├── .gitignore ├── LICENSE ├── README.md ├── blip2.py ├── install.py ├── screenshots ├── screenshot-1.jpg └── screenshot-2.jpg └── scripts └── main.py /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | pip-wheel-metadata/ 24 | share/python-wheels/ 25 | *.egg-info/ 26 | .installed.cfg 27 | *.egg 28 | MANIFEST 29 | 30 | # PyInstaller 31 | # Usually these files are written by a python script from a template 32 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 33 | *.manifest 34 | *.spec 35 | 36 | # Installer logs 37 | pip-log.txt 38 | pip-delete-this-directory.txt 39 | 40 | # Unit test / coverage reports 41 | htmlcov/ 42 | .tox/ 43 | .nox/ 44 | .coverage 45 | .coverage.* 46 | .cache 47 | nosetests.xml 48 | coverage.xml 49 | *.cover 50 | *.py,cover 51 | .hypothesis/ 52 | .pytest_cache/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | target/ 76 | 77 | # Jupyter Notebook 78 | .ipynb_checkpoints 79 | 80 | # IPython 81 | profile_default/ 82 | ipython_config.py 83 | 84 | # pyenv 85 | .python-version 86 | 87 | # pipenv 88 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 89 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 90 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 91 | # install all needed dependencies. 92 | #Pipfile.lock 93 | 94 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow 95 | __pypackages__/ 96 | 97 | # Celery stuff 98 | celerybeat-schedule 99 | celerybeat.pid 100 | 101 | # SageMath parsed files 102 | *.sage.py 103 | 104 | # Environments 105 | .env 106 | .venv 107 | env/ 108 | venv/ 109 | ENV/ 110 | env.bak/ 111 | venv.bak/ 112 | 113 | # Spyder project settings 114 | .spyderproject 115 | .spyproject 116 | 117 | # Rope project settings 118 | .ropeproject 119 | 120 | # mkdocs documentation 121 | /site 122 | 123 | # mypy 124 | .mypy_cache/ 125 | .dmypy.json 126 | dmypy.json 127 | 128 | # Pyre type checker 129 | .pyre/ 130 | 131 | models 132 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU AFFERO GENERAL PUBLIC LICENSE 2 | Version 3, 19 November 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU Affero General Public License is a free, copyleft license for 11 | software and other kinds of works, specifically designed to ensure 12 | cooperation with the community in the case of network server software. 13 | 14 | The licenses for most software and other practical works are designed 15 | to take away your freedom to share and change the works. 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It is safest 628 | to attach them to the start of each source file to most effectively 629 | state the exclusion of warranty; and each file should have at least 630 | the "copyright" line and a pointer to where the full notice is found. 631 | 632 | 633 | Copyright (C) 634 | 635 | This program is free software: you can redistribute it and/or modify 636 | it under the terms of the GNU Affero General Public License as published 637 | by the Free Software Foundation, either version 3 of the License, or 638 | (at your option) any later version. 639 | 640 | This program is distributed in the hope that it will be useful, 641 | but WITHOUT ANY WARRANTY; without even the implied warranty of 642 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 643 | GNU Affero General Public License for more details. 644 | 645 | You should have received a copy of the GNU Affero General Public License 646 | along with this program. If not, see . 