Spaces:
Runtime error
Runtime error
| import argparse | |
| import os | |
| import tempfile | |
| from functools import partial | |
| import cv2 | |
| import gradio as gr | |
| import imageio | |
| import numpy as np | |
| import torch | |
| import torchvision | |
| from omegaconf import OmegaConf | |
| from PIL import Image | |
| from pytorch_lightning import seed_everything | |
| from gradio_utils.camera_utils import CAMERA_MOTION_MODE, process_camera | |
| from gradio_utils.traj_utils import (OBJECT_MOTION_MODE, get_provided_traj, | |
| process_points, process_traj) | |
| from gradio_utils.utils import vis_camera | |
| from lvdm.models.samplers.ddim import DDIMSampler | |
| from main.evaluation.motionctrl_inference import (DEFAULT_NEGATIVE_PROMPT, | |
| load_model_checkpoint, | |
| post_prompt) | |
| from utils.utils import instantiate_from_config | |
| os.environ['KMP_DUPLICATE_LIB_OK']='True' | |
| #### Description #### | |
| title = r"""<h1 align="center">MotionCtrl: A Unified and Flexible Motion Controller for Video Generation</h1>""" | |
| description = r""" | |
| <b>Official Gradio demo</b> for <a href='https://github.com/TencentARC/MotionCtrl' target='_blank'><b>MotionCtrl: A Unified and Flexible Motion Controller for Video Generation</b></a>.<br> | |
| 🔥 MotionCtrl is capable of independently and flexibly controling the camera motion and object motion of a generated video, with only a unified model.<br> | |
| 🤗 Try to control the motion of the generated videos yourself!<br> | |
| ❗❗❗ Please note that current version of **MotionCtrl** is deployed on **LVDM/VideoCrafter**. The versions that depolyed on **AnimateDiff** and **SVD** will be released soon.<br> | |
| """ | |
| article = r""" | |
| If MotionCtrl is helpful, please help to ⭐ the <a href='https://github.com/TencentARC/MotionCtrl' target='_blank'>Github Repo</a>. Thanks! | |
| [](https://github.com/TencentARC/MotionCtrl) | |
| --- | |
| 📝 **Citation** | |
| <br> | |
| If our work is useful for your research, please consider citing: | |
| ```bibtex | |
| @inproceedings{wang2023motionctrl, | |
| title={MotionCtrl: A Unified and Flexible Motion Controller for Video Generation}, | |
| author={Wang, Zhouxia and Yuan, Ziyang and Wang, Xintao and Chen, Tianshui and Xia, Menghan and Luo, Ping and Shan, Yin}, | |
| booktitle={arXiv preprint arXiv:2312.03641}, | |
| year={2023} | |
| } | |
| ``` | |
| 📧 **Contact** | |
| <br> | |
| If you have any questions, please feel free to reach me out at <b>wzhoux@connect.hku.hk</b>. | |
| """ | |
| css = """ | |
| .gradio-container {width: 85% !important} | |
| .gr-monochrome-group {border-radius: 5px !important; border: revert-layer !important; border-width: 2px !important; color: black !important;} | |
| span.svelte-s1r2yt {font-size: 17px !important; font-weight: bold !important; color: #d30f2f !important;} | |
| button {border-radius: 8px !important;} | |
| .add_button {background-color: #4CAF50 !important;} | |
| .remove_button {background-color: #f44336 !important;} | |
| .clear_button {background-color: gray !important;} | |
| .mask_button_group {gap: 10px !important;} | |
| .video {height: 300px !important;} | |
| .image {height: 300px !important;} | |
| .video .wrap.svelte-lcpz3o {display: flex !important; align-items: center !important; justify-content: center !important;} | |
| .video .wrap.svelte-lcpz3o > :first-child {height: 100% !important;} | |
| .margin_center {width: 50% !important; margin: auto !important;} | |
| .jc_center {justify-content: center !important;} | |
| """ | |
| T_base = [ | |
| [1.,0.,0.], ## W2C x 的正方向： 相机朝左 left | |
| [-1.,0.,0.], ## W2C x 的负方向： 相机朝右 right | |
| [0., 1., 0.], ## W2C y 的正方向： 相机朝上 up | |
| [0.,-1.,0.], ## W2C y 的负方向： 相机朝下 down | |
| [0.,0.,1.], ## W2C z 的正方向： 相机往前 zoom out | |
| [0.,0.,-1.], ## W2C z 的负方向： 相机往前 zoom in | |
| ] | |
| radius = 1 | |
| n = 16 | |
| # step = | |
| look_at = np.array([0, 0, 0.8]).reshape(3,1) | |
| # look_at = np.array([0, 0, 0.2]).reshape(3,1) | |
| T_list = [] | |
| base_R = np.array([[1., 0., 0.], | |
| [0., 1., 0.], | |
| [0., 0., 1.]]) | |
| res = [] | |
| res_forsave = [] | |
| T_range = 1.8 | |
| for i in range(0, 16): | |
| # theta = (1)*np.pi*i/n | |
| R = base_R[:,:3] | |
| T = np.array([0.,0.,1.]).reshape(3,1) * (i/n)*2 | |
| RT = np.concatenate([R,T], axis=1) | |
| res.append(RT) | |
| fig = vis_camera(res) | |
| # MODE = ["camera motion control", "object motion control", "camera + object motion control"] | |
| MODE = ["control camera poses", "control object trajectory", "control both camera and object motion"] | |
| BASE_MODEL = ['LVDM/VideoCrafter', 'AnimateDiff', 'SVD'] | |
| traj_list = [] | |
| camera_dict = { | |
| "motion":[], | |
| "mode": "Customized Mode 1: First A then B", # "First A then B", "Both A and B", "Custom" | |
| "speed": 1.0, | |
| "complex": None | |
| } | |
| def fn_vis_camera(info_mode): | |
| global camera_dict | |
| RT = process_camera(camera_dict) # [t, 3, 4] | |
| if camera_dict['complex'] is not None: | |
| # rescale T to [-2,2] | |
| for i in range(3): | |
| min_T = np.min(RT[:,i,-1]) | |
| max_T = np.max(RT[:,i,-1]) | |
| if min_T < -2 or max_T > 2: | |
| RT[:,i,-1] = RT[:,i,-1] - min_T | |
