diff options
Diffstat (limited to 'modules/interrogate.py')
| -rw-r--r-- | modules/interrogate.py | 11 |
1 files changed, 5 insertions, 6 deletions
diff --git a/modules/interrogate.py b/modules/interrogate.py index e1665708..111b1322 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -11,7 +11,6 @@ import torch.hub from torchvision import transforms
from torchvision.transforms.functional import InterpolationMode
-import modules.shared as shared
from modules import devices, paths, shared, lowvram, modelloader, errors
blip_image_eval_size = 384
@@ -28,7 +27,7 @@ def category_types(): def download_default_clip_interrogate_categories(content_dir):
print("Downloading CLIP categories...")
- tmpdir = content_dir + "_tmp"
+ tmpdir = f"{content_dir}_tmp"
category_types = ["artists", "flavors", "mediums", "movements"]
try:
@@ -160,7 +159,7 @@ class InterrogateModels: text_array = text_array[0:int(shared.opts.interrogate_clip_dict_limit)]
top_count = min(top_count, len(text_array))
- text_tokens = clip.tokenize([text for text in text_array], truncate=True).to(devices.device_interrogate)
+ text_tokens = clip.tokenize(list(text_array), truncate=True).to(devices.device_interrogate)
text_features = self.clip_model.encode_text(text_tokens).type(self.dtype)
text_features /= text_features.norm(dim=-1, keepdim=True)
@@ -208,13 +207,13 @@ class InterrogateModels: image_features /= image_features.norm(dim=-1, keepdim=True)
- for name, topn, items in self.categories():
- matches = self.rank(image_features, items, top_count=topn)
+ for cat in self.categories():
+ matches = self.rank(image_features, cat.items, top_count=cat.topn)
for match, score in matches:
if shared.opts.interrogate_return_ranks:
res += f", ({match}:{score/100:.3f})"
else:
- res += ", " + match
+ res += f", {match}"
except Exception:
print("Error interrogating", file=sys.stderr)
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