647 | 648 | Also add information on how to contact you by electronic and paper mail. 649 | 650 | If your software can interact with users remotely through a computer 651 | network, you should also make sure that it provides a way for users to 652 | get its source. For example, if your program is a web application, its 653 | interface could display a "Source" link that leads users to an archive 654 | of the code. There are many ways you could offer source, and different 655 | solutions will be better for different programs; see section 13 for the 656 | specific requirements. 657 | 658 | You should also get your employer (if you work as a programmer) or school, 659 | if any, to sign a "copyright disclaimer" for the program, if necessary. 660 | For more information on this, and how to apply and follow the GNU AGPL, see 661 | . 662 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # stable-diffusion-webui-blip2-captioner 2 | 3 | BLIP2 captioning tool as an extension of AUTOMATIC's WebUI. 4 | 5 | # Screenshots 6 | 7 | ![screenshot 1](./screenshots/screenshot-1.jpg) 8 | 9 | ![screenshot 2](./screenshots/screenshot-2.jpg) 10 | 11 | # Features 12 | 13 | - Lightweight models without large language models (the `coco` model only) 14 | - Batch processing 15 | 16 | # Parameters 17 | 18 | | Name | Values | Default | Description | 19 | | ------------------ | -------------------- | --------- | ---------------------------------------------------------------------------------------------- | 20 | | Sampling method | `Nucleus` or `Top-K` | `Nucleus` | I don't know the difference. sorry. | 21 | | Number of beams | ≧ 0 | 3 | Number of beams for beam search. 1 means no beam search. | 22 | | Caption min length | ≧ 0 | 10 | The minimum length of the caption to be generated. If very large, caption accuracy may degrade | 23 | | Caption max length | ≧ Caption min length | 30 | The minimum length of the caption to be generated. | 24 | | Top P | ≧ 0.0 | 0.9 | The cumulative probability for nucleus sampling. | 25 | 26 | 27 | # License 28 | This software includes the following third-party libraries: 29 | - [salesforce-lavis](https://github.com/salesforce/LAVIS/tree/main/projects/blip2) (BSD-3-Clause License) 30 | 31 | 32 | # Related extensions 33 | 34 | - [Tps-F/sd-webui-blip2](https://github.com/Tps-F/sd-webui-blip2) 35 | - [toriato/stable-diffusion-webui-wd14-tagger](https://github.com/toriato/stable-diffusion-webui-wd14-tagger) 36 | 37 | -------------------------------------------------------------------------------- /blip2.py: -------------------------------------------------------------------------------- 1 | import torch 2 | from typing import Optional, List, Tuple 3 | from PIL import Image 4 | from lavis.models import load_model_and_preprocess 5 | 6 | class BLIP2: 7 | def __init__(self, model_type): 8 | # setup device to use 9 | self.device = torch.device("cuda") if torch.cuda.is_available() else "cpu" 10 | self.model, self.vis_processors, _ = load_model_and_preprocess(name="blip2", model_type=model_type, is_eval=True, device=self.device) 11 | 12 | def generate_caption( 13 | self, 14 | image: Image, 15 | num_beams: int = 3, # number of beams to use for beam search. 1 means no beam search. 16 | use_nucleus_sampling: bool = False, # if False, use top-k sampling 17 | max_length: int = 3, # maximum length of the generated caption 18 | min_length: int = 30, # minimum length of the generated caption 19 | top_p: float = 10, # The cumulative probability for nucleus sampling. 20 | repetition_penalty: float = 0.9, # The parameter for repetition penalty. 1.0 means no penalty. 21 | # num_captions: int = 1, # number of captions to generate # this is not exist!! 