Stable Diffusion Texual Inversion Models
Generated from huggingface.co/sd-concepts-library @@ -102,10 +105,6 @@ jobs: Downloaded models are straight from the HuggingFace repositories and are named learned_embeds.bin. Rename to model_name.pt
-- The HuggingFace repository is changed regularly so this page might not be current. -
-""" @@ -151,3 +150,8 @@ jobs: f = open('sd-concepts-library.html', 'w') f.write(html_struct) f.close() + + # markdown = markdownify.markdownify(html_struct, heading_style="ATX") + # f = open('sd-concepts-library.md', 'w') + # f.write(markdown) + # f.close() diff --git a/other/generate_tx_models_html.py b/other/generate_tx_models_html.py new file mode 100644 index 0000000..3fa4752 --- /dev/null +++ b/other/generate_tx_models_html.py @@ -0,0 +1,132 @@ +import os +import shutil +from urllib import request as ulreq + +import requests +from huggingface_hub import HfApi +from PIL import ImageFile + + +def getsizes(uri): + # https://stackoverflow.com/a/37709319 + # get file size *and* image size (None if not known) + file = ulreq.urlopen(uri) + size = file.headers.get("content-length") + if size: + size = int(size) + p = ImageFile.Parser() + while True: + data = file.read(1024) + if not data: + break + p.feed(data) + if p.image: + return size, p.image.size + break + file.close() + return (size, None) + + +# Get list of model directories +# working_dir = os.getcwd() +# root_dir_list = [] +# for x in os.listdir(working_dir): +# if os.path.isdir(x): +# root_dir_list.append(x) + +# Get list of models under the sd-concepts-library organization +api = HfApi() +root_dir_list = api.list_models(author="sd-concepts-library").sort() + +html_struct = """ + + +
+
+
+
+""" + +# Move the model out +i = 1 +for model_name in root_dir_list: + print(f'{i}/{len(root_dir_list)} -> {model_name}') + # if os.path.exists(f'{model_name}/learned_embeds.bin'): # double check the file exists since sometimes it hasn't been uploaded yet + # shutil.move(f'{model_name}/learned_embeds.bin', f'{model_name}/{model_name}.pt') + # pass + # else: + # continue + + # Images can be in a few different formats, figure out which one it's in + img_type = None + img_width = None + for type in ['jpeg', 'png', 'jpg']: + r = requests.head(f'https://huggingface.co/sd-concepts-library/{model_name}/resolve/main/concept_images/0.{type}', allow_redirects=True) + if r.status_code == 200: + img_type = type + img_width = getsizes(f'https://huggingface.co/sd-concepts-library/{model_name}/resolve/main/concept_images/0.{type}')[1][0] + break + + html_struct = html_struct + f"""
'
+
+f = open('sd-concepts-library.html', 'w')
+f.write(html_struct)
+f.close()
+
+# markdown = markdownify.markdownify(html_struct, heading_style="ATX")
+# f = open('sd-concepts-library.md', 'w')
+# f.write(markdown)
+# f.close()
Stable Diffusion Texual Inversion Models
+ Generated from huggingface.co/sd-concepts-library +
+ ++ Downloaded models are straight from the HuggingFace repositories and are named learned_embeds.bin. Rename to model_name.pt +
+ + ++""" + +# Move the model out +i = 1 +for model_name in root_dir_list: + print(f'{i}/{len(root_dir_list)} -> {model_name}') + # if os.path.exists(f'{model_name}/learned_embeds.bin'): # double check the file exists since sometimes it hasn't been uploaded yet + # shutil.move(f'{model_name}/learned_embeds.bin', f'{model_name}/{model_name}.pt') + # pass + # else: + # continue + + # Images can be in a few different formats, figure out which one it's in + img_type = None + img_width = None + for type in ['jpeg', 'png', 'jpg']: + r = requests.head(f'https://huggingface.co/sd-concepts-library/{model_name}/resolve/main/concept_images/0.{type}', allow_redirects=True) + if r.status_code == 200: + img_type = type + img_width = getsizes(f'https://huggingface.co/sd-concepts-library/{model_name}/resolve/main/concept_images/0.{type}')[1][0] + break + + html_struct = html_struct + f"""
{model_name}
+ + +
+
"""
+ i = i + 1
+
+html_struct = html_struct + '
+ 
+
+
+ 
+
+
+ 
+
+