary - threshold) + threshold
     over_mask = input_tensor > threshold
@@ -23,21 +24,26 @@ def soft_clamp_tensor(input_tensor, threshold=3.5, boundary=4):
     min_replace = ((input_tensor + threshold) / (min_vals + threshold)) * (-boundary + threshold) - threshold
     under_mask = input_tensor < -threshold
     debug(f'HDE soft clamp: threshold={threshold} boundary={boundary}')
-    res = torch.where(over_mask, max_replace, torch.where(under_mask, min_replace, input_tensor))
-    return res
+    input_tensor = torch.where(over_mask, max_replace, torch.where(under_mask, min_replace, input_tensor))
+    return input_tensor
 
 
 def center_tensor(input_tensor, channel_shift=1.0, full_shift=1.0, channels=[0, 1, 2, 3]):
+    if channel_shift == 0 and full_shift == 0:
+        return input_tensor
     means = []
     for channel in channels:
         means.append(input_tensor[0, channel].mean())
         input_tensor[0, channel] -= means[-1] * channel_shift
     debug(f'HDR center: channel-shift{channel_shift} full-shift={full_shift} means={torch.stack(means)}')
-    res = input_tensor - input_tensor.mean() * full_shift
-    return res
+    input_tensor = input_tensor - input_tensor.mean() * full_shift
+    return input_tensor
 
 
-def maximize_tensor(input_tensor, boundary=4.0, channels=[0, 1, 2]):
+def maximize_tensor(input_tensor, boundary=1.0, channels=[0, 1, 2]):
+    if boundary == 1.0:
+        return input_tensor
+    boundary *= 4
     min_val = input_tensor.min()
     max_val = input_tensor.max()
     normalization_factor = boundary / max(abs(min_val), abs(max_val))
@@ -52,6 +58,6 @@ def correction_callback(p, timestep, kwags):
     if timestep > 700 and p.hdr_center:
         kwags["latents"] = center_tensor(kwags["latents"], channel_shift=p.hdr_channel_shift, full_shift=p.hdr_full_shift)
     if timestep > 1 and timestep < 100 and p.hdr_maximize:
-        kwags["latents"] = center_tensor(kwags["latents"], channel_shift=0.6, full_shift=1.0)
+        kwags["latents"] = center_tensor(kwags["latents"], channel_shift=p.hdr_max_center, full_shift=1.0)
         kwags["latents"] = maximize_tensor(kwags["latents"], boundary=p.hdr_max_boundry)
     return kwags

modules/processing_diffusers.py

@@ -346,6 +346,12 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
         clean['generator'] = generator_device
         clean['parser'] = parser
         shared.log.debug(f'Diffuser pipeline: {model.__class__.__name__} task={sd_models.get_diffusers_task(model)} set={clean}')
+        if p.hdr_clamp or p.hdr_center or p.hdr_maximize:
+            txt = 'HDR:'
+            txt += f' Clamp threshold={p.hdr_threshold} boundary={p.hdr_boundary}' if p.hdr_clamp else 'Clamp off'
+            txt += f' Center channel-shift={p.hdr_channel_shift} full-shift={p.hdr_full_shift}' if p.hdr_center else 'Center off'
+            txt += f' Maximize boundary={p.hdr_max_boundry} center={p.hdr_max_center}' if p.hdr_maximize else 'Maximize off'
+            shared.log.debug(txt)
         # components = [{ k: getattr(v, 'device', None) } for k, v in model.components.items()]
         # shared.log.debug(f'Diffuser pipeline components: {components}')
         return args

modules/txt2img.py

@@ -4,7 +4,7 @@ from modules.generation_parameters_copypaste import create_override_settings_dic
 from modules.ui import plaintext_to_html
 
 
-def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, latent_index: int, full_quality: bool, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, diffusers_guidance_rescale: float, clip_skip: int, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_force: bool, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, refiner_steps: int, refiner_start: int, refiner_prompt: str, refiner_negative: str, hdr_clamp, hdr_boundary, hdr_threshold, hdr_center, hdr_channel_shift, hdr_full_shift, hdr_maximize, hdr_max_boundry, override_settings_texts, *args): # pylint: disable=unused-argument
+def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, latent_index: int, full_quality: bool, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, diffusers_guidance_rescale: float, clip_skip: int, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_force: bool, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, refiner_steps: int, refiner_start: int, refiner_prompt: str, refiner_negative: str, hdr_clamp, hdr_boundary, hdr_threshold, hdr_center, hdr_channel_shift, hdr_full_shift, hdr_maximize, hdr_max_center, hdr_max_boundry, override_settings_texts, *args): # pylint: disable=unused-argument
 