22 | ): 23 | # loads BLIP-2 pre-trained model 24 | # prepare the image 25 | image = self.vis_processors["eval"](image).unsqueeze(0).to(self.device) 26 | 27 | captions = self.model.generate( 28 | {"image": image}, 29 | num_beams=num_beams, 30 | use_nucleus_sampling=use_nucleus_sampling, 31 | max_length=max_length, 32 | min_length=min_length, 33 | top_p=top_p, 34 | repetition_penalty=repetition_penalty, 35 | # num_captions=num_captions, 36 | ) 37 | return captions 38 | 39 | def unload(self): 40 | del self.model 41 | del self.vis_processors 42 | torch.cuda.empty_cache() 43 | -------------------------------------------------------------------------------- /install.py: -------------------------------------------------------------------------------- 1 | import launch 2 | 3 | if not launch.is_installed("lavis"): 4 | launch.run_pip( 5 | "install salesforce-lavis", 6 | "requirements for BLIP2 captioner (lavis)", 7 | ) 8 | 9 | if not launch.is_installed("pywintypes"): 10 | launch.run_pip( 11 | "install pywintypes", 12 | "requirements for BLIP2 captioner (pywintypes)", 13 | ) -------------------------------------------------------------------------------- /screenshots/screenshot-1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/p1atdev/stable-diffusion-webui-blip2-captioner/b7b1df0077654a3ed676be2363264cdb106300ff/screenshots/screenshot-1.jpg -------------------------------------------------------------------------------- /screenshots/screenshot-2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/p1atdev/stable-diffusion-webui-blip2-captioner/b7b1df0077654a3ed676be2363264cdb106300ff/screenshots/screenshot-2.jpg -------------------------------------------------------------------------------- /scripts/main.py: -------------------------------------------------------------------------------- 1 | import os 2 | from pathlib import Path 3 | import torch 4 | 5 | import gradio as gr 6 | from PIL import Image, ImageFile 7 | 8 | ImageFile.LOAD_TRUNCATED_IMAGES = True 9 | 10 | from modules import script_callbacks 11 | 12 | from blip2 import BLIP2 13 | 14 | captioners = {} 15 | # model_loading_status = 0 # 1 to loading, 2 to loaded 16 | 17 | model_list = [ 18 | "coco", 19 | "pretrain", 20 | ] 21 | 22 | sampling_methods = ["Nucleus", "Top-K"] 23 | 24 | def model_check(name): 25 | # global model_loading_status 26 | # if model_loading_status == 1: 27 | # raise Exception("Model is loading") 28 | if name not in captioners: 29 | # library_check() 30 | if name in model_list: 31 | print(f"Loading {name} model...") 32 | # model_loading_status = 1 33 | # unload other models 34 | # unload_models(False) 35 | captioners[name] = BLIP2( 36 | name 37 | ) 38 | print(f"Model {name} loaded") 39 | # model_loading_status = 2 40 | 41 | 42 | def unload_models(log: bool = True): 43 | if log: 44 | print("Unloading models...") 45 | for key in captioners: 46 | captioners[key].unload() 47 | captioners.clear() 48 | torch.cuda.empty_cache() 49 | # global model_loading_status 50 | # model_loading_status = 0 51 | if log: 52 | print("Done. Models unloaded") 53 | 54 | def generate_caption( 55 | image: Image, 56 | # model_name, 57 | sampling_type, 58 | num_beams, 59 | caption_max_length, 60 | caption_min_length, 61 | top_p, 62 | # repitition_penalty, 63 | ): 64 | if image is None: 65 | return "" 66 | model_name = "coco" 67 | try: 68 | model_check(model_name) 69 | except: 70 | return "" 71 | print(f"Generating captions...") 