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Running
on
Zero
| import os | |
| import torch | |
| import sys | |
| # os.system('pip install iopath') | |
| # os.system("pip install -v -v -v 'git+https://github.com/facebookresearch/pytorch3d.git@stable'") | |
| # os.system("cd pytorch3d && pip install -e . && cd ..") | |
| os.system("pip install 'git+https://github.com/facebookresearch/pytorch3d.git'") | |
| import gradio as gr | |
| import random | |
| from viewcrafter import ViewCrafter | |
| from configs.infer_config import get_parser | |
| from huggingface_hub import hf_hub_download | |
| i2v_examples = [ | |
| ['test/images/boy.png', 0, 1.0, '0 40', '0 0', '0 0', 50, 123], | |
| ['test/images/car.jpeg', 0, 1.0, '0 -35', '0 0', '0 -0.1', 50, 123], | |
| ['test/images/fruit.jpg', 0, 1.0, '0 -3 -15 -20 -17 -5 0', '0 -2 -5 -10 -8 -5 0 2 5 3 0', '0 0', 50, 123], | |
| ['test/images/room.png', 5, 1.0, '0 3 10 20 17 10 0', '0 -2 -8 -6 0 2 5 3 0', '0 -0.02 -0.09 -0.16 -0.09 0', 50, 123], | |
| ['test/images/castle.png', 0, 1.0, '0 30', '0 -1 -5 -4 0 1 5 4 0', '0 -0.2', 50, 123], | |
| ] | |
| max_seed = 2 ** 31 | |
| def download_model(): | |
| REPO_ID = 'Drexubery/ViewCrafter_25' | |
| filename_list = ['model.ckpt'] | |
| for filename in filename_list: | |
| local_file = os.path.join('./checkpoints/', filename) | |
| if not os.path.exists(local_file): | |
| hf_hub_download(repo_id=REPO_ID, filename=filename, local_dir='./checkpoints/', force_download=True) | |
| REPO_ID = 'naver/DUSt3R_ViTLarge_BaseDecoder_512_dpt' | |
| download_model() | |
| def viewcrafter_demo(opts): | |
| css = """#input_img {max-width: 1024px !important} #output_vid {max-width: 1024px; max-height:576px} #random_button {max-width: 100px !important}""" | |
| image2video = ViewCrafter(opts, gradio = True) | |
| with gr.Blocks(analytics_enabled=False, css=css) as viewcrafter_iface: | |
| gr.Markdown("<div align='center'> <h1> ViewCrafter: Taming Video Diffusion Models for High-fidelity Novel View Synthesis </span> </h1> \ | |
| <h2 style='font-weight: 450; font-size: 1rem; margin: 0rem'>\ | |
| <a href='https://scholar.google.com/citations?user=UOE8-qsAAAAJ&hl=zh-CN'>Wangbo Yu</a>, \ | |
| <a href='https://doubiiu.github.io/'>Jinbo Xing</a>, <a href=''>Li Yuan</a>, \ | |
| <a href='https://wbhu.github.io/'>Wenbo Hu</a>, <a href='https://xiaoyu258.github.io/'>Xiaoyu Li</a>,\ | |
| <a href=''>Zhipeng Huang</a>, <a href='https://scholar.google.com/citations?user=qgdesEcAAAAJ&hl=en/'>Xiangjun Gao</a>,\ | |
| <a href='https://www.cse.cuhk.edu.hk/~ttwong/myself.html/'>Tien-Tsin Wong</a>,\ | |
| <a href='https://scholar.google.com/citations?hl=en&user=4oXBp9UAAAAJ&view_op=list_works&sortby=pubdate/'>Ying Shan</a>\ | |
| <a href=''>Yonghong Tian</a>\ | |
| </h2> \ | |
| <a style='font-size:18px;color: #FF5DB0' href='https://github.com/Drexubery/ViewCrafter/blob/main/docs/render_help.md'> [Guideline] </a>\ | |
| <a style='font-size:18px;color: #000000' href=''> [ArXiv] </a>\ | |
