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SerdarHelli
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b440279
Upload 2 files
Browse files- app.py +45 -53
- example_input.png +0 -0
app.py
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import sys
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import os
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import re
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from typing import List, Optional, Tuple, Union
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import dnnlib
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import numpy as np
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import PIL.Image
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import torch
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from tqdm import tqdm
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import legacy
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from camera_utils import LookAtPoseSampler
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from huggingface_hub import hf_hub_download
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from matplotlib import pyplot as plt
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from pathlib import Path
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import json
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import gradio as gr
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from training.utils import color_mask, color_list
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import plotly.graph_objects as go
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from tqdm import tqdm
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import imageio
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import argparse
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import trimesh
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import pyrender
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import mcubes
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os.environ["PYOPENGL_PLATFORM"] = "egl"
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@@ -198,11 +188,13 @@ def get_all(cfg,input,truncation_psi,mesh_resolution,random_seed,fps,num_frames)
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fig_mesh=return_plot_go(mesh_trimesh)
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return fig_mesh,image_color,image_seg,video,video_label
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[Arxiv: "3D-aware Conditional Image Synthesis".](https://arxiv.org/abs/2302.08509)
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[Project Page.](https://www.cs.cmu.edu/~pix2pix3D/)
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[For the official implementation.](https://github.com/dunbar12138/pix2pix3D)
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### Future Work based on interest
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The process can take long time.Especially ,To generate videos and the time of process depends the number of frames,Mesh Resolution and current compiler device.
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'''
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gr.
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import sys
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import os
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os.system("https://github.com/dunbar12138/pix2pix3D.git")
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sys.path.append("pix2pix3D")
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from typing import List, Optional, Tuple, Union
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import dnnlib
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import numpy as np
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import PIL.Image
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import torch
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from tqdm import tqdm
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import legacy
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from camera_utils import LookAtPoseSampler
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from huggingface_hub import hf_hub_download
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from matplotlib import pyplot as plt
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from pathlib import Path
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import gradio as gr
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from training.utils import color_mask, color_list
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import plotly.graph_objects as go
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from tqdm import tqdm
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import imageio
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import trimesh
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import mcubes
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os.environ["PYOPENGL_PLATFORM"] = "egl"
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fig_mesh=return_plot_go(mesh_trimesh)
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return fig_mesh,image_color,image_seg,video,video_label
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title="3D-aware Conditional Image Synthesis"
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desc=f'''
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[Arxiv: "3D-aware Conditional Image Synthesis".](https://arxiv.org/abs/2302.08509)
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[Project Page.](https://www.cs.cmu.edu/~pix2pix3D/)
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[For the official implementation.](https://github.com/dunbar12138/pix2pix3D)
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### Future Work based on interest
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The process can take long time.Especially ,To generate videos and the time of process depends the number of frames,Mesh Resolution and current compiler device.
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'''
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demo_inputs=[
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gr.Dropdown(choices=["seg2cat"],label="Choose Model",value="seg2cat"),
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gr.Image(type="filepath",shape=(512, 512),label="Mask"),
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gr.Slider( minimum=0, maximum=2,label='Truncation PSI',value=1),
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gr.Slider( minimum=32, maximum=512,label='Mesh Resolution',value=32),
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gr.Slider( minimum=0, maximum=2**16,label='Seed',value=128),
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gr.Slider( minimum=10, maximum=120,label='FPS',value=30),
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gr.Slider( minimum=10, maximum=120,label='The Number of Frames',value=30),
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]
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demo_outputs=[
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gr.Plot(),
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gr.Image(type="pil",shape=(256,256)),
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gr.Image(type="pil",shape=(256,256)),
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gr.Video(),
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gr.Video()
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]
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examples = [
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["seg2cat", "example_input.png", 1, 32, 128, 30, 30],
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]
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demo_app = gr.Interface(
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fn=get_all,
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inputs=demo_inputs,
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outputs=demo_outputs,
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cache_examples=True,
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title=title,
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theme="huggingface",
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description=desc,
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examples=examples,
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cache_examples=True,
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)
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demo_app.launch(debug=True, enable_queue=True)
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example_input.png
ADDED