72 | captions = captioners[model_name].generate_caption( 73 | image, 74 | num_beams=num_beams, 75 | use_nucleus_sampling=(sampling_type == "Nucleus"), 76 | max_length=caption_max_length, 77 | min_length=caption_min_length, 78 | top_p=top_p, 79 | # repetition_penalty=repitition_penalty, 80 | ) 81 | caption = captions[0] 82 | print(caption) 83 | 84 | return caption 85 | 86 | def generate_caption_for_single_image( 87 | image, 88 | sampling_type, 89 | num_beams, 90 | caption_max_length, 91 | caption_min_length, 92 | top_p, 93 | ): 94 | caption = generate_caption( 95 | image, 96 | sampling_type, 97 | num_beams, 98 | caption_max_length, 99 | caption_min_length, 100 | top_p, 101 | ) 102 | return caption 103 | 104 | def create_caption_file(caption, output_caption_path): 105 | with open(output_caption_path, "w", encoding="utf-8") as f: 106 | f.write(caption) 107 | 108 | def batch_captioning( 109 | input_dir, 110 | output_dir, 111 | caption_ext, 112 | # model_name, 113 | sampling_type, 114 | num_beams, 115 | caption_max_length, 116 | caption_min_length, 117 | top_p, 118 | # repitition_penalty, 119 | ): 120 | print("Batch captioning started") 121 | try: 122 | input_dir = Path(input_dir) 123 | output_dir = Path(output_dir) 124 | image_paths = [ 125 | p 126 | for p in input_dir.iterdir() 127 | if (p.is_file and p.suffix.lower() in [".png", ".jpg", ".jpeg", ".webp"]) 128 | ] 129 | 130 | print(f"Found {len(image_paths)} images") 131 | 132 | if not os.path.exists(output_dir): 133 | os.makedirs(output_dir) 134 | 135 | for i, f in enumerate(image_paths): 136 | if f.is_dir(): 137 | continue 138 | 139 | # without ext 140 | filename = f.stem 141 | 142 | caption_output_path = output_dir / f"{filename}.{caption_ext}" 143 | 144 | if caption_output_path.exists(): 145 | print(f"File already exists: {caption_output_path}. Skipped.") 146 | continue 147 | 148 | img = Image.open(f) 149 | # fix png 150 | if img.mode == "RGBA": 151 | img = img.convert("RGB") 152 | 153 | caption = generate_caption( 154 | img, 155 | # model_name, 156 | sampling_type=(sampling_type == "Nucleus"), 157 | num_beams=num_beams, 158 | caption_max_length=caption_max_length, 159 | caption_min_length=caption_min_length, 160 | top_p=top_p, 161 | # repitition_penalty=repitition_penalty, 162 | ) 163 | 164 | if caption_ext.startswith("."): # remove dot 165 | caption_ext = caption_ext[1:] 166 | 167 | create_caption_file(caption, caption_output_path) 168 | 169 | print( 170 | f"{f.name}: {caption}" 171 | ) 172 | 173 | print("All done!") 174 | return "Done!" 175 | except Exception as e: 176 | return f"Error: {e}" 177 | 178 | 179 | def on_ui_tabs(): 180 | with gr.Blocks(analytics_enabled=False) as ui: 181 | with gr.Column(): 182 | with gr.Tabs(): 183 | with gr.TabItem(label="Single"): 184 | with gr.Row().style(equal_height=False): 185 | with gr.Column(): 186 | image = gr.Image( 187 | source="upload", 188 | label="Image", 189 | interactive=True, 190 | type="pil", 191 | ) 192 | 193 | # single_model_select = gr.Dropdown( 194 | # label="Model", 195 | # choices=model_list, 196 | # value=model_list[0], 197 | # interactive=True, 198 | # ) 199 | single_start_btn = gr.Button( 200 | value="Interrogate", variant="primary" 201 | ) 202 | 203 | with gr.Column(): 204 | # single_caption_result = gr.TextArea( 205 | # label="Generated Caption", 206 | # value="", 207 | # readonly=True, 208 | # placeholder="No caption yet", 209 | # ) 210 | single_caption_result = gr.Label( 211 | label="Generated Caption", 212 | ) 213 | 214 | with gr.TabItem(label="Batch"): 215 | with gr.Row().style(equal_height=False): 216 | with gr.Column(): 217 | input_dir_input = gr.Textbox( 218 | label="Image Directory", 219 | placeholder="path/to/caption", 220 | type="text", 