| RT[:,i,-1] = RT[:,i,-1] / (np.max(RT[:,:,-1]) + 1e-6) | |
| RT[:,i,-1] = RT[:,i,-1] * 4 | |
| RT[:,i,-1] = RT[:,i,-1] - 2 | |
| fig = vis_camera(RT) | |
| if info_mode == MODE[0]: | |
| vis_step3_prompt_generate = True | |
| vis_prompt = True | |
| vis_num_samples = True | |
| vis_seed = True | |
| vis_start = True | |
| vis_gen_video = True | |
| vis_object_mode = False | |
| vis_object_info = False | |
| else: | |
| vis_step3_prompt_generate = False | |
| vis_prompt = False | |
| vis_num_samples = False | |
| vis_seed = False | |
| vis_start = False | |
| vis_gen_video = False | |
| vis_object_mode = True | |
| vis_object_info = True | |
| return fig, \ | |
| gr.update(visible=vis_object_mode), \ | |
| gr.update(visible=vis_object_info), \ | |
| gr.update(visible=vis_step3_prompt_generate), \ | |
| gr.update(visible=vis_prompt), \ | |
| gr.update(visible=vis_num_samples), \ | |
| gr.update(visible=vis_seed), \ | |
| gr.update(visible=vis_start), \ | |
| gr.update(visible=vis_gen_video, value=None) | |
| def fn_vis_traj(): | |
| global traj_list | |
| xy_range = 1024 | |
| points = process_points(traj_list) | |
| imgs = [] | |
| for idx in range(16): | |
| bg_img = np.ones((1024, 1024, 3), dtype=np.uint8) * 255 | |
| for i in range(15): | |
| p = points[i] | |
| p1 = points[i+1] | |
| cv2.line(bg_img, p, p1, (255, 0, 0), 2) | |
| if i == idx: | |
| cv2.circle(bg_img, p, 2, (0, 255, 0), 20) | |
| if idx==(15): | |
| cv2.circle(bg_img, points[-1], 2, (0, 255, 0), 20) | |
| imgs.append(bg_img.astype(np.uint8)) | |
| # size = (512, 512) | |
| fps = 10 | |
| path = tempfile.NamedTemporaryFile(suffix='.mp4', delete=False).name | |
| writer = imageio.get_writer(path, format='mp4', mode='I', fps=fps) | |
| for img in imgs: | |
| writer.append_data(img) | |
| writer.close() | |
| vis_step3_prompt_generate = True | |
| vis_prompt = True | |
| vis_num_samples = True | |
| vis_seed = True | |
| vis_start = True | |
| vis_gen_video = True | |
| return path, gr.update(visible=vis_step3_prompt_generate), \ | |
| gr.update(visible=vis_prompt), \ | |
| gr.update(visible=vis_num_samples), \ | |
| gr.update(visible=vis_seed), \ | |
| gr.update(visible=vis_start), \ | |
| gr.update(visible=vis_gen_video, value=None) | |
| def display_camera_info(camera_dict, camera_mode=None): | |
| if camera_dict['complex'] is not None: | |
| res = f"complex : {camera_dict['complex']}. " | |
| else: | |
| res = "" | |
| res += f"motion : {[_ for _ in camera_dict['motion']]}. " | |
| res += f"speed : {camera_dict['speed']}. " | |
| if camera_mode == 'Custom Camera Poses': | |
| res += f"mode : {camera_dict['mode']}. " | |
| return res | |
| def add_traj_point(evt: gr.SelectData, ): | |
| global traj_list | |
| traj_list.append(evt.index) | |
| traj_str = [f"{traj}" for traj in traj_list] | |
| return ", ".join(traj_str) | |
| def add_provided_traj(traj_name): | |
| global traj_list | |
| traj_list = get_provided_traj(traj_name) | |
| traj_str = [f"{traj}" for traj in traj_list] | |
| return ", ".join(traj_str) | |
| def add_camera_motion(camera_motion, camera_mode): | |
| global camera_dict | |
| if camera_dict['complex'] is not None: | |
| camera_dict['complex'] = None | |
| if camera_mode == 'Custom Camera Poses' and len(camera_dict['motion']) <2: | |
| camera_dict['motion'].append(camera_motion) | |
| else: | |
| camera_dict['motion']=[camera_motion] | |
| return display_camera_info(camera_dict, camera_mode) | |
| def add_complex_camera_motion(camera_motion): | |
| global camera_dict | |
| camera_dict['complex']=camera_motion | |
| return display_camera_info(camera_dict) | |
| def change_camera_mode(combine_type, camera_mode): | |
| global camera_dict | |
| camera_dict['mode'] = combine_type | |
| return display_camera_info(camera_dict, camera_mode) | |
| def change_camera_speed(camera_speed): | |
| global camera_dict | |
| camera_dict['speed'] = camera_speed | |
| return display_camera_info(camera_dict) | |
| def reset_camera(): | |
| global camera_dict | |
| camera_dict = { | |
| "motion":[], | |
| "mode": "Customized Mode 1: First A then B", | |
| "speed": 1.0, | |
| "complex": None | |
| } | |
| return display_camera_info(camera_dict) | |
| def fn_traj_droplast(): | |
| global traj_list | |
| if traj_list: | |
| traj_list.pop() | |
| if traj_list: | |
| traj_str = [f"{traj}" for traj in traj_list] | |
| return ", ".join(traj_str) | |
| else: | |
| return "Click to specify trajectory" | |
| def fn_traj_reset(): | |
| global traj_list | |
| traj_list = [] | |
| return "Click to specify trajectory" | |
| ########################################### | |
| model_path='./motionctrl.pth?download=true' | |
| config_path='./configs/inference/config_both.yaml' | |
| if not os.path.exists(model_path): | |
| os.system(f'wget https://huggingface.co/TencentARC/MotionCtrl/resolve/main/motionctrl.pth?download=true -P .') | |
| config = OmegaConf.load(config_path) | |
| model_config = config.pop("model", OmegaConf.create()) | |
| model = instantiate_from_config(model_config) | |
| if torch.cuda.is_available(): | |
| model = model.cuda() | |
| model = load_model_checkpoint(model, model_path) | |
| model.eval() | |
| def model_run(prompts, infer_mode, seed, n_samples): | |
