made 'reuse seed' button give you the seed/subseed of the currently selected picture rather than the first

modules/processing.py

@@ -83,7 +83,7 @@ class StableDiffusionProcessing:
 
 
 class Processed:
-    def __init__(self, p: StableDiffusionProcessing, images_list, seed, info, subseed=None):
+    def __init__(self, p: StableDiffusionProcessing, images_list, seed=-1, info="", subseed=None, all_prompts=None, all_seeds=None, all_subseeds=None, index_of_first_image=0):
         self.images = images_list
         self.prompt = p.prompt
         self.negative_prompt = p.negative_prompt
@@ -93,26 +93,62 @@ class Processed:
         self.info = info
         self.width = p.width
         self.height = p.height
+        self.sampler_index = p.sampler_index
         self.sampler = samplers[p.sampler_index].name
         self.cfg_scale = p.cfg_scale
         self.steps = p.steps
+        self.batch_size = p.batch_size
+        self.restore_faces = p.restore_faces
+        self.face_restoration_model = opts.face_restoration_model if p.restore_faces else None
+        self.sd_model_hash = shared.sd_model.sd_model_hash
+        self.seed_resize_from_w = p.seed_resize_from_w
+        self.seed_resize_from_h = p.seed_resize_from_h
+        self.denoising_strength = getattr(p, 'denoising_strength', None)
+        self.extra_generation_params = p.extra_generation_params
+        self.index_of_first_image = index_of_first_image
+
+        self.prompt = self.prompt if type(self.prompt) != list else self.prompt[0]
+        self.negative_prompt = self.negative_prompt if type(self.negative_prompt) != list else self.negative_prompt[0]
+        self.seed = int(self.seed if type(self.seed) != list else self.seed[0])
+        self.subseed = int(self.subseed if type(self.subseed) != list else self.subseed[0]) if self.subseed is not None else -1
+
+        self.all_prompts = all_prompts or [self.prompt]
+        self.all_seeds = all_seeds or [self.seed]
+        self.all_subseeds = all_subseeds or [self.subseed]
 
     def js(self):
         obj = {
-            "prompt": self.prompt if type(self.prompt) != list else self.prompt[0],
+            "prompt": self.prompt,
-            "negative_prompt": self.negative_prompt if type(self.negative_prompt) != list else self.negative_prompt[0],
+            "all_prompts": self.all_prompts,
-            "seed": int(self.seed if type(self.seed) != list else self.seed[0]),
+            "negative_prompt": self.negative_prompt,
-            "subseed": int(self.subseed if type(self.subseed) != list else self.subseed[0]) if self.subseed is not None else -1,
+            "seed": self.seed,
+            "all_seeds": self.all_seeds,
+            "subseed": self.subseed,
+            "all_subseeds": self.all_subseeds,
             "subseed_strength": self.subseed_strength,
             "width": self.width,
             "height": self.height,
+            "sampler_index": self.sampler_index,
             "sampler": self.sampler,
             "cfg_scale": self.cfg_scale,
             "steps": self.steps,
+            "batch_size": self.batch_size,
+            "restore_faces": self.restore_faces,
+            "face_restoration_model": self.face_restoration_model,
+            "sd_model_hash": self.sd_model_hash,
+            "seed_resize_from_w": self.seed_resize_from_w,
+            "seed_resize_from_h": self.seed_resize_from_h,
+            "denoising_strength": self.denoising_strength,
+            "extra_generation_params": self.extra_generation_params,
+            "index_of_first_image": self.index_of_first_image,
         }
 
         return json.dumps(obj)
 
+    def infotext(self,  p: StableDiffusionProcessing, index):
+        return create_infotext(p, self.all_prompts, self.all_seeds, self.all_subseeds, comments=[], position_in_batch=index % self.batch_size, iteration=index // self.batch_size)
+
+
 # from https://discuss.pytorch.org/t/help-regarding-slerp-function-for-generative-model-sampling/32475/3
 def slerp(val, low, high):
     low_norm = low/torch.norm(low, dim=1, keepdim=True)
@@ -156,11 +192,9 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see
         noise = devices.randn(seed, noise_shape)
 
         if subnoise is not None:
-            #noise = subnoise * subseed_strength + noise * (1 - subseed_strength)
             noise = slerp(subseed_strength, noise, subnoise)
 
         if noise_shape != shape:
-            #noise = torch.nn.functional.interpolate(noise.unsqueeze(1), size=shape[1:], mode="bilinear").squeeze()
             x = devices.randn(seed, shape)
             dx = (shape[2] - noise_shape[2]) // 2
             dy = (shape[1] - noise_shape[1]) // 2
@@ -194,6 +228,35 @@ def fix_seed(p):
     p.subseed = int(random.randrange(4294967294)) if p.subseed is None or p.subseed == -1 else p.subseed
 
