output directory options

1 files changed, 49 insertions, 29 deletions

diff --git a/webui.py b/webui.py
index 6c5eafb2..a6704bd4 100644
--- a/webui.py
+++ b/webui.py
@@ -36,6 +36,7 @@ from collections import namedtuple
 from contextlib import nullcontext

 import signal

 import tqdm

+import re

 

 import k_diffusion.sampling

 from ldm.util import instantiate_from_config

@@ -187,7 +188,14 @@ class Options:
 

     data = None

     data_labels = {

-        "outdir": OptionInfo("", "Output dictectory; if empty, defaults to 'outputs/*'"),

+        "outdir_samples": OptionInfo("", "Output dictectory for images; if empty, defaults to two directories below"),

+        "outdir_txt2img_samples": OptionInfo("outputs/txt2img-images", 'Output dictectory for txt2img images'),

+        "outdir_img2img_samples": OptionInfo("outputs/img2img-images", 'Output dictectory for img2img images'),

+        "outdir_grids": OptionInfo("", "Output dictectory for grids; if empty, defaults to two directories below"),

+        "outdir_txt2img_grids": OptionInfo("outputs/txt2img-grids", 'Output dictectory for txt2img grids'),

+        "outdir_img2img_grids": OptionInfo("outputs/img2img-grids", 'Output dictectory for img2img grids'),

+        "save_to_dirs": OptionInfo(False, "When writing images/grids, create a directory with name derived from the prompt"),

+        "save_to_dirs_prompt_len": OptionInfo(10, "When using above, how many words from prompt to put into directory name", gr.Slider, {"minimum": 1, "maximum": 32, "step": 1}),

         "samples_save": OptionInfo(True, "Save indiviual samples"),

         "samples_format": OptionInfo('png', 'File format for indiviual samples'),

         "grid_save": OptionInfo(True, "Save image grids"),

@@ -342,11 +350,12 @@ def torch_gc():
 

 

 def save_image(image, path, basename, seed=None, prompt=None, extension='png', info=None, short_filename=False):

-

     if short_filename or prompt is None or seed is None:

-        filename = f"{basename}"

+        file_decoration = ""

+    elif opts.save_to_dirs:

+        file_decoration = f"-{seed}"

     else:

-        filename = f"{basename}-{seed}-{sanitize_filename_part(prompt)[:128]}"

+        file_decoration = f"-{seed}-{sanitize_filename_part(prompt)[:128]}"

 

     if extension == 'png' and opts.enable_pnginfo and info is not None:

         pnginfo = PngImagePlugin.PngInfo()

@@ -354,8 +363,26 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
     else:

         pnginfo = None

 

+    if opts.save_to_dirs:

+        words = re.findall(r'\w+', prompt or "")

+        if len(words) == 0:

+            words = ["empty"]

+

+        dirname = " ".join(words[0:opts.save_to_dirs_prompt_len])

+        path = os.path.join(path, dirname)

+

     os.makedirs(path, exist_ok=True)

-    fullfn = os.path.join(path, f"{filename}.{extension}")

+

+    filecount = len(os.listdir(path))

+    fullfn = "a.png"

+    fullfn_without_extension = "a"

+    for i in range(100):

+        fn = f"{filecount:05}" if basename == '' else f"{basename}-{filecount:04}"

+        fullfn = os.path.join(path, f"{fn}{file_decoration}.{extension}")

+        fullfn_without_extension = os.path.join(path, f"{fn}{file_decoration}")

+        if not os.path.exists(fullfn):

+            break

+

     image.save(fullfn, quality=opts.jpeg_quality, pnginfo=pnginfo)

 

     target_side_length = 4000

@@ -368,7 +395,7 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
         elif oversize:

             image = image.resize((image.width * target_side_length // image.height, target_side_length), LANCZOS)

 

-        image.save(os.path.join(path, f"{filename}.jpg"), quality=opts.jpeg_quality, pnginfo=pnginfo)

+        image.save(os.path.join(path, f"{fullfn_without_extension}.jpg"), quality=opts.jpeg_quality, pnginfo=pnginfo)

 

 

 

@@ -824,8 +851,9 @@ class EmbeddingsWithFixes(nn.Module):
 

 

 class StableDiffusionProcessing:

-    def __init__(self, outpath=None, prompt="", seed=-1, sampler_index=0, batch_size=1, n_iter=1, steps=50, cfg_scale=7.0, width=512, height=512, prompt_matrix=False, use_GFPGAN=False, do_not_save_samples=False, do_not_save_grid=False, extra_generation_params=None, overlay_images=None, negative_prompt=None):

-        self.outpath: str = outpath

+    def __init__(self, outpath_samples=None, outpath_grids=None, prompt="", seed=-1, sampler_index=0, batch_size=1, n_iter=1, steps=50, cfg_scale=7.0, width=512, height=512, prompt_matrix=False, use_GFPGAN=False, do_not_save_samples=False, do_not_save_grid=False, extra_generation_params=None, overlay_images=None, negative_prompt=None):

+        self.outpath_samples: str = outpath_samples

+        self.outpath_grids: str = outpath_grids

         self.prompt: str = prompt

         self.negative_prompt: str = (negative_prompt or "")

         self.seed: int = seed

@@ -969,10 +997,8 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
 

     seed = int(random.randrange(4294967294) if p.seed == -1 else p.seed)

 

-    sample_path = os.path.join(p.outpath, "samples")

-    os.makedirs(sample_path, exist_ok=True)

-    base_count = len(os.listdir(sample_path))