| global traj_list | |
| global camera_dict | |
| RT = process_camera(camera_dict).reshape(-1,12) | |
| traj_flow = process_traj(traj_list).transpose(3,0,1,2) | |
| print(prompts) | |
| print(RT.shape) | |
| print(traj_flow.shape) | |
| noise_shape = [1, 4, 16, 32, 32] | |
| unconditional_guidance_scale = 7.5 | |
| unconditional_guidance_scale_temporal = None | |
| # n_samples = 1 | |
| ddim_steps= 50 | |
| ddim_eta=1.0 | |
| cond_T=800 | |
| if n_samples < 1: | |
| n_samples = 1 | |
| if n_samples > 4: | |
| n_samples = 4 | |
| seed_everything(seed) | |
| if infer_mode == MODE[0]: | |
| camera_poses = RT | |
| camera_poses = torch.tensor(camera_poses).float() | |
| camera_poses = camera_poses.unsqueeze(0) | |
| trajs = None | |
| if torch.cuda.is_available(): | |
| camera_poses = camera_poses.cuda() | |
| elif infer_mode == MODE[1]: | |
| trajs = traj_flow | |
| trajs = torch.tensor(trajs).float() | |
| trajs = trajs.unsqueeze(0) | |
| camera_poses = None | |
| if torch.cuda.is_available(): | |
| trajs = trajs.cuda() | |
| else: | |
| camera_poses = RT | |
| trajs = traj_flow | |
| camera_poses = torch.tensor(camera_poses).float() | |
| trajs = torch.tensor(trajs).float() | |
| camera_poses = camera_poses.unsqueeze(0) | |
| trajs = trajs.unsqueeze(0) | |
| if torch.cuda.is_available(): | |
| camera_poses = camera_poses.cuda() | |
| trajs = trajs.cuda() | |
| ddim_sampler = DDIMSampler(model) | |
| batch_size = noise_shape[0] | |
| ## get condition embeddings (support single prompt only) | |
| if isinstance(prompts, str): | |
| prompts = [prompts] | |
| for i in range(len(prompts)): | |
| prompts[i] = f'{prompts[i]}, {post_prompt}' | |
| cond = model.get_learned_conditioning(prompts) | |
| if camera_poses is not None: | |
| RT = camera_poses[..., None] | |
| else: | |
| RT = None | |
| if trajs is not None: | |
| traj_features = model.get_traj_features(trajs) | |
| else: | |
| traj_features = None | |
| if unconditional_guidance_scale != 1.0: | |
| # prompts = batch_size * [""] | |
| prompts = batch_size * [DEFAULT_NEGATIVE_PROMPT] | |
| uc = model.get_learned_conditioning(prompts) | |
| if traj_features is not None: | |
| un_motion = model.get_traj_features(torch.zeros_like(trajs)) | |
| else: | |
| un_motion = None | |
| uc = {"features_adapter": un_motion, "uc": uc} | |
| else: | |
| uc = None | |
| batch_variants = [] | |
| for _ in range(n_samples): | |
| if ddim_sampler is not None: | |
| samples, _ = ddim_sampler.sample(S=ddim_steps, | |
| conditioning=cond, | |
| batch_size=noise_shape[0], | |
| shape=noise_shape[1:], | |
| verbose=False, | |
| unconditional_guidance_scale=unconditional_guidance_scale, | |
| unconditional_conditioning=uc, | |
| eta=ddim_eta, | |
| temporal_length=noise_shape[2], | |
| conditional_guidance_scale_temporal=unconditional_guidance_scale_temporal, | |
| features_adapter=traj_features, | |
| pose_emb=RT, | |
| cond_T=cond_T | |
| ) | |
| ## reconstruct from latent to pixel space | |
| batch_images = model.decode_first_stage(samples) | |
| batch_variants.append(batch_images) | |
| ## variants, batch, c, t, h, w | |
| batch_variants = torch.stack(batch_variants, dim=1) | |
| batch_variants = batch_variants[0] | |
| # file_path = save_results(batch_variants, "MotionCtrl", "gradio_temp", fps=10) | |
| file_path = save_results(batch_variants, fps=10) | |
| print(file_path) | |
| return gr.update(value=file_path, width=256*n_samples, height=256) | |
| # return file_path | |
| def save_results(video, fps=10): | |
| # b,c,t,h,w | |
| video = video.detach().cpu() | |
| video = torch.clamp(video.float(), -1., 1.) | |
| n = video.shape[0] | |
| video = video.permute(2, 0, 1, 3, 4) # t,n,c,h,w | |
| frame_grids = [torchvision.utils.make_grid(framesheet, nrow=int(n)) for framesheet in video] #[3, 1*h, n*w] | |
| grid = torch.stack(frame_grids, dim=0) # stack in temporal dim [t, 3, n*h, w] | |
| grid = (grid + 1.0) / 2.0 | |
| grid = (grid * 255).to(torch.uint8).permute(0, 2, 3, 1) # [t, h, w*n, 3] | |
| path = tempfile.NamedTemporaryFile(suffix='.mp4', delete=False).name | |
| writer = imageio.get_writer(path, format='mp4', mode='I', fps=fps) | |
| for i in range(grid.shape[0]): | |
| img = grid[i].numpy() | |
| writer.append_data(img) | |
| writer.close() | |
| return path | |
| def visualized_step2(infer_mode): | |
| # reset | |
| reset_camera() | |
| fn_traj_reset() | |
| # camera motion control | |
| vis_basic_camera_motion = False | |
| vis_basic_camera_motion_des = False | |
| vis_custom_camera_motion = False | |
| vis_custom_run_status = False | |
| vis_complex_camera_motion = False | |
| vis_complex_camera_motion_des = False | |
| vis_U = False | |
| vis_D = False | |
| vis_L = False | |
| vis_R = False | |
| vis_I = False | |
| vis_O = False | |
| vis_ACW = False | |
| vis_CW = False | |
| vis_combine1 = False | |
| vis_combine2 = False | |
| vis_speed = False | |
| vis_Pose_1, vis_Pose_2, vis_Pose_3, vis_Pose_4 = False, False, False, False | |
| vis_Pose_5, vis_Pose_6, vis_Pose_7, vis_Pose_8 = False, False, False, False | |
| vis_camera_args = False | |
| vis_camera_reset = False | |
| vis_camera_vis = False | |
| vis_vis_camera = False | |