     shared.log.debug(f'txt2img: id_task={id_task}|prompt={prompt}|negative_prompt={negative_prompt}|prompt_styles={prompt_styles}|steps={steps}|sampler_index={sampler_index}|latent_index={latent_index}|full_quality={full_quality}|restore_faces={restore_faces}|tiling={tiling}|n_iter={n_iter}|batch_size={batch_size}|cfg_scale={cfg_scale}|clip_skip={clip_skip}|seed={seed}|subseed={subseed}|subseed_strength={subseed_strength}|seed_resize_from_h={seed_resize_from_h}|seed_resize_from_w={seed_resize_from_w}||height={height}|width={width}|enable_hr={enable_hr}|denoising_strength={denoising_strength}|hr_scale={hr_scale}|hr_upscaler={hr_upscaler}|hr_force={hr_force}|hr_second_pass_steps={hr_second_pass_steps}|hr_resize_x={hr_resize_x}|hr_resize_y={hr_resize_y}|image_cfg_scale={image_cfg_scale}|diffusers_guidance_rescale={diffusers_guidance_rescale}|refiner_steps={refiner_steps}|refiner_start={refiner_start}|refiner_prompt={refiner_prompt}|refiner_negative={refiner_negative}|override_settings_texts={override_settings_texts}')
 
@@ -59,7 +59,7 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step
         refiner_negative=refiner_negative,
         hdr_clamp=hdr_clamp, hdr_boundary=hdr_boundary, hdr_threshold=hdr_threshold,
         hdr_center=hdr_center, hdr_channel_shift=hdr_channel_shift, hdr_full_shift=hdr_full_shift,
-        hdr_maximize=hdr_maximize, hdr_max_boundry=hdr_max_boundry,
+        hdr_maximize=hdr_maximize, hdr_max_center=hdr_max_center, hdr_max_boundry=hdr_max_boundry,
         override_settings=override_settings,
     )
     p.scripts = modules.scripts.scripts_txt2img

modules/ui.py

@@ -417,27 +417,31 @@ def create_ui(startup_timer = None):
                     seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w = create_seed_inputs('txt2img')
 
