Merge branch 'AUTOMATIC1111:master' into draft

3 files changed, 7 insertions, 11 deletions

diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index 488aa5b5..56b9b2eb 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -6,12 +6,10 @@ import sys
 import tqdm

 import time

 

-from modules import shared, images

+from modules import shared, images, deepbooru

 from modules.paths import models_path

 from modules.shared import opts, cmd_opts

 from modules.textual_inversion import autocrop

-if cmd_opts.deepdanbooru:

-    import modules.deepbooru as deepbooru

 

 

 def preprocess(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False):

@@ -20,9 +18,7 @@ def preprocess(process_src, process_dst, process_width, process_height, preproce
             shared.interrogator.load()

 

         if process_caption_deepbooru:

-            db_opts = deepbooru.create_deepbooru_opts()

-            db_opts[deepbooru.OPT_INCLUDE_RANKS] = False

-            deepbooru.create_deepbooru_process(opts.interrogate_deepbooru_score_threshold, db_opts)

+            deepbooru.model.start()

 

         preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_flip, process_split, process_caption, process_caption_deepbooru, split_threshold, overlap_ratio, process_focal_crop, process_focal_crop_face_weight, process_focal_crop_entropy_weight, process_focal_crop_edges_weight, process_focal_crop_debug)

 

@@ -32,7 +28,7 @@ def preprocess(process_src, process_dst, process_width, process_height, preproce
             shared.interrogator.send_blip_to_ram()

 

         if process_caption_deepbooru:

-            deepbooru.release_process()

+            deepbooru.model.stop()

 

 

 def listfiles(dirname):

@@ -58,7 +54,7 @@ def save_pic_with_caption(image, index, params: PreprocessParams, existing_capti
     if params.process_caption_deepbooru:

         if len(caption) > 0:

             caption += ", "

-        caption += deepbooru.get_tags_from_process(image)

+        caption += deepbooru.model.tag_multi(image)

 

     filename_part = params.src

     filename_part = os.path.splitext(filename_part)[0]

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 0aeb0459..5e4d8688 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -10,7 +10,7 @@ import csv
 

 from PIL import Image, PngImagePlugin

 

-from modules import shared, devices, sd_hijack, processing, sd_models, images

+from modules import shared, devices, sd_hijack, processing, sd_models, images, sd_samplers

 import modules.textual_inversion.dataset

 from modules.textual_inversion.learn_schedule import LearnRateScheduler

 

@@ -345,7 +345,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
                 p.prompt = preview_prompt

                 p.negative_prompt = preview_negative_prompt

                 p.steps = preview_steps

-                p.sampler_index = preview_sampler_index

+                p.sampler_name = sd_samplers.samplers[preview_sampler_index].name

                 p.cfg_scale = preview_cfg_scale

                 p.seed = preview_seed

                 p.width = preview_width

diff --git a/modules/textual_inversion/ui.py b/modules/textual_inversion/ui.py
index d679e6f4..35c4feef 100644
--- a/modules/textual_inversion/ui.py
+++ b/modules/textual_inversion/ui.py
@@ -18,7 +18,7 @@ def create_embedding(name, initialization_text, nvpt, overwrite_old):
 def preprocess(*args):

     modules.textual_inversion.preprocess.preprocess(*args)

 

-    return "Preprocessing finished.", ""

+    return f"Preprocessing {'interrupted' if shared.state.interrupted else 'finished'}.", ""

 

 

 def train_embedding(*args):