File size: 11,617 Bytes
44d3d88
 
 
 
 
 
 
 
 
 
 
0933cd2
 
 
b31a1c0
 
 
 
 
 
 
44d3d88
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0626ef0
44d3d88
 
 
 
 
b31a1c0
 
44d3d88
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
import os
import glob
import time
import pathlib
import shlex
import subprocess
import gradio as gr
from huggingface_hub import snapshot_download
from datasets import load_from_disk
import random

# Fix the random seed for reproducibility
random.seed(42)  # You can use any fixed number as the seed

# Define common combinations
common_combinations = [
    ("lookaround", "back_and_forth"),  # Most common
    ("lookdown", "back_and_forth"),    # Less common
    ("rotate360", "headbanging")       # Rare
]

# 下载数据集
repo_id = "svjack/3DitScene_cache"
folder_path = "Genshin-Impact-Couple-with-Tags-IID-Gender-Only-Two-Joy-Caption_Head10"
local_dir = snapshot_download(
    repo_id=repo_id,
    repo_type="dataset",
    allow_patterns=f"{folder_path}/*",
    cache_dir=os.getcwd(),
    local_dir="."
)

# 加载数据集
dataset = load_from_disk(folder_path)

# 提取 image 和 joy-caption
examples = []
for example in dataset:
    examples.append({
        'image': example['image'],
        'joy-caption': example['joy_caption_surrounding']
    })

# 为每个例子随机分配 gen_camerapath 和 render_camerapath
examples_with_combinations = []
for example in examples:
    # Randomly select a combination from common_combinations
    gen_camerapath, render_camerapath = random.choice(common_combinations)
    examples_with_combinations.append({
        'image': example['image'],
        'joy-caption': example['joy-caption'],
        'gen_camerapath': gen_camerapath,
        'render_camerapath': render_camerapath
    })

root = pathlib.Path(__file__).parent
example_root = os.path.join(root, 'examples')
ckpt_root = os.path.join(root, 'stablediffusion')

d = example_root
if len(glob.glob(os.path.join(d, '*.ply'))) < 8:
    snapshot_download(repo_id="ironjr/LucidDreamerDemo", repo_type="model", local_dir=d)

d = os.path.join(ckpt_root, 'Blazing Drive V11m')
if not os.path.exists(d):
    snapshot_download(repo_id="ironjr/BlazingDriveV11m", repo_type="model", local_dir=d)
d = os.path.join(ckpt_root, 'RealCartoon-Pixar V5')
if not os.path.exists(d):
    snapshot_download(repo_id="ironjr/RealCartoon-PixarV5", repo_type="model", local_dir=d)
d = os.path.join(ckpt_root, 'Realistic Vision V5.1')
if not os.path.exists(d):
    snapshot_download(repo_id="ironjr/RealisticVisionV5-1", repo_type="model", local_dir=d)
d = os.path.join(ckpt_root, 'SD1-5')

if not os.path.exists(d):
    snapshot_download(repo_id="runwayml/stable-diffusion-inpainting", repo_type="model", local_dir=d)

try:
    import simple_knn
except ModuleNotFoundError:
    subprocess.run(shlex.split(f'pip install {root}/dist/simple_knn-0.0.0-cp39-cp39-linux_x86_64.whl'))
try:
    import depth_diff_gaussian_rasterization_min 
except ModuleNotFoundError:
    subprocess.run(shlex.split(f'pip install {root}/dist/depth_diff_gaussian_rasterization_min-0.0.0-cp39-cp39-linux_x86_64.whl'))

from luciddreamer import LucidDreamer

css = """
#run-button {
  background: coral;
  color: white;
}
"""

save_dir = "local_save"
os.makedirs(save_dir, exist_ok=True)

ld = LucidDreamer(save_dir=save_dir)

with gr.Blocks(css=css) as demo:

    gr.HTML(
        """
        <div style="display: flex; justify-content: center; align-items: center; text-align: center;">
        <div>
            <h1>LucidDreamer: Domain-free Generation of 3D Gaussian Splatting Scenes - Genshin Impact Couple</h1>
            <h5 style="margin: 0;">If you like our project, please visit our Github, too! ✨✨✨ More features are waiting!</h5>
            </br>
            <div style="display: flex; justify-content: center; align-items: center; text-align: center;">
                <a href='https://arxiv.org/abs/2311.13384'>
                    <img src="https://img.shields.io/badge/Arxiv-2311.13384-red">
                </a>
                &nbsp;
                <a href='https://luciddreamer-cvlab.github.io'>
                    <img src='https://img.shields.io/badge/Project-LucidDreamer-green' alt='Project Page'>
                </a>
                &nbsp;
                <a href='https://github.com/luciddreamer-cvlab/LucidDreamer'>
                    <img src='https://img.shields.io/github/stars/luciddreamer-cvlab/LucidDreamer?label=Github&color=blue'>
                </a>
                &nbsp;
                <a href='https://twitter.com/_ironjr_'>
                    <img src='https://img.shields.io/twitter/url?label=_ironjr_&url=https%3A%2F%2Ftwitter.com%2F_ironjr_'>
                </a>
            </div>
            <div style="display: flex; justify-content: center; align-items: center; text-align: left; border: 1px solid lightgray; padding: 10px; margin-top: 20px; margin-left: 100px; margin-right: 100px; border-radius: 10px">
                <p style="align-items: center;">
                <a style="display:inline-block" target="_blank" href="https://huggingface.co/spaces/ironjr/LucidDreamer-mini"><img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-sm.svg"></a>
                <a class="duplicate-button" style="display:inline-block" target="_blank" href="https://huggingface.co/spaces/ironjr/LucidDreamer?duplicate=true"><img style="margin-top:0;margin-bottom:0" src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&amp;style=flat&amp;logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&amp;logoWidth=14" alt="Duplicate Space"></a>
                </p>
                <p style="margin-left: 15px">
                <b>Attention</b>: In case of high traffic, you can alternatively use our backup server (first button: without custom SD support) or clone this repository to run on your own machine (second button). We gratefully welcome any type of your contributions!
                </p>
            </div>
        </div>
        </div>
        """
    )

