diff options
Diffstat (limited to 'modules')
| -rw-r--r-- | modules/api/api.py | 23 | ||||
| -rw-r--r-- | modules/api/models.py | 1 | ||||
| -rw-r--r-- | modules/interrogate.py | 49 | ||||
| -rw-r--r-- | modules/paths.py | 14 | ||||
| -rw-r--r-- | modules/shared.py | 1 | ||||
| -rw-r--r-- | modules/ui_extra_networks.py | 6 |
6 files changed, 68 insertions, 26 deletions
diff --git a/modules/api/api.py b/modules/api/api.py index b1dd14cc..25c65e57 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -53,7 +53,11 @@ def setUpscalers(req: dict): def decode_base64_to_image(encoding): if encoding.startswith("data:image/"): encoding = encoding.split(";")[1].split(",")[1] - return Image.open(BytesIO(base64.b64decode(encoding))) + try: + image = Image.open(BytesIO(base64.b64decode(encoding))) + return image + except Exception as err: + raise HTTPException(status_code=500, detail="Invalid encoded image") def encode_pil_to_base64(image): with io.BytesIO() as output_bytes: @@ -371,13 +375,16 @@ class Api: return [{"name": sampler[0], "aliases":sampler[2], "options":sampler[3]} for sampler in sd_samplers.all_samplers] def get_upscalers(self): - upscalers = [] - - for upscaler in shared.sd_upscalers: - u = upscaler.scaler - upscalers.append({"name":u.name, "model_name":u.model_name, "model_path":u.model_path, "model_url":u.model_url}) - - return upscalers + return [ + { + "name": upscaler.name, + "model_name": upscaler.scaler.model_name, + "model_path": upscaler.data_path, + "model_url": None, + "scale": upscaler.scale, + } + for upscaler in shared.sd_upscalers + ] def get_sd_models(self): return [{"title": x.title, "model_name": x.model_name, "hash": x.shorthash, "sha256": x.sha256, "filename": x.filename, "config": find_checkpoint_config(x)} for x in checkpoints_list.values()] diff --git a/modules/api/models.py b/modules/api/models.py index 1eb1fcf1..805bd8f7 100644 --- a/modules/api/models.py +++ b/modules/api/models.py @@ -220,6 +220,7 @@ class UpscalerItem(BaseModel): model_name: Optional[str] = Field(title="Model Name") model_path: Optional[str] = Field(title="Path") model_url: Optional[str] = Field(title="URL") + scale: Optional[float] = Field(title="Scale") class SDModelItem(BaseModel): title: str = Field(title="Title") diff --git a/modules/interrogate.py b/modules/interrogate.py index 19938cbb..c72ff694 100644 --- a/modules/interrogate.py +++ b/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)
-
- 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("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"))
-
+ for category_type in category_types:
+ 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"))
os.rename(tmpdir, content_dir)
except Exception as e:
@@ -51,31 +53,44 @@ 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:
- return self.loaded_categories
-
- self.loaded_categories = []
-
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 os.path.exists(self.content_dir):
- for filename in os.listdir(self.content_dir):
- m = re_topn.search(filename)
+ self.skip_categories = shared.opts.interrogate_clip_skip_categories
+ 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(os.path.join(self.content_dir, filename), "r", encoding="utf8") as file:
+ with open(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
+ def create_fake_fairscale(self):
+ class FakeFairscale:
+ def checkpoint_wrapper(self):
+ pass
+
+ sys.modules["fairscale.nn.checkpoint.checkpoint_activations"] = FakeFairscale
+
def load_blip_model(self):
+ self.create_fake_fairscale()
import models.blip
files = modelloader.load_models(
@@ -139,6 +154,8 @@ 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)]
diff --git a/modules/paths.py b/modules/paths.py index 4dd03a35..20b3e4d8 100644 --- a/modules/paths.py +++ b/modules/paths.py @@ -38,3 +38,17 @@ for d, must_exist, what, options in path_dirs: else:
sys.path.append(d)
paths[what] = d
+
+
+class Prioritize:
+ def __init__(self, name):
+ self.name = name
+ self.path = None
+
+ def __enter__(self):
+ self.path = sys.path.copy()
+ sys.path = [paths[self.name]] + sys.path
+
+ def __exit__(self, exc_type, exc_val, exc_tb):
+ sys.path = self.path
+ self.path = None
diff --git a/modules/shared.py b/modules/shared.py index e17b4561..5f713bee 100644 --- a/modules/shared.py +++ b/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"),
diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py index 2ddac3d8..8b4f97f8 100644 --- a/modules/ui_extra_networks.py +++ b/modules/ui_extra_networks.py @@ -3,6 +3,7 @@ import os.path from modules import shared
import gradio as gr
import json
+import html
from modules.generation_parameters_copypaste import image_from_url_text
@@ -54,12 +55,13 @@ class ExtraNetworksPage: preview = item.get("preview", None)
args = {
- "preview_html": "style='background-image: url(" + json.dumps(preview) + ")'" if preview else '',
+ "preview_html": "style='background-image: url(\"" + html.escape(preview) + "\")'" if preview else '',
"prompt": item["prompt"],
"tabname": json.dumps(tabname),
"local_preview": json.dumps(item["local_preview"]),
"name": item["name"],
- "allow_negative_prompt": "true" if self.allow_negative_prompt else "false",
+ "card_clicked": '"' + html.escape(f"""return cardClicked({json.dumps(tabname)}, {item["prompt"]}, {"true" if self.allow_negative_prompt else "false"})""") + '"',
+ "save_card_preview": '"' + html.escape(f"""return saveCardPreview(event, {json.dumps(tabname)}, {json.dumps(item["local_preview"])})""") + '"',
}
return self.card_page.format(**args)
|