Merge branch 'master' into hn-activation

1 files changed, 33 insertions, 5 deletions

diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index 33eaddb6..e13b1894 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -7,12 +7,14 @@ import tqdm
 import time

 

 from modules import shared, images

+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):

+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):

     try:

         if process_caption:

             shared.interrogator.load()

@@ -22,7 +24,7 @@ def preprocess(process_src, process_dst, process_width, process_height, preproce
             db_opts[deepbooru.OPT_INCLUDE_RANKS] = False

             deepbooru.create_deepbooru_process(opts.interrogate_deepbooru_score_threshold, db_opts)

 

-        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)

+        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)

 

     finally:

 

@@ -34,7 +36,7 @@ def preprocess(process_src, process_dst, process_width, process_height, preproce
 

 

 

-def preprocess_work(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):

+def preprocess_work(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):

     width = process_width

     height = process_height

     src = os.path.abspath(process_src)

@@ -113,6 +115,7 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre
                 splitted = image.crop((0, y, to_w, y + to_h))

             yield splitted

 

+

     for index, imagefile in enumerate(tqdm.tqdm(files)):

         subindex = [0]

         filename = os.path.join(src, imagefile)

@@ -137,11 +140,36 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre
             ratio = (img.height * width) / (img.width * height)

             inverse_xy = True

 

+        process_default_resize = True

+

         if process_split and ratio < 1.0 and ratio <= split_threshold:

             for splitted in split_pic(img, inverse_xy):

                 save_pic(splitted, index, existing_caption=existing_caption)

-        else:

+            process_default_resize = False

+

+        if process_focal_crop and img.height != img.width:

+

+            dnn_model_path = None

+            try:

+                dnn_model_path = autocrop.download_and_cache_models(os.path.join(models_path, "opencv"))

+            except Exception as e:

+                print("Unable to load face detection model for auto crop selection. Falling back to lower quality haar method.", e)

+

+            autocrop_settings = autocrop.Settings(

+                crop_width = width,

+                crop_height = height,

+                face_points_weight = process_focal_crop_face_weight,

+                entropy_points_weight = process_focal_crop_entropy_weight,

+                corner_points_weight = process_focal_crop_edges_weight,

+                annotate_image = process_focal_crop_debug,

+                dnn_model_path = dnn_model_path,

+            )

+            for focal in autocrop.crop_image(img, autocrop_settings):

+                save_pic(focal, index, existing_caption=existing_caption)

+            process_default_resize = False

+

+        if process_default_resize:

             img = images.resize_image(1, img, width, height)

             save_pic(img, index, existing_caption=existing_caption)

 

-        shared.state.nextjob()

+        shared.state.nextjob()
\ No newline at end of file