| # object motion control | |
| vis_provided_traj = False | |
| vis_provided_traj_des = False | |
| vis_draw_yourself = False | |
| vis_draw_run_status = False | |
| vis_traj_1, vis_traj_2, vis_traj_3, vis_traj_4 = False, False, False, False | |
| vis_traj_5, vis_traj_6, vis_traj_7, vis_traj_8 = False, False, False, False | |
| traj_args = False | |
| traj_droplast, traj_reset = False, False | |
| traj_vis = False | |
| traj_input, vis_traj = False, False | |
| # generate video | |
| vis_step3_prompt_generate = False | |
| vis_prompt = False | |
| vis_num_samples = False | |
| vis_seed = False | |
| vis_start = False | |
| vis_gen_video = False | |
| if infer_mode == MODE[0]: | |
| vis_step2_camera_motion = True | |
| vis_step2_camera_motion_des = True | |
| vis_camera_mode = True | |
| vis_camera_info = True | |
| vis_step2_object_motion = False | |
| vis_step2_object_motion_des = False | |
| vis_traj_mode = False | |
| vis_traj_info = False | |
| step2_camera_object_motion = False | |
| step2_camera_object_motion_des = False | |
| elif infer_mode == MODE[1]: | |
| vis_step2_camera_motion = False | |
| vis_step2_camera_motion_des = False | |
| vis_camera_mode = False | |
| vis_camera_info = False | |
| vis_step2_object_motion = True | |
| vis_step2_object_motion_des = True | |
| vis_traj_mode = True | |
| vis_traj_info = True | |
| step2_camera_object_motion = False | |
| step2_camera_object_motion_des = False | |
| else: #infer_mode == MODE[2]: | |
| vis_step2_camera_motion = False | |
| vis_step2_camera_motion_des = False | |
| vis_camera_mode = False | |
| vis_camera_info = False | |
| vis_step2_object_motion = False | |
| vis_step2_object_motion_des = False | |
| vis_traj_mode = False | |
| vis_traj_info = False | |
| step2_camera_object_motion = True | |
| step2_camera_object_motion_des = True | |
| vis_basic_camera_motion = True | |
| vis_basic_camera_motion_des = True | |
| vis_U = True | |
| vis_D = True | |
| vis_L = True | |
| vis_R = True | |
| vis_I = True | |
| vis_O = True | |
| vis_ACW = True | |
| vis_CW = True | |
| vis_speed = True | |
| vis_camera_args = True | |
| vis_camera_reset = True | |
| vis_camera_vis = True | |
| vis_vis_camera = True | |
| return gr.update(visible=vis_step2_camera_motion), \ | |
| gr.update(visible=vis_step2_camera_motion_des), \ | |
| gr.update(visible=vis_camera_mode), \ | |
| gr.update(visible=vis_camera_info), \ | |
| gr.update(visible=vis_basic_camera_motion), \ | |
| gr.update(visible=vis_basic_camera_motion_des), \ | |
| gr.update(visible=vis_custom_camera_motion), \ | |
| gr.update(visible=vis_custom_run_status), \ | |
| gr.update(visible=vis_complex_camera_motion), \ | |
| gr.update(visible=vis_complex_camera_motion_des), \ | |
| gr.update(visible=vis_U), gr.update(visible=vis_D), gr.update(visible=vis_L), gr.update(visible=vis_R), \ | |
| gr.update(visible=vis_I), gr.update(visible=vis_O), gr.update(visible=vis_ACW), gr.update(visible=vis_CW), \ | |
| gr.update(visible=vis_combine1), gr.update(visible=vis_combine2), \ | |
| gr.update(visible=vis_speed), \ | |
| gr.update(visible=vis_Pose_1), gr.update(visible=vis_Pose_2), gr.update(visible=vis_Pose_3), gr.update(visible=vis_Pose_4), \ | |
| gr.update(visible=vis_Pose_5), gr.update(visible=vis_Pose_6), gr.update(visible=vis_Pose_7), gr.update(visible=vis_Pose_8), \ | |
| gr.update(visible=vis_camera_args, value=None), \ | |
| gr.update(visible=vis_camera_reset), gr.update(visible=vis_camera_vis), \ | |
| gr.update(visible=vis_vis_camera, value=None), \ | |
| gr.update(visible=vis_step2_object_motion), \ | |
| gr.update(visible=vis_step2_object_motion_des), \ | |
| gr.update(visible=vis_traj_mode), \ | |
| gr.update(visible=vis_traj_info), \ | |
| gr.update(visible=vis_provided_traj), \ | |
| gr.update(visible=vis_provided_traj_des), \ | |
| gr.update(visible=vis_draw_yourself), \ | |
| gr.update(visible=vis_draw_run_status), \ | |
| gr.update(visible=vis_traj_1), gr.update(visible=vis_traj_2), gr.update(visible=vis_traj_3), gr.update(visible=vis_traj_4), \ | |
| gr.update(visible=vis_traj_5), gr.update(visible=vis_traj_6), gr.update(visible=vis_traj_7), gr.update(visible=vis_traj_8), \ | |
| gr.update(visible=traj_args), \ | |
| gr.update(visible=traj_droplast), gr.update(visible=traj_reset), \ | |
| gr.update(visible=traj_vis), \ | |
| gr.update(visible=traj_input), gr.update(visible=vis_traj, value=None), \ | |
| gr.update(visible=step2_camera_object_motion), \ | |
| gr.update(visible=step2_camera_object_motion_des), \ | |
| gr.update(visible=vis_step3_prompt_generate), \ | |
| gr.update(visible=vis_prompt), \ | |
| gr.update(visible=vis_num_samples), \ | |
| gr.update(visible=vis_seed), \ | |
| gr.update(visible=vis_start), \ | |
| gr.update(visible=vis_gen_video) | |
| def visualized_camera_poses(step2_camera_motion): | |
| reset_camera() | |
| # generate video | |
| vis_step3_prompt_generate = False | |
| vis_prompt = False | |
| vis_num_samples = False | |
| vis_seed = False | |
| vis_start = False | |
| vis_gen_video = False | |
| if step2_camera_motion == CAMERA_MOTION_MODE[0]: | |
| vis_basic_camera_motion = True | |
| vis_basic_camera_motion_des = True | |
| vis_custom_camera_motion = False | |