                     with gr.Accordion(open=False, label="Advanced", elem_id="txt2img_advanced", elem_classes=["small-accordion"]):
-                        with FormRow():
-                            cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.1, label='CFG scale', value=6.0, elem_id="txt2img_cfg_scale")
-                            clip_skip = gr.Slider(label='CLIP skip', value=1, minimum=1, maximum=14, step=1, elem_id='txt2img_clip_skip', interactive=True)
-                        with FormRow():
-                            image_cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.1, label='Secondary CFG scale', value=6.0, elem_id="txt2img_image_cfg_scale")
-                            diffusers_guidance_rescale = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Guidance rescale', value=0.7, elem_id="txt2img_image_cfg_rescale")
-                        with FormRow():
-                            full_quality = gr.Checkbox(label='Full quality', value=True, elem_id="txt2img_full_quality")
-                            restore_faces = gr.Checkbox(label='Face restore', value=False, visible=len(modules.shared.face_restorers) > 1, elem_id="txt2img_restore_faces")
-                            tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")
-                        with FormRow():
-                            hdr_clamp = gr.Checkbox(label='HDR clamp', value=False, elem_id="txt2img_hdr_clamp")
-                            hdr_boundary = gr.Slider(minimum=0.0, maximum=10.0, step=0.1, value=4.0,  label='Range', elem_id="txt2img_hdr_boundary")
-                            hdr_threshold = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.95,  label='Threshold', elem_id="txt2img_hdr_threshold")
-                        with FormRow():
-                            hdr_center = gr.Checkbox(label='HDR center', value=False, elem_id="txt2img_hdr_center")
-                            hdr_channel_shift = gr.Slider(minimum=0.0, maximum=2.0, step=0.1, value=1.0,  label='Channel shift', elem_id="txt2img_hdr_channel_shift")
-                            hdr_full_shift = gr.Slider(minimum=0.0, maximum=2.0, step=0.1, value=1,  label='Full shift', elem_id="txt2img_hdr_full_shift")
-                        with FormRow():
-                            hdr_maximize = gr.Checkbox(label='HDR maximize', value=False, elem_id="txt2img_hdr_maximize")
-                            hdr_max_boundry = gr.Slider(minimum=0.0, maximum=10.0, step=0.1, value=4.0,  label='range', elem_id="txt2img_hdr_max_boundry")
+                        with gr.Group():
+                            with FormRow():
+                                cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.1, label='CFG scale', value=6.0, elem_id="txt2img_cfg_scale")
+                                clip_skip = gr.Slider(label='CLIP skip', value=1, minimum=1, maximum=14, step=1, elem_id='txt2img_clip_skip', interactive=True)
+                            with FormRow():
+                                image_cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.1, label='Secondary CFG scale', value=6.0, elem_id="txt2img_image_cfg_scale")
+                                diffusers_guidance_rescale = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Guidance rescale', value=0.7, elem_id="txt2img_image_cfg_rescale")
+                        with gr.Group():
+                            with FormRow():
+                                full_quality = gr.Checkbox(label='Full quality', value=True, elem_id="txt2img_full_quality")
+                                restore_faces = gr.Checkbox(label='Face restore', value=False, visible=len(modules.shared.face_restorers) > 1, elem_id="txt2img_restore_faces")
+                                tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")
+                        with gr.Group():
+                            with FormRow():
+                                hdr_clamp = gr.Checkbox(label='HDR clamp', value=False, elem_id="txt2img_hdr_clamp")
+                                hdr_boundary = gr.Slider(minimum=0.0, maximum=10.0, step=0.1, value=4.0,  label='Range', elem_id="txt2img_hdr_boundary")
+                                hdr_threshold = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.95,  label='Threshold', elem_id="txt2img_hdr_threshold")
+                            with FormRow():
+                                hdr_center = gr.Checkbox(label='HDR center', value=False, elem_id="txt2img_hdr_center")
+                                hdr_channel_shift = gr.Slider(minimum=0.0, maximum=2.0, step=0.1, value=1.0,  label='Channel shift', elem_id="txt2img_hdr_channel_shift")
+                                hdr_full_shift = gr.Slider(minimum=0.0, maximum=2.0, step=0.1, value=1,  label='Full shift', elem_id="txt2img_hdr_full_shift")
+                            with FormRow():
+                                hdr_maximize = gr.Checkbox(label='HDR maximize', value=False, elem_id="txt2img_hdr_maximize")
+                                hdr_max_center = gr.Slider(minimum=0.0, maximum=2.0, step=0.1, value=0.6,  label='Center', elem_id="txt2img_hdr_max_center")
+                                hdr_max_boundry = gr.Slider(minimum=0.5, maximum=2.0, step=0.1, value=1.0,  label='Range', elem_id="txt2img_hdr_max_boundry")
 
                     with gr.Accordion(open=False, label="Second pass", elem_id="txt2img_second_pass", elem_classes=["small-accordion"]):
                         with FormGroup():
@@ -504,7 +508,7 @@ def create_ui(startup_timer = None):
                     enable_hr, denoising_strength,
                     hr_scale, hr_upscaler, hr_force, hr_second_pass_steps, hr_resize_x, hr_resize_y,
                     refiner_steps, refiner_start, refiner_prompt, refiner_negative,
-                    hdr_clamp, hdr_boundary, hdr_threshold, hdr_center, hdr_channel_shift, hdr_full_shift, hdr_maximize, hdr_max_boundry,
+                    hdr_clamp, hdr_boundary, hdr_threshold, hdr_center, hdr_channel_shift, hdr_full_shift, hdr_maximize, hdr_max_center, hdr_max_boundry,
                     override_settings,
                 ] + custom_inputs,
                 outputs=[

scripts/xyz_grid.py

@@ -261,6 +261,7 @@ axis_options = [
     AxisOption("[HDR] Clamp threshold", float, apply_field("hdr_threshold")),
     AxisOption("[HDR] Center channel shift", float, apply_field("hdr_channel_shift")),
     AxisOption("[HDR] Center full shift", float, apply_field("hdr_full_shift")),
+    AxisOption("[HDR] Maximize center shift", float, apply_field("hdr_max_center")),
     AxisOption("[HDR] Maximize boundary", float, apply_field("hdr_max_boundry")),
     AxisOption("[ToMe] Token merging ratio (txt2img)", float, apply_override('token_merging_ratio')),
     AxisOption("[ToMe] Token merging ratio (hires)", float, apply_override('token_merging_ratio_hr')),