-    grid_count = len(os.listdir(p.outpath)) - 1

+    os.makedirs(p.outpath_samples, exist_ok=True)

+    os.makedirs(p.outpath_grids, exist_ok=True)

 

     comments = []

 

@@ -1071,10 +1097,9 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
                         image = image.convert('RGB')

 

                     if not p.do_not_save_samples:

-                        save_image(image, sample_path, f"{base_count:05}", seeds[i], prompts[i], opts.samples_format, info=infotext())

+                        save_image(image, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext())

 

                     output_images.append(image)

-                    base_count += 1

 

         unwanted_grid_because_of_img_count = len(output_images) < 2 and opts.grid_only_if_multiple

         if (p.prompt_matrix or opts.grid_save) and not p.do_not_save_grid and not unwanted_grid_because_of_img_count:

@@ -1097,8 +1122,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             if return_grid:

                 output_images.insert(0, grid)

 

-            save_image(grid, p.outpath, f"grid-{grid_count:04}", seed, prompt, opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename)

-            grid_count += 1

+            save_image(grid, p.outpath_grids, "grid", seed, prompt, opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename)

 

     torch_gc()

     return Processed(output_images, seed, infotext())

@@ -1114,11 +1138,11 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
         samples_ddim = self.sampler.sample(self, x, conditioning, unconditional_conditioning)

         return samples_ddim

 

-def txt2img(prompt: str, negative_prompt: str, steps: int, sampler_index: int, use_GFPGAN: bool, prompt_matrix: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, height: int, width: int, code: str):

-    outpath = opts.outdir or "outputs/txt2img-samples"

 

+def txt2img(prompt: str, negative_prompt: str, steps: int, sampler_index: int, use_GFPGAN: bool, prompt_matrix: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, height: int, width: int, code: str):

     p = StableDiffusionProcessingTxt2Img(

-        outpath=outpath,

+        outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,

+        outpath_grids=opts.outdir_grids or opts.outdir_txt2img_grids,

         prompt=prompt,

         negative_prompt=negative_prompt,

         seed=seed,

@@ -1138,6 +1162,7 @@ def txt2img(prompt: str, negative_prompt: str, steps: int, sampler_index: int, u
         p.do_not_save_samples = True

 

         display_result_data = [[], -1, ""]

+

         def display(imgs, s=display_result_data[1], i=display_result_data[2]):

             display_result_data[0] = imgs

             display_result_data[1] = s

@@ -1422,8 +1447,6 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
 

 

 def img2img(prompt: str, init_img, init_img_with_mask, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, use_GFPGAN: bool, prompt_matrix, mode: int, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, height: int, width: int, resize_mode: int, upscaler_name: str, upscale_overlap: int, inpaint_full_res: bool):

-    outpath = opts.outdir or "outputs/img2img-samples"

-

     is_classic = mode == 0

     is_inpaint = mode == 1

     is_loopback = mode == 2

@@ -1439,7 +1462,8 @@ def img2img(prompt: str, init_img, init_img_with_mask, steps: int, sampler_index
     assert 0. <= denoising_strength <= 1., 'can only work with strength in [0.0, 1.0]'

 

     p = StableDiffusionProcessingImg2Img(

-        outpath=outpath,

+        outpath_samples=opts.outdir_samples or opts.outdir_img2img_samples,

+        outpath_grids=opts.outdir_grids or opts.outdir_img2img_grids,

         prompt=prompt,

         seed=seed,

         sampler_index=sampler_index,

@@ -1483,10 +1507,9 @@ def img2img(prompt: str, init_img, init_img_with_mask, steps: int, sampler_index
             p.denoising_strength = max(p.denoising_strength * 0.95, 0.1)

             history.append(processed.images[0])

 

-        grid_count = len(os.listdir(outpath)) - 1

         grid = image_grid(history, batch_size, rows=1)

 

-        save_image(grid, outpath, f"grid-{grid_count:04}", initial_seed, prompt, opts.grid_format, info=info, short_filename=not opts.grid_extended_filename)

+        save_image(grid, p.outpath_grids, "grid", initial_seed, prompt, opts.grid_format, info=info, short_filename=not opts.grid_extended_filename)

 

         processed = Processed(history, initial_seed, initial_info)

 

@@ -1535,8 +1558,7 @@ def img2img(prompt: str, init_img, init_img_with_mask, steps: int, sampler_index
 

         combined_image = combine_grid(grid)

 

-        grid_count = len(os.listdir(outpath)) - 1

-        save_image(combined_image, outpath, f"grid-{grid_count:04}", initial_seed, prompt, opts.grid_format, info=initial_info, short_filename=not opts.grid_extended_filename)

+        save_image(combined_image, p.outpath_grids, "grid", initial_seed, prompt, opts.grid_format, info=initial_info, short_filename=not opts.grid_extended_filename)

 

         processed = Processed([combined_image], initial_seed, initial_info)

 

@@ -1708,9 +1730,7 @@ def run_extras(image, GFPGAN_strength, RealESRGAN_upscaling, RealESRGAN_model_in
     if have_realesrgan and RealESRGAN_upscaling != 1.0:

         image = upscale_with_realesrgan(image, RealESRGAN_upscaling, RealESRGAN_model_index)

 

-    os.makedirs(outpath, exist_ok=True)

-    base_count = len(os.listdir(outpath))

-    save_image(image, outpath, f"{base_count:05}", None, '', opts.samples_format, short_filename=True)

+    save_image(image, outpath, "", None, '', opts.samples_format, short_filename=True)

 

     return image, 0, ''