| vis_custom_run_status = False | |
| vis_complex_camera_motion = False | |
| vis_complex_camera_motion_des = False | |
| vis_U = True | |
| vis_D = True | |
| vis_L = True | |
| vis_R = True | |
| vis_I = True | |
| vis_O = True | |
| vis_ACW = True | |
| vis_CW = True | |
| vis_combine1 = False | |
| vis_combine2 = False | |
| vis_speed = True | |
| vis_Pose_1, vis_Pose_2, vis_Pose_3, vis_Pose_4 = False, False, False, False | |
| vis_Pose_5, vis_Pose_6, vis_Pose_7, vis_Pose_8 = False, False, False, False | |
| elif step2_camera_motion == CAMERA_MOTION_MODE[1]: | |
| vis_basic_camera_motion = False | |
| vis_basic_camera_motion_des = False | |
| vis_custom_camera_motion = False | |
| vis_custom_run_status = False | |
| vis_complex_camera_motion = True | |
| vis_complex_camera_motion_des = True | |
| vis_U = False | |
| vis_D = False | |
| vis_L = False | |
| vis_R = False | |
| vis_I = False | |
| vis_O = False | |
| vis_ACW = False | |
| vis_CW = False | |
| vis_combine1 = False | |
| vis_combine2 = False | |
| vis_speed = False | |
| vis_Pose_1, vis_Pose_2, vis_Pose_3, vis_Pose_4 = True, True, True, True | |
| vis_Pose_5, vis_Pose_6, vis_Pose_7, vis_Pose_8 = True, True, True, True | |
| else: # step2_camera_motion = CAMERA_MOTION_MODE[2]: | |
| vis_basic_camera_motion = False | |
| vis_basic_camera_motion_des = False | |
| vis_custom_camera_motion = True | |
| vis_custom_run_status = True | |
| vis_complex_camera_motion = False | |
| vis_complex_camera_motion_des = False | |
| vis_U = True | |
| vis_D = True | |
| vis_L = True | |
| vis_R = True | |
| vis_I = True | |
| vis_O = True | |
| vis_ACW = True | |
| vis_CW = True | |
| vis_combine1 = True | |
| vis_combine2 = True | |
| vis_speed = True | |
| vis_Pose_1, vis_Pose_2, vis_Pose_3, vis_Pose_4 = False, False, False, False | |
| vis_Pose_5, vis_Pose_6, vis_Pose_7, vis_Pose_8 = False, False, False, False | |
| vis_camera_args = True | |
| vis_camera_reset = True | |
| vis_camera_vis = True | |
| vis_vis_camera = True | |
| return gr.update(visible=vis_basic_camera_motion), \ | |
| gr.update(visible=vis_basic_camera_motion_des), \ | |
| gr.update(visible=vis_custom_camera_motion), \ | |
| gr.update(visible=vis_custom_run_status), \ | |
| gr.update(visible=vis_complex_camera_motion), \ | |
| gr.update(visible=vis_complex_camera_motion_des), \ | |
| gr.update(visible=vis_U), gr.update(visible=vis_D), gr.update(visible=vis_L), gr.update(visible=vis_R), \ | |
| gr.update(visible=vis_I), gr.update(visible=vis_O), gr.update(visible=vis_ACW), gr.update(visible=vis_CW), \ | |
| gr.update(visible=vis_combine1), gr.update(visible=vis_combine2), \ | |
| gr.update(visible=vis_speed), \ | |
| gr.update(visible=vis_Pose_1), gr.update(visible=vis_Pose_2), gr.update(visible=vis_Pose_3), gr.update(visible=vis_Pose_4), \ | |
| gr.update(visible=vis_Pose_5), gr.update(visible=vis_Pose_6), gr.update(visible=vis_Pose_7), gr.update(visible=vis_Pose_8), \ | |
| gr.update(visible=vis_camera_args, value=None), \ | |
| gr.update(visible=vis_camera_reset), gr.update(visible=vis_camera_vis), \ | |
| gr.update(visible=vis_vis_camera, value=None), \ | |
| gr.update(visible=vis_step3_prompt_generate), \ | |
| gr.update(visible=vis_prompt), \ | |
| gr.update(visible=vis_num_samples), \ | |
| gr.update(visible=vis_seed), \ | |
| gr.update(visible=vis_start), \ | |
| gr.update(visible=vis_gen_video) | |
| def visualized_traj_poses(step2_object_motion): | |
| fn_traj_reset() | |
| # generate video | |
| vis_step3_prompt_generate = False | |
| vis_prompt = False | |
| vis_num_samples = False | |
| vis_seed = False | |
| vis_start = False | |
| vis_gen_video = False | |
| if step2_object_motion == "Provided Trajectory": | |
| vis_provided_traj = True | |
| vis_provided_traj_des = True | |
| vis_draw_yourself = False | |
| vis_draw_run_status = False | |
| vis_traj_1, vis_traj_2, vis_traj_3, vis_traj_4 = True, True, True, True | |
| vis_traj_5, vis_traj_6, vis_traj_7, vis_traj_8 = True, True, True, True | |
| traj_args = True | |
| traj_droplast, traj_reset = False, True | |
| traj_vis = True | |
| traj_input, vis_traj = False, True | |
| elif step2_object_motion == "Custom Trajectory": | |
| vis_provided_traj = False | |
| vis_provided_traj_des = False | |
| vis_draw_yourself = True | |
| vis_draw_run_status = True | |
| vis_traj_1, vis_traj_2, vis_traj_3, vis_traj_4 = False, False, False, False | |
| vis_traj_5, vis_traj_6, vis_traj_7, vis_traj_8 = False, False, False, False | |
| traj_args = True | |
| traj_droplast, traj_reset = True, True | |
| traj_vis = True | |
| traj_input, vis_traj = True, True | |
| return gr.update(visible=vis_provided_traj), \ | |
| gr.update(visible=vis_provided_traj_des), \ | |
| gr.update(visible=vis_draw_yourself), \ | |
| gr.update(visible=vis_draw_run_status), \ | |
| gr.update(visible=vis_traj_1), gr.update(visible=vis_traj_2), gr.update(visible=vis_traj_3), gr.update(visible=vis_traj_4), \ | |
| gr.update(visible=vis_traj_5), gr.update(visible=vis_traj_6), gr.update(visible=vis_traj_7), gr.update(visible=vis_traj_8), \ | |
| gr.update(visible=traj_args), \ | |
| gr.update(visible=traj_droplast), gr.update(visible=traj_reset), \ | |
| gr.update(visible=traj_vis), \ | |