 
+def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration=0, position_in_batch=0):
+    index = position_in_batch + iteration * p.batch_size
+
+    generation_params = {
+        "Steps": p.steps,
+        "Sampler": samplers[p.sampler_index].name,
+        "CFG scale": p.cfg_scale,
+        "Seed": all_seeds[index],
+        "Face restoration": (opts.face_restoration_model if p.restore_faces else None),
+        "Size": f"{p.width}x{p.height}",
+        "Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash),
+        "Batch size": (None if p.batch_size < 2 else p.batch_size),
+        "Batch pos": (None if p.batch_size < 2 else position_in_batch),
+        "Variation seed": (None if p.subseed_strength == 0 else all_subseeds[index]),
+        "Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength),
+        "Seed resize from": (None if p.seed_resize_from_w == 0 or p.seed_resize_from_h == 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),
+        "Denoising strength": getattr(p, 'denoising_strength', None),
+    }
+
+    if p.extra_generation_params is not None:
+        generation_params.update(p.extra_generation_params)
+
+    generation_params_text = ", ".join([k if k == v else f'{k}: {v}' for k, v in generation_params.items() if v is not None])
+
+    negative_prompt_text = "\nNegative prompt: " + p.negative_prompt if p.negative_prompt else ""
+
+    return f"{all_prompts[index]}{negative_prompt_text}\n{generation_params_text}".strip() + "".join(["\n\n" + x for x in comments])
+
+
 def process_images(p: StableDiffusionProcessing) -> Processed:
     """this is the main loop that both txt2img and img2img use; it calls func_init once inside all the scopes and func_sample once per batch"""
 
@@ -231,32 +294,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
         all_subseeds = [int(p.subseed + x) for x in range(len(all_prompts))]
 
     def infotext(iteration=0, position_in_batch=0):
-        index = position_in_batch + iteration * p.batch_size
+        return create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration, position_in_batch)
-
-        generation_params = {
-            "Steps": p.steps,
-            "Sampler": samplers[p.sampler_index].name,
-            "CFG scale": p.cfg_scale,
-            "Seed": all_seeds[index],
-            "Face restoration": (opts.face_restoration_model if p.restore_faces else None),
-            "Size": f"{p.width}x{p.height}",
-            "Model hash": (None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash),
-            "Batch size": (None if p.batch_size < 2 else p.batch_size),
-            "Batch pos": (None if p.batch_size < 2 else position_in_batch),
-            "Variation seed": (None if p.subseed_strength == 0 else all_subseeds[index]),
-            "Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength),
-            "Seed resize from": (None if p.seed_resize_from_w == 0 or p.seed_resize_from_h == 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),
-            "Denoising strength": getattr(p, 'denoising_strength', None),
-        }
-
-        if p.extra_generation_params is not None:
-            generation_params.update(p.extra_generation_params)
-
-        generation_params_text = ", ".join([k if k == v else f'{k}: {v}' for k, v in generation_params.items() if v is not None])
-        
-        negative_prompt_text = "\nNegative prompt: " + p.negative_prompt if p.negative_prompt else ""
-
-        return f"{all_prompts[index]}{negative_prompt_text}\n{generation_params_text}".strip() + "".join(["\n\n" + x for x in comments])
 
     if os.path.exists(cmd_opts.embeddings_dir):
         model_hijack.load_textual_inversion_embeddings(cmd_opts.embeddings_dir, p.sd_model)
@@ -350,18 +388,20 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
 
         p.color_corrections = None
 
+        index_of_first_image = 0
         unwanted_grid_because_of_img_count = len(output_images) < 2 and opts.grid_only_if_multiple
         if (opts.return_grid or opts.grid_save) and not p.do_not_save_grid and not unwanted_grid_because_of_img_count:
             grid = images.image_grid(output_images, p.batch_size)
 
             if opts.return_grid:
                 output_images.insert(0, grid)
+                index_of_first_image = 1
 
             if opts.grid_save:
                 images.save_image(grid, p.outpath_grids, "grid", all_seeds[0], all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p)
 
     devices.torch_gc()
-    return Processed(p, output_images, all_seeds[0], infotext(), subseed=all_subseeds[0])
+    return Processed(p, output_images, all_seeds[0], infotext(), subseed=all_subseeds[0], all_prompts=all_prompts, all_seeds=all_seeds, all_subseeds=all_subseeds, index_of_first_image=index_of_first_image)
 
 
 class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):

modules/ui.py

@@ -297,53 +297,39 @@ def create_seed_inputs():
     return seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w
 
