File size: 10,578 Bytes
0163a2c
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
import gradio as gr
from modules import script_callbacks, scripts, shared
from modules.processing import (Processed, StableDiffusionProcessing,
                                StableDiffusionProcessingImg2Img)
from modules.scripts import PostprocessBatchListArgs, PostprocessImageArgs

from scripts.animatediff_cn import AnimateDiffControl
from scripts.animatediff_infv2v import AnimateDiffInfV2V
from scripts.animatediff_latent import AnimateDiffI2VLatent
from scripts.animatediff_logger import logger_animatediff as logger
from scripts.animatediff_lora import AnimateDiffLora
from scripts.animatediff_mm import mm_animatediff as motion_module
from scripts.animatediff_prompt import AnimateDiffPromptSchedule
from scripts.animatediff_output import AnimateDiffOutput
from scripts.animatediff_ui import AnimateDiffProcess, AnimateDiffUiGroup, supported_save_formats
from scripts.animatediff_infotext import update_infotext, infotext_pasted
from scripts.animatediff_xyz import patch_xyz, xyz_attrs

script_dir = scripts.basedir()
motion_module.set_script_dir(script_dir)


class AnimateDiffScript(scripts.Script):

    def __init__(self):
        self.lora_hacker = None
        self.cfg_hacker = None
        self.cn_hacker = None
        self.prompt_scheduler = None
        self.hacked = False
        self.infotext_fields: List[Tuple[gr.components.IOComponent, str]] = []
        self.paste_field_names: List[str] = []


    def title(self):
        return "AnimateDiff"


    def show(self, is_img2img):
        return scripts.AlwaysVisible


    def ui(self, is_img2img):
        unit = AnimateDiffUiGroup().render(
            is_img2img,
            motion_module.get_model_dir(),
            self.infotext_fields,
            self.paste_field_names
        )
        return (unit,)

    def before_process(self, p: StableDiffusionProcessing, params: AnimateDiffProcess):
        if p.is_api and isinstance(params, dict):
            self.ad_params = AnimateDiffProcess(**params)
            params = self.ad_params

        # apply XYZ settings
        params.apply_xyz()
        xyz_attrs.clear()

        if params.enable:
            logger.info("AnimateDiff process start.")
            params.set_p(p)
            motion_module.inject(p.sd_model, params.model)
            self.prompt_scheduler = AnimateDiffPromptSchedule()
            self.lora_hacker = AnimateDiffLora(motion_module.mm.is_v2)
            self.lora_hacker.hack()
            self.cfg_hacker = AnimateDiffInfV2V(p, self.prompt_scheduler)
            self.cfg_hacker.hack(params)
            self.cn_hacker = AnimateDiffControl(p, self.prompt_scheduler)
            self.cn_hacker.hack(params)
            update_infotext(p, params)
            self.hacked = True
        elif self.hacked:
            self.cn_hacker.restore()
            self.cfg_hacker.restore()
            self.lora_hacker.restore()
            motion_module.restore(p.sd_model)
            self.hacked = False


    def before_process_batch(self, p: StableDiffusionProcessing, params: AnimateDiffProcess, **kwargs):
        if p.is_api and isinstance(params, dict): params = self.ad_params
        if params.enable and isinstance(p, StableDiffusionProcessingImg2Img) and not hasattr(p, '_animatediff_i2i_batch'):
            AnimateDiffI2VLatent().randomize(p, params)


    def postprocess_batch_list(self, p: StableDiffusionProcessing, pp: PostprocessBatchListArgs, params: AnimateDiffProcess, **kwargs):
        if p.is_api and isinstance(params, dict): params = self.ad_params
        if params.enable:
            self.prompt_scheduler.save_infotext_img(p)


    def postprocess_image(self, p: StableDiffusionProcessing, pp: PostprocessImageArgs, params: AnimateDiffProcess, *args):
        if p.is_api and isinstance(params, dict): params = self.ad_params
        if params.enable and isinstance(p, StableDiffusionProcessingImg2Img) and hasattr(p, '_animatediff_paste_to_full'):
            p.paste_to = p._animatediff_paste_to_full[p.batch_index]


    def postprocess(self, p: StableDiffusionProcessing, res: Processed, params: AnimateDiffProcess):
        if p.is_api and isinstance(params, dict): params = self.ad_params
        if params.enable:
            self.prompt_scheduler.save_infotext_txt(res)
            self.cn_hacker.restore()
            self.cfg_hacker.restore()
            self.lora_hacker.restore()
            motion_module.restore(p.sd_model)
            self.hacked = False
            AnimateDiffOutput().output(p, res, params)
            logger.info("AnimateDiff process end.")