| gr.update(visible=traj_input), gr.update(visible=vis_traj, value=None), \ | |
| gr.update(visible=vis_step3_prompt_generate), \ | |
| gr.update(visible=vis_prompt), \ | |
| gr.update(visible=vis_num_samples), \ | |
| gr.update(visible=vis_seed), \ | |
| gr.update(visible=vis_start), \ | |
| gr.update(visible=vis_gen_video) | |
| def main(args): | |
| demo = gr.Blocks() | |
| with demo: | |
| gr.Markdown(title) | |
| gr.Markdown(description) | |
| # state = gr.State({ | |
| # "mode": "camera_only", | |
| # "camera_input": [], | |
| # "traj_input": [], | |
| # }) | |
| with gr.Column(): | |
| ''' | |
| # step 0: select based model. | |
| gr.Markdown("## Step0: Selecting the model", show_label=False) | |
| gr.Markdown( f'- {BASE_MODEL[0]}: **MotionCtrl** deployed on {BASE_MODEL[0]}', show_label=False) | |
| gr.Markdown( f'- {BASE_MODEL[1]}: **MotionCtrl** deployed on {BASE_MODEL[1]}', show_label=False) | |
| gr.Markdown( f'- {BASE_MODEL[2]}: **MotionCtrl** deployed on {BASE_MODEL[2]}', show_label=False) | |
| gr.Markdown( f'- **Only the model that deployed on {BASE_MODEL[0]} is avalible now. MotionCtrl models deployed on {BASE_MODEL[1]} and {BASE_MODEL[2]} are coming soon.**', show_label=False) | |
| gr.Radio(choices=BASE_MODEL, value=BASE_MODEL[0], label="Based Model", interactive=False) | |
| ''' | |
| # step 1: select motion control mode | |
| gr.Markdown("## Step 1/3: Selecting the motion control mode", show_label=False) | |
| gr.Markdown( f'- {MODE[0]}: Control the camera motion only', show_label=False) | |
| gr.Markdown( f'- {MODE[1]}: Control the object motion only', show_label=False) | |
| gr.Markdown( f'- {MODE[2]}: Control both the camera and object motion', show_label=False) | |
| gr.Markdown( f'- Click `Proceed` to go into next step', show_label=False) | |
| infer_mode = gr.Radio(choices=MODE, value=MODE[0], label="Motion Control Mode", interactive=True) | |
| mode_info = gr.Button(value="Proceed") | |
| # step2 - camera + object motion control | |
| step2_camera_object_motion = gr.Markdown("---\n## Step 2/3: Select the camera poses and trajectory", show_label=False, visible=False) | |
| step2_camera_object_motion_des = gr.Markdown(f"\n 1. Select a basic camera pose. \ | |
| \n 2. Select a provided trajectory or draw the trajectory yourself.", | |
| show_label=False, visible=False) | |
| # step2 - camera motion control | |
| step2_camera_motion = gr.Markdown("---\n## Step 2/3: Select the camera poses", show_label=False, visible=False) | |
| step2_camera_motion_des = gr.Markdown(f"\n - {CAMERA_MOTION_MODE[0]}: Including 8 basic camera poses, such as pan up, pan down, zoom in, and zoom out. \ | |
| \n - {CAMERA_MOTION_MODE[1]}: Complex camera poses extracted from the real videos. \ | |
| \n - {CAMERA_MOTION_MODE[2]}: You can customize complex camera poses yourself by combining or fusing two of the eight basic camera poses. \ | |
| \n - Click `Proceed` to go into next step", | |
| show_label=False, visible=False) | |
| camera_mode = gr.Radio(choices=CAMERA_MOTION_MODE, value=CAMERA_MOTION_MODE[0], label="Camera Motion Control Mode", interactive=True, visible=False) | |
| camera_info = gr.Button(value="Proceed", visible=False) | |
| with gr.Row(): | |
| with gr.Column(): | |
| # step2.1 - camera motion control - basic | |
| basic_camera_motion = gr.Markdown("---\n### Basic Camera Poses", show_label=False, visible=False) | |
| basic_camera_motion_des = gr.Markdown(f"\n 1. Click one of the basic camera poses, such as `Pan Up`; \ | |
| \n 2. Slide the `Motion speed` to get a speed value. The large the value, the fast the camera motion; \ | |
| \n 3. Click `Visualize Camera and Proceed` to visualize the camera poses and go proceed; \ | |
| \n 4. Click `Reset Camera` to reset the camera poses (If needed). ", | |
| show_label=False, visible=False) | |
| # step2.2 - camera motion control - provided complex | |
| complex_camera_motion = gr.Markdown("---\n### Provided Complex Camera Poses", show_label=False, visible=False) | |
| complex_camera_motion_des = gr.Markdown(f"\n 1. Click one of the complex camera poses, such as `Pose_1`; \ | |
| \n 2. Click `Visualize Camera and Proceed` to visualize the camera poses and go proceed; \ | |
| \n 3. Click `Reset Camera` to reset the camera poses (If needed). ", | |
| show_label=False, visible=False) | |
| # step2.3 - camera motion control - custom | |
| custom_camera_motion = gr.Markdown("---\n### Custom Camera Poses", show_label=False, visible=False) | |
| custom_run_status = gr.Markdown(f"\n 1. Click two of the basic camera poses, such as `Pan Up` and `Pan Left`; \ | |
| \n 2. Click `Customized Mode 1: First A then B` or `Customized Mode 1: First A then B` \ | |
| \n - `Customized Mode 1: First A then B`: The camera first `Pan Up` and then `Pan Left`; \ | |
| \n - `Customized Mode 2: Both A and B`: The camera move towards the upper left corner; \ | |
| \n 3. Slide the `Motion speed` to get a speed value. The large the value, the fast the camera motion; \ | |
| \n 4. Click `Visualize Camera and Proceed` to visualize the camera poses and go proceed; \ | |
| \n 5. Click `Reset Camera` to reset the camera poses (If needed). ", | |
| show_label=False, visible=False) | |