| <a style='font-size:18px;color: #000000' href='https://drexubery.github.io/ViewCrafter/'> [Project Page] </a>\ | |
| <a style='font-size:18px;color: #000000' href='https://github.com/Drexubery/ViewCrafter'> [Github] </a> </div>") | |
| #######image2video###### | |
| with gr.Tab(label="ViewCrafter_25, 'single_view_txt' mode"): | |
| with gr.Column(): | |
| with gr.Row(): | |
| with gr.Column(): | |
| with gr.Row(): | |
| i2v_input_image = gr.Image(label="Input Image",elem_id="input_img") | |
| with gr.Row(): | |
| i2v_elevation = gr.Slider(minimum=-45, maximum=45, step=1, elem_id="elevation", label="elevation", value=5) | |
| with gr.Row(): | |
| i2v_center_scale = gr.Slider(minimum=0.1, maximum=2, step=0.1, elem_id="i2v_center_scale", label="center_scale", value=1) | |
| with gr.Row(): | |
| i2v_d_phi = gr.Text(label='d_phi sequence, should start with 0') | |
| with gr.Row(): | |
| i2v_d_theta = gr.Text(label='d_theta sequence, should start with 0') | |
| with gr.Row(): | |
| i2v_d_r = gr.Text(label='d_r sequence, should start with 0') | |
| with gr.Row(): | |
| i2v_steps = gr.Slider(minimum=1, maximum=50, step=1, elem_id="i2v_steps", label="Sampling steps", value=50) | |
| with gr.Row(): | |
| i2v_seed = gr.Slider(label='Random Seed', minimum=0, maximum=max_seed, step=1, value=123) | |
| i2v_end_btn = gr.Button("Generate") | |
| # with gr.Tab(label='Result'): | |
| with gr.Column(): | |
| with gr.Row(): | |
| i2v_traj_video = gr.Video(label="Camera Trajectory",elem_id="traj_vid",autoplay=True,show_share_button=True) | |
| with gr.Row(): | |
| i2v_output_video = gr.Video(label="Generated Video",elem_id="output_vid",autoplay=True,show_share_button=True) | |
| gr.Examples(examples=i2v_examples, | |
| inputs=[i2v_input_image, i2v_elevation, i2v_center_scale, i2v_d_phi, i2v_d_theta, i2v_d_r, i2v_steps, i2v_seed], | |
| outputs=[i2v_traj_video,i2v_output_video], | |
| fn = image2video.run_gradio, | |
| cache_examples=False, | |
| ) | |
| # image2video.run_gradio(i2v_input_image='test/images/boy.png', i2v_elevation='10', i2v_d_phi='0 40', i2v_d_theta='0 0', i2v_d_r='0 0', i2v_center_scale=1, i2v_steps=50, i2v_seed=123) | |
| i2v_end_btn.click(inputs=[i2v_input_image, i2v_elevation, i2v_center_scale, i2v_d_phi, i2v_d_theta, i2v_d_r, i2v_steps, i2v_seed], | |
| outputs=[i2v_traj_video,i2v_output_video], | |
| fn = image2video.run_gradio | |
| ) | |
| return viewcrafter_iface | |
| if __name__ == "__main__": | |
| parser = get_parser() # infer_config.py | |
| opts = parser.parse_args() # default device: 'cuda:0' | |
| opts.save_dir = './' | |
| os.makedirs(opts.save_dir,exist_ok=True) | |
| test_tensor = torch.Tensor([0]).cuda() | |
| opts.device = str(test_tensor.device) | |
| viewcrafter_iface = viewcrafter_demo(opts) | |
| viewcrafter_iface.queue(max_size=10) | |
| viewcrafter_iface.launch() | |
| # viewcrafter_iface.launch(server_name='127.0.0.1', server_port=80, max_threads=1,debug=False) | |