    with gr.Row():

        result_gallery = gr.Video(label='RGB Video', show_label=True, autoplay=True, format='mp4')

        result_depth = gr.Video(label='Depth Video', show_label=True, autoplay=True, format='mp4')

        result_ply_file = gr.File(label='Gaussian splatting PLY', show_label=True)

    with gr.Row():

        input_image = gr.Image(
            label='Image prompt',
            sources='upload',
            type='pil',
        )

        with gr.Column():
            model_name = gr.Radio(
                label='SD checkpoint',
                choices=['SD1.5 (default)', 'Blazing Drive V11m', 'Realistic Vision V5.1', 'RealCartoon-Pixar V5',],
                value='SD1.5 (default)'
            )
            
            prompt = gr.Textbox(
                label='Text prompt',
                value='A cozy livingroom',
            )
            n_prompt = gr.Textbox(
                label='Negative prompt',
                value='photo frame, frame, boarder, simple color, inconsistent, humans, people',
            )
            gen_camerapath = gr.Radio(
                label='Camera trajectory for generation (STEP 1)',
                choices=['lookaround', 'lookdown', 'rotate360'],
                value='lookaround',
            )
            
            with gr.Row():
                seed = gr.Slider(
                    label='Seed',
                    minimum=1,
                    maximum=2147483647,
                    step=1,
                    randomize=True,
                )
                diff_steps = gr.Slider(
                    label='SD inpainting steps',
                    minimum=1,
                    maximum=50,
                    step=1,
                    value=30,
                )

            render_camerapath = gr.Radio(
                label='Camera trajectory for rendering (STEP 2)',
                choices=['back_and_forth', 'llff', 'headbanging'],
                value='llff',
            )

        with gr.Column():
            run_button = gr.Button(value='Run! (it may take a while)', elem_id='run-button')

            gr.HTML(
                """
                <div style="display: flex; justify-content: center; align-items: center; text-align: center;">
                <div>
                    <h3>...or you can run in two steps</h3>
                    <h5>(hint: press STEP 2 if you have already baked Gaussians in STEP 1).</h5>
                </div>
                </div>
                """
            )

            with gr.Row():
                gaussian_button = gr.Button(value='STEP 1: Generate Gaussians')
                render_button = gr.Button(value='STEP 2: Render A Video')

            gr.HTML(
                """
                <div style="display: flex; justify-content: center; align-items: center; text-align: center;">
                <div>
                    <h5>...or you can just watch a quick preload we have baked already.</h5>
                </div>
                </div>
                """
            )

            example_name = gr.Radio(
                label='Quick load',
                choices=['DON\'T'],
                value='DON\'T',
            )

    ips = [example_name, input_image, prompt, n_prompt, gen_camerapath, seed, diff_steps, render_camerapath, model_name]

    run_button.click(fn=ld.run, inputs=ips[1:] + ips[:1], outputs=[result_ply_file, result_gallery, result_depth])
    gaussian_button.click(fn=ld.create, inputs=ips[1:-2] + ips[-1:] + ips[:1], outputs=[result_ply_file])
    render_button.click(fn=ld.render_video, inputs=ips[-2:-1] + ips[:1], outputs=[result_gallery, result_depth])

    # 替换 examples
    gr.Examples(
        examples=[
            [
                'DON\'T',
                example['image'],
                example['joy-caption'],
                'photo frame, frame, boarder, simple color, inconsistent, humans, people',
                example['gen_camerapath'],  # 随机分配的 gen_camerapath
                10,  # seed
                25,  # diff_steps
                example['render_camerapath'],  # 随机分配的 render_camerapath
                'RealCartoon-Pixar V5',
            ] for example in examples_with_combinations
        ],
        inputs=ips,
        outputs=[result_ply_file, result_gallery, result_depth],
        fn=ld.run,
        cache_examples=False,
    )

    gr.HTML(
        """
        <div style="display: flex; justify-content: center; align-items: center; text-align: left;">
        </br>
        <div>
            <h5 style="margin: 0;">Acknowledgement and Disclaimer</h5>
            </br>
            <p>We deeply thank <a href="https://twitter.com/br_d">br_d</a>, <a href="https://ko-fi.com/7whitefire7">7whitefire7</a>, and <a href="https://huggingface.co/SG161222">SG161222</a> for their awesome Stable Diffusion models. We also appreciate <a href="https://twitter.com/ai_pictures21">ai_pictures21</a> and <a href="https://twitter.com/recatm">recatm</a> for the beautiful illustrations used in the examples. Please note that the authors of this work do not own the model checkpoints and the illustrations in this demo. LucidDreamer algorithm cannot be used for commercial purpose. Please contact the authors for permission requests.</p>
        </div>
        </div>
        """
    )


if __name__ == '__main__':
    demo.launch(share=True)