| gr.HighlightedText(value=[("",""), ("1. Select two of the basic camera poses; 2. Select Customized Mode 1 OR Customized Mode 2. 3. Visualized Camera to show the customized camera poses", "Normal")], | |
| color_map={"Normal": "green", "Error": "red", "Clear clicks": "gray", "Add mask": "green", "Remove mask": "red"}, visible=False) | |
| with gr.Row(): | |
| U = gr.Button(value="Pan Up", visible=False) | |
| D = gr.Button(value="Pan Down", visible=False) | |
| L = gr.Button(value="Pan Left", visible=False) | |
| R = gr.Button(value="Pan Right", visible=False) | |
| with gr.Row(): | |
| I = gr.Button(value="Zoom In", visible=False) | |
| O = gr.Button(value="Zoom Out", visible=False) | |
| ACW = gr.Button(value="ACW", visible=False) | |
| CW = gr.Button(value="CW", visible=False) | |
| with gr.Row(): | |
| combine1 = gr.Button(value="Customized Mode 1: First A then B", visible=False) | |
| combine2 = gr.Button(value="Customized Mode 2: Both A and B", visible=False) | |
| with gr.Row(): | |
| speed = gr.Slider(minimum=0, maximum=2, step=0.2, label="Motion Speed", value=1.0, visible=False) | |
| with gr.Row(): | |
| Pose_1 = gr.Button(value="Pose_1", visible=False) | |
| Pose_2 = gr.Button(value="Pose_2", visible=False) | |
| Pose_3 = gr.Button(value="Pose_3", visible=False) | |
| Pose_4 = gr.Button(value="Pose_4", visible=False) | |
| with gr.Row(): | |
| Pose_5 = gr.Button(value="Pose_5", visible=False) | |
| Pose_6 = gr.Button(value="Pose_6", visible=False) | |
| Pose_7 = gr.Button(value="Pose_7", visible=False) | |
| Pose_8 = gr.Button(value="Pose_8", visible=False) | |
| with gr.Row(): | |
| camera_args = gr.Textbox(value="Camera Type", label="Camera Type", visible=False) | |
| with gr.Row(): | |
| camera_vis= gr.Button(value="Visualize Camera and Proceed", visible=False) | |
| camera_reset = gr.Button(value="Reset Camera", visible=False) | |
| with gr.Column(): | |
| vis_camera = gr.Plot(fig, label='Camera Poses', visible=False) | |
| # step2 - object motion control | |
| step2_object_motion = gr.Markdown("---\n## Step 2/3: Select a Provided Trajectory of Draw Yourself", show_label=False, visible=False) | |
| step2_object_motion_des = gr.Markdown(f"\n - {OBJECT_MOTION_MODE[0]}: We provide some example trajectories. You can select one of them directly. \ | |
| \n - {OBJECT_MOTION_MODE[1]}: Draw the trajectory yourself. \ | |
| \n - Click `Proceed` to go into next step", | |
| show_label=False, visible=False) | |
| object_mode = gr.Radio(choices=OBJECT_MOTION_MODE, value=OBJECT_MOTION_MODE[0], label="Motion Control Mode", interactive=True, visible=False) | |
| object_info = gr.Button(value="Proceed", visible=False) | |
| with gr.Row(): | |
| with gr.Column(): | |
| # step2.1 - object motion control - provided | |
| provided_traj = gr.Markdown("---\n### Provided Trajectory", show_label=False, visible=False) | |
| provided_traj_des = gr.Markdown(f"\n 1. Click one of the provided trajectories, such as `horizon_1`; \ | |
| \n 2. Click `Visualize Trajectory and Proceed` to visualize the trajectory and go proceed; \ | |
| \n 3. Click `Reset Trajectory` to reset the trajectory (If needed). ", | |
| show_label=False, visible=False) | |
| # step2.2 - object motion control - draw yourself | |
| draw_traj = gr.Markdown("---\n### Draw Yourself", show_label=False, visible=False) | |
| draw_run_status = gr.Markdown(f"\n 1. Click the `Canvas` in the right to draw the trajectory. **Note that You have to click the canva many times. For time saving, \ | |
| the click point will not appear in the canvas but its coordinates will be written in `Points of Trajectory`**; \ | |
| \n 2. Click `Visualize Trajectory and Proceed` to visualize the trajectory and go proceed; \ | |
| \n 3. Click `Reset Trajectory` to reset the trajectory (If needed). ", | |
| show_label=False, visible=False) | |
| with gr.Row(): | |
| traj_1 = gr.Button(value="horizon_1", visible=False) | |
| traj_2 = gr.Button(value="swaying_1", visible=False) | |
| traj_3 = gr.Button(value="swaying_2", visible=False) | |
| traj_4 = gr.Button(value="swaying_3", visible=False) | |
| with gr.Row(): | |
| traj_5 = gr.Button(value="curve_1", visible=False) | |
| traj_6 = gr.Button(value="curve_2", visible=False) | |
| traj_7 = gr.Button(value="curve_3", visible=False) | |
| traj_8 = gr.Button(value="curve_4", visible=False) | |
| traj_args = gr.Textbox(value="", label="Points of Trajectory", visible=False) | |
| with gr.Row(): | |
| traj_vis = gr.Button(value="Visualize Trajectory and Proceed", visible=False) | |
| traj_reset = gr.Button(value="Reset Trajectory", visible=False) | |
| traj_droplast = gr.Button(value="Drop Last Point", visible=False) | |
| with gr.Column(): | |
| # traj_input = gr.Image("assets/traj_layout.png", tool='sketch', source="canvas", | |
| # width=256, height=256, | |
| # label="Canvas for Drawing", visible=False) | |
| traj_input = gr.Image("assets/traj_layout.png", source="canvas", | |
| width=256, height=256, | |
| label="Canvas for Drawing", visible=False) | |
| vis_traj = gr.Video(value=None, label="Trajectory", visible=False, width=256, height=256) | |
| # step3 - Add prompt and Generate videos | |
| with gr.Row(): | |