221 | ) 222 | output_dir_input = gr.Textbox( 223 | label="Output Directory", 224 | placeholder="path/to/output", 225 | type="text", 226 | ) 227 | output_caption_ext = gr.Textbox( 228 | label="Output Caption Extension", 229 | placeholder="txt", 230 | value="txt", 231 | type="text", 232 | ) 233 | 234 | gr.Markdown("") 235 | 236 | batch_start_btn = gr.Button( 237 | value="Interrogate", variant="primary" 238 | ) 239 | 240 | batch_unload_models_btn = gr.Button( 241 | value="Unload models", variant="secondary" 242 | ) 243 | 244 | with gr.Column(): 245 | status_block = gr.Label(label="Status", value="Idle") 246 | 247 | with gr.Row(): 248 | with gr.Column(): 249 | sampling_method_radio = gr.Radio( 250 | label="Sampling method", 251 | choices=sampling_methods, 252 | value=sampling_methods[0], 253 | interactive=True, 254 | ) 255 | 256 | number_of_beams_slider = gr.Slider( 257 | label="Number of beams (0 = no beam search)", 258 | minimum=0, 259 | maximum=10, 260 | step=1, 261 | value=3, 262 | interactive=True, 263 | ) 264 | 265 | with gr.Row(): 266 | caption_min_length_slider = gr.Slider( 267 | label="Caption min length", 268 | minimum=0, 269 | maximum=200, 270 | step=1, 271 | value=10, 272 | interactive=True, 273 | ) 274 | caption_max_length_slider = gr.Slider( 275 | label="Caption max length", 276 | minimum=1, 277 | maximum=200, 278 | step=1, 279 | value=30, 280 | interactive=True, 281 | ) 282 | 283 | top_p_slider = gr.Slider( 284 | label="Top p", 285 | minimum=0.0, 286 | maximum=1.0, 287 | step=0.01, 288 | value=0.9, 289 | interactive=True, 290 | ) 291 | # single_repetition_penalty_slider = gr.Slider( 292 | # label="Repetition penalty (1.0 = no penalty)", 293 | # minimum=0.0, 294 | # maximum=1.0, 295 | # step=0.01, 296 | # value=1.0, 297 | # interactive=True, 298 | # ) 299 | 300 | unload_models_btn = gr.Button( 301 | value="Unload models", variant="secondary" 302 | ) 303 | 304 | gr.Column() 305 | 306 | # commnet out beacause of loading the model twice... 307 | # image.change( 308 | # fn=generate_caption_for_single_image, 309 | # inputs=[ 310 | # image, 311 | # # single_model_select, 312 | # sampling_method_radio, 313 | # number_of_beams_slider, 314 | # caption_max_length_slider, 315 | # caption_min_length_slider, 316 | # top_p_slider, 317 | # # single_repetition_penalty_slider 318 | # ], 319 | # outputs=[single_caption_result], 320 | # ) 321 | 322 | single_start_btn.click( 323 | fn=generate_caption_for_single_image, 324 | inputs=[ 325 | image, 326 | # single_model_select, 327 | sampling_method_radio, 328 | number_of_beams_slider, 329 | caption_max_length_slider, 330 | caption_min_length_slider, 331 | top_p_slider, 332 | # single_repetition_penalty_slider 333 | ], 334 | outputs=[single_caption_result], 335 | ) 336 | unload_models_btn.click( 337 | fn=unload_models, 338 | inputs=[], 339 | outputs=[], 340 | ) 341 | 342 | batch_start_btn.click( 343 | fn=batch_captioning, 344 | inputs=[ 345 | input_dir_input, 346 | output_dir_input, 347 | output_caption_ext, 348 | # batch_model_select, 349 | sampling_method_radio, 350 | number_of_beams_slider, 351 | caption_max_length_slider, 352 | caption_min_length_slider, 353 | top_p_slider, 354 | # batch_repetition_penalty_slider, 355 | ], 356 | outputs=[status_block], 357 | ) 358 | batch_unload_models_btn.click( 359 | fn=unload_models, 360 | inputs=[], 361 | outputs=[], 362 | ) 363 | 364 | return [(ui, "BLIP2 Captioner", "blip2_captioner")] 365 | 366 | 367 | script_callbacks.on_ui_tabs(on_ui_tabs) 368 | --------------------------------------------------------------------------------