Merge pull request #7113 from vladmandic/interrogate

Add selector to interrogate categories

modules/interrogate.py

@@ -2,6 +2,7 @@ import os
 import sys
 import traceback
 from collections import namedtuple
+from pathlib import Path
 import re
 
 import torch
@@ -20,19 +21,20 @@ Category = namedtuple("Category", ["name", "topn", "items"])
 
 re_topn = re.compile(r"\.top(\d+)\.")
 
+def category_types():
+    return [f.stem for f in Path(shared.interrogator.content_dir).glob('*.txt')]
+
 
 def download_default_clip_interrogate_categories(content_dir):
     print("Downloading CLIP categories...")
 
     tmpdir = content_dir + "_tmp"
+    category_types = ["artists", "flavors", "mediums", "movements"]
+
     try:
         os.makedirs(tmpdir)
-
+        for category_type in category_types:
-        torch.hub.download_url_to_file("https://raw.githubusercontent.com/pharmapsychotic/clip-interrogator/main/clip_interrogator/data/artists.txt", os.path.join(tmpdir, "artists.txt"))
+            torch.hub.download_url_to_file(f"https://raw.githubusercontent.com/pharmapsychotic/clip-interrogator/main/clip_interrogator/data/{category_type}.txt", os.path.join(tmpdir, f"{category_type}.txt"))
-        torch.hub.download_url_to_file("https://raw.githubusercontent.com/pharmapsychotic/clip-interrogator/main/clip_interrogator/data/flavors.txt", os.path.join(tmpdir, "flavors.top3.txt"))
-        torch.hub.download_url_to_file("https://raw.githubusercontent.com/pharmapsychotic/clip-interrogator/main/clip_interrogator/data/mediums.txt", os.path.join(tmpdir, "mediums.txt"))
-        torch.hub.download_url_to_file("https://raw.githubusercontent.com/pharmapsychotic/clip-interrogator/main/clip_interrogator/data/movements.txt", os.path.join(tmpdir, "movements.txt"))
-
         os.rename(tmpdir, content_dir)
 
     except Exception as e:
@@ -51,27 +53,32 @@ class InterrogateModels:
 
     def __init__(self, content_dir):
         self.loaded_categories = None
+        self.skip_categories = []
         self.content_dir = content_dir
         self.running_on_cpu = devices.device_interrogate == torch.device("cpu")
 
     def categories(self):
-        if self.loaded_categories is not None:
+        if not os.path.exists(self.content_dir):
+            download_default_clip_interrogate_categories(self.content_dir)
+
+        if self.loaded_categories is not None and self.skip_categories == shared.opts.interrogate_clip_skip_categories:
            return self.loaded_categories
 
         self.loaded_categories = []
 
-        if not os.path.exists(self.content_dir):
-            download_default_clip_interrogate_categories(self.content_dir)
-
         if os.path.exists(self.content_dir):
-            for filename in os.listdir(self.content_dir):
+            self.skip_categories = shared.opts.interrogate_clip_skip_categories
-                m = re_topn.search(filename)
+            category_types = []
+            for filename in Path(self.content_dir).glob('*.txt'):
+                category_types.append(filename.stem)
+                if filename.stem in self.skip_categories:
+                    continue
+                m = re_topn.search(filename.stem)
                 topn = 1 if m is None else int(m.group(1))
-
+                with open(filename, "r", encoding="utf8") as file:
-                with open(os.path.join(self.content_dir, filename), "r", encoding="utf8") as file:
                     lines = [x.strip() for x in file.readlines()]
 
-                self.loaded_categories.append(Category(name=filename, topn=topn, items=lines))
+                self.loaded_categories.append(Category(name=filename.stem, topn=topn, items=lines))
 
         return self.loaded_categories
 
@@ -139,6 +146,8 @@ class InterrogateModels:
     def rank(self, image_features, text_array, top_count=1):
         import clip
 
+        devices.torch_gc()
+
         if shared.opts.interrogate_clip_dict_limit != 0:
             text_array = text_array[0:int(shared.opts.interrogate_clip_dict_limit)]
 

modules/shared.py

@@ -424,6 +424,7 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"),
     "interrogate_clip_min_length": OptionInfo(24, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}),
     "interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}),
     "interrogate_clip_dict_limit": OptionInfo(1500, "CLIP: maximum number of lines in text file (0 = No limit)"),
+    "interrogate_clip_skip_categories": OptionInfo([], "CLIP: skip inquire categories", gr.CheckboxGroup, lambda: {"choices": modules.interrogate.category_types()}, refresh=modules.interrogate.category_types),
     "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
     "deepbooru_sort_alpha": OptionInfo(True, "Interrogate: deepbooru sort alphabetically"),
     "deepbooru_use_spaces": OptionInfo(False, "use spaces for tags in deepbooru"),