 
-def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: gr.Textbox):
+def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: gr.Textbox, dummy_component, is_subseed):
-    """ Connects a 'reuse seed' button's click event so that it copies last used
+    """ Connects a 'reuse (sub)seed' button's click event so that it copies last used
-        seed value from generation info the to the seed."""
+        (sub)seed value from generation info the to the seed field. If copying subseed and subseed strength
-    def copy_seed(gen_info_string: str):
-        try:
-            gen_info = json.loads(gen_info_string)
-            return gen_info.get('seed', -1)
-        except json.decoder.JSONDecodeError as e:
-            if gen_info_string != '':
-                print("Error parsing JSON generation info:", file=sys.stderr)
-                print(gen_info_string, file=sys.stderr)
-            return -1
-
-    reuse_seed.click(
-        fn=copy_seed,
-        show_progress=False,
-        inputs=[generation_info],
-        outputs=[seed]
-    )
-
-
-def connect_reuse_subseed(seed: gr.Number, reuse_seed: gr.Button, generation_info: gr.Textbox):
-    """ Connects a 'reuse subseed' button's click event so that it copies last used
-        subseed value from generation info the to the subseed. If subseed strength
         was 0, i.e. no variation seed was used, it copies the normal seed value instead."""
-    def copy_seed(gen_info_string: str):
+    def copy_seed(gen_info_string: str, index):
+        res = -1
+
         try:
             gen_info = json.loads(gen_info_string)
-            subseed_strength = gen_info.get('subseed_strength', 0)
+            index -= gen_info.get('index_of_first_image', 0)
-            if subseed_strength > 0:
+
-                return gen_info.get('subseed', -1)
+            if is_subseed and gen_info.get('subseed_strength', 0) > 0:
+                all_subseeds = gen_info.get('all_subseeds', [-1])
+                res = all_subseeds[index if 0 <= index < len(all_subseeds) else 0]
             else:
-                return gen_info.get('seed', -1)
+                all_seeds = gen_info.get('all_seeds', [-1])
+                res = all_seeds[index if 0 <= index < len(all_seeds) else 0]
+
         except json.decoder.JSONDecodeError as e:
             if gen_info_string != '':
                 print("Error parsing JSON generation info:", file=sys.stderr)
                 print(gen_info_string, file=sys.stderr)
-            return -1
+
+        return [res, gr_show(False)]
 
     reuse_seed.click(
         fn=copy_seed,
+        _js="(x, y) => [x, selected_gallery_index()]",
         show_progress=False,
-        inputs=[generation_info],
+        inputs=[generation_info, dummy_component],
-        outputs=[seed]
+        outputs=[seed, dummy_component]
     )
 
-
 def create_toprow(is_img2img):
     with gr.Row(elem_id="toprow"):
         with gr.Column(scale=4):
@@ -399,6 +385,7 @@ def setup_progressbar(progressbar, preview):
 def create_ui(txt2img, img2img, run_extras, run_pnginfo):
     with gr.Blocks(analytics_enabled=False) as txt2img_interface:
         txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, txt2img_prompt_style_apply, txt2img_save_style = create_toprow(is_img2img=False)
+        dummy_component = gr.Label(visible=False)
 
         with gr.Row().style(equal_height=False):
             with gr.Column(variant='panel'):
@@ -445,8 +432,8 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
                     html_info = gr.HTML()
                     generation_info = gr.Textbox(visible=False)
 
-            connect_reuse_seed(seed, reuse_seed, generation_info)
+            connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
-            connect_reuse_subseed(subseed, reuse_subseed, generation_info)
+            connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
 
             txt2img_args = dict(
                 fn=txt2img,
@@ -487,11 +474,11 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
 
             save.click(
                 fn=wrap_gradio_call(save_files),
-                _js = "(x, y, z) => [x, y, selected_gallery_index()]",
+                _js="(x, y, z) => [x, y, selected_gallery_index()]",
                 inputs=[
                     generation_info,
                     txt2img_gallery,
-                    html_info
+                    html_info,
                 ],
                 outputs=[
                     html_info,
@@ -583,8 +570,8 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
                     html_info = gr.HTML()
                     generation_info = gr.Textbox(visible=False)
 
-            connect_reuse_seed(seed, reuse_seed, generation_info)
+            connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
-            connect_reuse_subseed(subseed, reuse_subseed, generation_info)
+            connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
 
             def apply_mode(mode, uploadmask):
                 is_classic = mode == 0
@@ -723,7 +710,6 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
             prompts = [(txt2img_prompt, txt2img_negative_prompt), (img2img_prompt, img2img_negative_prompt)]
             style_dropdowns = [(txt2img_prompt_style, txt2img_prompt_style2), (img2img_prompt_style, img2img_prompt_style2)]
 
-            dummy_component = gr.Label(visible=False)
             for button, (prompt, negative_prompt) in zip([txt2img_save_style, img2img_save_style], prompts):
                 button.click(
                     fn=add_style,