1 files changed, 142 insertions, 62 deletions
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index 886cf0c3..feb876c6 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -1,27 +1,26 @@
 import os
 from PIL import Image, ImageOps
+import math
 import platform
 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
-if cmd_opts.deepdanbooru:
-    import modules.deepbooru as deepbooru
+from modules.textual_inversion import autocrop
 
 
-def preprocess(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru=False):
+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()
 
         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, process_flip, process_split, process_caption, process_caption_deepbooru)
+        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:
 
@@ -29,88 +28,169 @@ def preprocess(process_src, process_dst, process_width, process_height, process_
             shared.interrogator.send_blip_to_ram()
 
         if process_caption_deepbooru:
-            deepbooru.release_process()
+            deepbooru.model.stop()
 
 
+def listfiles(dirname):
+    return os.listdir(dirname)
 
-def preprocess_work(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru=False):
+
+class PreprocessParams:
+    src = None
+    dstdir = None
+    subindex = 0
+    flip = False
+    process_caption = False
+    process_caption_deepbooru = False
+    preprocess_txt_action = None
+
+
+def save_pic_with_caption(image, index, params: PreprocessParams, existing_caption=None):
+    caption = ""
+
+    if params.process_caption:
+        caption += shared.interrogator.generate_caption(image)
+
+    if params.process_caption_deepbooru:
+        if len(caption) > 0:
+            caption += ", "
+        caption += deepbooru.model.tag_multi(image)
+
+    filename_part = params.src
+    filename_part = os.path.splitext(filename_part)[0]
+    filename_part = os.path.basename(filename_part)
+
+    basename = f"{index:05}-{params.subindex}-{filename_part}"
+    image.save(os.path.join(params.dstdir, f"{basename}.png"))
+
+    if params.preprocess_txt_action == 'prepend' and existing_caption:
+        caption = existing_caption + ' ' + caption
+    elif params.preprocess_txt_action == 'append' and existing_caption:
+        caption = caption + ' ' + existing_caption
+    elif params.preprocess_txt_action == 'copy' and existing_caption:
+        caption = existing_caption
+
+    caption = caption.strip()
+
+    if len(caption) > 0:
+        with open(os.path.join(params.dstdir, f"{basename}.txt"), "w", encoding="utf8") as file:
+            file.write(caption)
+
+    params.subindex += 1
+
+
+def save_pic(image, index, params, existing_caption=None):
+    save_pic_with_caption(image, index, params, existing_caption=existing_caption)
+
+    if params.flip:
+        save_pic_with_caption(ImageOps.mirror(image), index, params, existing_caption=existing_caption)
+
+
+def split_pic(image, inverse_xy, width, height, overlap_ratio):
+    if inverse_xy:
+        from_w, from_h = image.height, image.width
+        to_w, to_h = height, width
+    else:
+        from_w, from_h = image.width, image.height
+        to_w, to_h = width, height
+    h = from_h * to_w // from_w
+    if inverse_xy:
+        image = image.resize((h, to_w))
+    else:
+        image = image.resize((to_w, h))
+
+    split_count = math.ceil((h - to_h * overlap_ratio) / (to_h * (1.0 - overlap_ratio)))
+    y_step = (h - to_h) / (split_count - 1)
+    for i in range(split_count):
+        y = int(y_step * i)
+        if inverse_xy:
+            splitted = image.crop((y, 0, y + to_h, to_w))
+        else:
+            splitted = image.crop((0, y, to_w, y + to_h))
+        yield splitted
+
+
+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)
     dst = os.path.abspath(process_dst)
+    split_threshold = max(0.0, min(1.0, split_threshold))
+    overlap_ratio = max(0.0, min(0.9, overlap_ratio))
 
     assert src != dst, 'same directory specified as source and destination'
 
     os.makedirs(dst, exist_ok=True)
 
-    files = os.listdir(src)
+    files = listfiles(src)
 
+    shared.state.job = "preprocess"
     shared.state.textinfo = "Preprocessing..."
     shared.state.job_count = len(files)
 
-    def save_pic_with_caption(image, index):
-        caption = ""
-
-        if process_caption:
-            caption += shared.interrogator.generate_caption(image)
-
-        if process_caption_deepbooru:
-            if len(caption) > 0:
-                caption += ", "
-            caption += deepbooru.get_tags_from_process(image)
-
-        filename_part = filename
-        filename_part = os.path.splitext(filename_part)[0]
-        filename_part = os.path.basename(filename_part)
-
-        basename = f"{index:05}-{subindex[0]}-{filename_part}"
-        image.save(os.path.join(dst, f"{basename}.png"))
-
-        if len(caption) > 0:
-            with open(os.path.join(dst, f"{basename}.txt"), "w", encoding="utf8") as file:
-                file.write(caption)
-
-        subindex[0] += 1
-
-    def save_pic(image, index):
-        save_pic_with_caption(image, index)
-
-        if process_flip:
-            save_pic_with_caption(ImageOps.mirror(image), index)
+    params = PreprocessParams()
+    params.dstdir = dst
+    params.flip = process_flip
+    params.process_caption = process_caption
+    params.process_caption_deepbooru = process_caption_deepbooru
+    params.preprocess_txt_action = preprocess_txt_action
 
     for index, imagefile in enumerate(tqdm.tqdm(files)):
-        subindex = [0]
+        params.subindex = 0
         filename = os.path.join(src, imagefile)
         try:
             img = Image.open(filename).convert("RGB")
         except Exception:
             continue
 
-        if shared.state.interrupted:
-            break
-
-        ratio = img.height / img.width
-        is_tall = ratio > 1.35
-        is_wide = ratio < 1 / 1.35
-
-        if process_split and is_tall:
-            img = img.resize((width, height * img.height // img.width))
+        params.src = filename
 
-            top = img.crop((0, 0, width, height))
-            save_pic(top, index)
+        existing_caption = None
+        existing_caption_filename = os.path.splitext(filename)[0] + '.txt'
+        if os.path.exists(existing_caption_filename):
+            with open(existing_caption_filename, 'r', encoding="utf8") as file:
+                existing_caption = file.read()
 
-            bot = img.crop((0, img.height - height, width, img.height))
-            save_pic(bot, index)
-        elif process_split and is_wide:
-            img = img.resize((width * img.width // img.height, height))
-
-            left = img.crop((0, 0, width, height))
-            save_pic(left, index)
+        if shared.state.interrupted:
+            break
 
-            right = img.crop((img.width - width, 0, img.width, height))
-            save_pic(right, index)
+        if img.height > img.width:
+            ratio = (img.width * height) / (img.height * width)
+            inverse_xy = False
         else:
+            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, width, height, overlap_ratio):
+                save_pic(splitted, index, params, existing_caption=existing_caption)
+            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, params, existing_caption=existing_caption)
+            process_default_resize = False
+
+        if process_default_resize:
             img = images.resize_image(1, img, width, height)
-            save_pic(img, index)
+            save_pic(img, index, params, existing_caption=existing_caption)
 
         shared.state.nextjob()