def on_ui_settings():
    section = ("animatediff", "AnimateDiff")
    s3_selection =("animatediff", "AnimateDiff AWS") 
    shared.opts.add_option(
        "animatediff_model_path",
        shared.OptionInfo(
            None,
            "Path to save AnimateDiff motion modules",
            gr.Textbox,
            section=section,
        ),
    )
    shared.opts.add_option(
        "animatediff_default_save_formats",
        shared.OptionInfo(
            ["GIF", "PNG"],
            "Default Save Formats",
            gr.CheckboxGroup,
            {"choices": supported_save_formats},
            section=section
        ).needs_restart()
    )
    shared.opts.add_option(
        "animatediff_optimize_gif_palette",
        shared.OptionInfo(
            False,
            "Calculate the optimal GIF palette, improves quality significantly, removes banding",
            gr.Checkbox,
            section=section
        )
    )
    shared.opts.add_option(
        "animatediff_optimize_gif_gifsicle",
        shared.OptionInfo(
            False,
            "Optimize GIFs with gifsicle, reduces file size",
            gr.Checkbox,
            section=section
        )
    )
    shared.opts.add_option(
        key="animatediff_mp4_crf",
        info=shared.OptionInfo(
            default=23,
            label="MP4 Quality (CRF)",
            component=gr.Slider,
            component_args={
                "minimum": 0,
                "maximum": 51,
                "step": 1},
            section=section
        )
        .link("docs", "https://trac.ffmpeg.org/wiki/Encode/H.264#crf")
        .info("17 for best quality, up to 28 for smaller size")
    )
    shared.opts.add_option(
        key="animatediff_mp4_preset",
        info=shared.OptionInfo(
            default="",
            label="MP4 Encoding Preset",
            component=gr.Dropdown,
            component_args={"choices": ["", 'veryslow', 'slower', 'slow', 'medium', 'fast', 'faster', 'veryfast', 'superfast', 'ultrafast']},
            section=section,
        )
        .link("docs", "https://trac.ffmpeg.org/wiki/Encode/H.264#Preset")
        .info("encoding speed, use the slowest you can tolerate")
    )
    shared.opts.add_option(
        key="animatediff_mp4_tune",
        info=shared.OptionInfo(
            default="",
            label="MP4 Tune encoding for content type",
            component=gr.Dropdown,
            component_args={"choices": ["", "film", "animation", "grain"]},
            section=section
        )
        .link("docs", "https://trac.ffmpeg.org/wiki/Encode/H.264#Tune")
        .info("optimize for specific content types")
    )
    shared.opts.add_option(
        "animatediff_webp_quality",
        shared.OptionInfo(
            80,
            "WebP Quality (if lossless=True, increases compression and CPU usage)",
            gr.Slider,
            {
                "minimum": 1,
                "maximum": 100,
                "step": 1},
            section=section
        )
    )
    shared.opts.add_option(
        "animatediff_webp_lossless",
        shared.OptionInfo(
            False,
            "Save WebP in lossless format (highest quality, largest file size)",
            gr.Checkbox,
            section=section
        )
    )
    shared.opts.add_option(
        "animatediff_save_to_custom",
        shared.OptionInfo(
            False,
            "Save frames to stable-diffusion-webui/outputs/{ txt|img }2img-images/AnimateDiff/{gif filename}/{date} "
            "instead of stable-diffusion-webui/outputs/{ txt|img }2img-images/{date}/.",
            gr.Checkbox,
            section=section
        )
    )
    shared.opts.add_option(
        "animatediff_xformers",
        shared.OptionInfo(
            "Optimize attention layers with xformers",
            "When you have --xformers in your command line args, you want AnimateDiff to ",
            gr.Radio,
            {"choices": ["Optimize attention layers with xformers",
                         "Optimize attention layers with sdp (torch >= 2.0.0 required)",
                         "Do not optimize attention layers"]},
            section=section
        )
    )
    shared.opts.add_option(
        "animatediff_disable_lcm",
        shared.OptionInfo(
            False,
            "Disable LCM",
            gr.Checkbox,
            section=section
        )
    )
    shared.opts.add_option(
        "animatediff_s3_enable",
        shared.OptionInfo(
            False,
            "Enable to Store file in object storage that supports the s3 protocol",
            gr.Checkbox,
            section=s3_selection
        )
    )
    shared.opts.add_option(
        "animatediff_s3_host",
        shared.OptionInfo(
            None,
            "S3 protocol host",
            gr.Textbox,
            section=s3_selection,
        ),
    )
    shared.opts.add_option(
        "animatediff_s3_port",
        shared.OptionInfo(
            None,
            "S3 protocol port",
            gr.Textbox,
            section=s3_selection,
        ),
    )
    shared.opts.add_option(
        "animatediff_s3_access_key",
        shared.OptionInfo(
            None,
            "S3 protocol access_key",
            gr.Textbox,
            section=s3_selection,
        ),
    )
    shared.opts.add_option(
        "animatediff_s3_secret_key",
        shared.OptionInfo(
            None,
            "S3 protocol secret_key",
            gr.Textbox,
            section=s3_selection,
        ),
    )
    shared.opts.add_option(
        "animatediff_s3_storge_bucket",
        shared.OptionInfo(
            None,
            "Bucket for file storage",
            gr.Textbox,
            section=s3_selection,
        ),
    )    

patch_xyz()

script_callbacks.on_ui_settings(on_ui_settings)
script_callbacks.on_after_component(AnimateDiffUiGroup.on_after_component)
script_callbacks.on_before_ui(AnimateDiffUiGroup.on_before_ui)
script_callbacks.on_infotext_pasted(infotext_pasted)