Spaces:
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Running
memoize and also based
Browse files
app.py
CHANGED
@@ -7,7 +7,20 @@ from PIL import Image
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from huggingface_hub import hf_hub_download
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from onnxruntime import InferenceSession
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-
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# noinspection PyUnresolvedReferences
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def make_square(img, target_size):
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old_size = img.shape[:2]
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@@ -119,7 +132,7 @@ WAIFU_MODELS: Mapping[str, WaifuDiffusionInterrogator] = {
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}
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RE_SPECIAL = re.compile(r'([\\()])')
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def image_to_wd14_tags(image: Image.Image, model_name: str, threshold: float,
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use_spaces: bool, use_escape: bool, include_ranks=False, score_descend=True) \
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-> Tuple[Mapping[str, float], str, Mapping[str, float]]:
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@@ -139,12 +152,15 @@ def image_to_wd14_tags(image: Image.Image, model_name: str, threshold: float,
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tag_outformat = tag
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if use_spaces:
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tag_outformat = tag_outformat.replace('_', ' ')
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if use_escape:
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tag_outformat = re.sub(RE_SPECIAL, r'\\\1', tag_outformat)
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if include_ranks:
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tag_outformat = f"({tag_outformat}:{score:.3f})"
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text_items.append(tag_outformat)
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output_text = '
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return ratings, output_text, filtered_tags
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from huggingface_hub import hf_hub_download
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from onnxruntime import InferenceSession
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from functools import wraps
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def memoize(func):
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cache = {}
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cache_maxsize = 25
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@wraps(func)
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def memoized_func(*args):
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if args not in cache:
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cache[args] = func(*args)
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if len(cache) > cache_maxsize:
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cache.popitem(last=False)
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return cache[args]
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return memoized_func
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# noinspection PyUnresolvedReferences
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def make_square(img, target_size):
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old_size = img.shape[:2]
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}
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RE_SPECIAL = re.compile(r'([\\()])')
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@memoize
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def image_to_wd14_tags(image: Image.Image, model_name: str, threshold: float,
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use_spaces: bool, use_escape: bool, include_ranks=False, score_descend=True) \
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-> Tuple[Mapping[str, float], str, Mapping[str, float]]:
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tag_outformat = tag
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if use_spaces:
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tag_outformat = tag_outformat.replace('_', ' ')
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tag_outformat.replace(' ', '-')
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else:
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tag_outformat.replace('_', '-')
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if use_escape:
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tag_outformat = re.sub(RE_SPECIAL, r'\\\1', tag_outformat)
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if include_ranks:
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tag_outformat = f"({tag_outformat}:{score:.3f})"
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text_items.append(tag_outformat)
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output_text = ' '.join(text_items)
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return ratings, output_text, filtered_tags
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