| with gr.Column(): | |
| step3_prompt_generate = gr.Markdown("---\n## Step 3/3: Add prompt and Generate videos", show_label=False, visible=False) | |
| prompt = gr.Textbox(value="a dog sitting on grass", label="Prompt", interactive=True, visible=False) | |
| n_samples = gr.Number(value=3, precision=0, interactive=True, label="n_samples", visible=False) | |
| seed = gr.Number(value=1234, precision=0, interactive=True, label="Seed", visible=False) | |
| start = gr.Button(value="Start generation !", visible=False) | |
| with gr.Column(): | |
| gen_video = gr.Video(value=None, label="Generate Video", visible=False) | |
| mode_info.click( | |
| fn=visualized_step2, | |
| inputs=[infer_mode], | |
| outputs=[step2_camera_motion, | |
| step2_camera_motion_des, | |
| camera_mode, | |
| camera_info, | |
| basic_camera_motion, | |
| basic_camera_motion_des, | |
| custom_camera_motion, | |
| custom_run_status, | |
| complex_camera_motion, | |
| complex_camera_motion_des, | |
| U, D, L, R, | |
| I, O, ACW, CW, | |
| combine1, combine2, | |
| speed, | |
| Pose_1, Pose_2, Pose_3, Pose_4, | |
| Pose_5, Pose_6, Pose_7, Pose_8, | |
| camera_args, | |
| camera_reset, camera_vis, | |
| vis_camera, | |
| step2_object_motion, | |
| step2_object_motion_des, | |
| object_mode, | |
| object_info, | |
| provided_traj, | |
| provided_traj_des, | |
| draw_traj, | |
| draw_run_status, | |
| traj_1, traj_2, traj_3, traj_4, | |
| traj_5, traj_6, traj_7, traj_8, | |
| traj_args, | |
| traj_droplast, traj_reset, | |
| traj_vis, | |
| traj_input, vis_traj, | |
| step2_camera_object_motion, | |
| step2_camera_object_motion_des, | |
| step3_prompt_generate, prompt, n_samples, seed, start, gen_video, | |
| ], | |
| ) | |
| camera_info.click( | |
| fn=visualized_camera_poses, | |
| inputs=[camera_mode], | |
| outputs=[basic_camera_motion, | |
| basic_camera_motion_des, | |
| custom_camera_motion, | |
| custom_run_status, | |
| complex_camera_motion, | |
| complex_camera_motion_des, | |
| U, D, L, R, | |
| I, O, ACW, CW, | |
| combine1, combine2, | |
| speed, | |
| Pose_1, Pose_2, Pose_3, Pose_4, | |
| Pose_5, Pose_6, Pose_7, Pose_8, | |
| camera_args, | |
| camera_reset, camera_vis, | |
| vis_camera, | |
| step3_prompt_generate, prompt, n_samples, seed, start, gen_video], | |
| ) | |
| object_info.click( | |
| fn=visualized_traj_poses, | |
| inputs=[object_mode], | |
| outputs=[provided_traj, | |
| provided_traj_des, | |
| draw_traj, | |
| draw_run_status, | |
| traj_1, traj_2, traj_3, traj_4, | |
| traj_5, traj_6, traj_7, traj_8, | |
| traj_args, | |
| traj_droplast, traj_reset, | |
| traj_vis, | |
| traj_input, vis_traj, | |
| step3_prompt_generate, prompt, n_samples, seed, start, gen_video,], | |
| ) | |
| U.click(fn=add_camera_motion, inputs=[U, camera_mode], outputs=camera_args) | |
| D.click(fn=add_camera_motion, inputs=[D, camera_mode], outputs=camera_args) | |
| L.click(fn=add_camera_motion, inputs=[L, camera_mode], outputs=camera_args) | |
| R.click(fn=add_camera_motion, inputs=[R, camera_mode], outputs=camera_args) | |
| I.click(fn=add_camera_motion, inputs=[I, camera_mode], outputs=camera_args) | |
| O.click(fn=add_camera_motion, inputs=[O, camera_mode], outputs=camera_args) | |
| ACW.click(fn=add_camera_motion, inputs=[ACW, camera_mode], outputs=camera_args) | |
| CW.click(fn=add_camera_motion, inputs=[CW, camera_mode], outputs=camera_args) | |
| speed.change(fn=change_camera_speed, inputs=speed, outputs=camera_args) | |
| camera_reset.click(fn=reset_camera, inputs=None, outputs=[camera_args]) | |
| combine1.click(fn=change_camera_mode, inputs=[combine1, camera_mode], outputs=camera_args) | |
| combine2.click(fn=change_camera_mode, inputs=[combine2, camera_mode], outputs=camera_args) | |
| camera_vis.click(fn=fn_vis_camera, inputs=[infer_mode], outputs=[vis_camera, object_mode, object_info, step3_prompt_generate, prompt, n_samples, seed, start, gen_video]) | |
| Pose_1.click(fn=add_complex_camera_motion, inputs=Pose_1, outputs=camera_args) | |
| Pose_2.click(fn=add_complex_camera_motion, inputs=Pose_2, outputs=camera_args) | |
| Pose_3.click(fn=add_complex_camera_motion, inputs=Pose_3, outputs=camera_args) | |
| Pose_4.click(fn=add_complex_camera_motion, inputs=Pose_4, outputs=camera_args) | |
| Pose_5.click(fn=add_complex_camera_motion, inputs=Pose_5, outputs=camera_args) | |
| Pose_6.click(fn=add_complex_camera_motion, inputs=Pose_6, outputs=camera_args) | |
| Pose_7.click(fn=add_complex_camera_motion, inputs=Pose_7, outputs=camera_args) | |
| Pose_8.click(fn=add_complex_camera_motion, inputs=Pose_8, outputs=camera_args) | |
| traj_1.click(fn=add_provided_traj, inputs=traj_1, outputs=traj_args) | |
| traj_2.click(fn=add_provided_traj, inputs=traj_2, outputs=traj_args) | |
| traj_3.click(fn=add_provided_traj, inputs=traj_3, outputs=traj_args) | |
| traj_4.click(fn=add_provided_traj, inputs=traj_4, outputs=traj_args) | |
| traj_5.click(fn=add_provided_traj, inputs=traj_5, outputs=traj_args) | |
| traj_6.click(fn=add_provided_traj, inputs=traj_6, outputs=traj_args) | |
| traj_7.click(fn=add_provided_traj, inputs=traj_7, outputs=traj_args) | |
| traj_8.click(fn=add_provided_traj, inputs=traj_8, outputs=traj_args) | |
| traj_vis.click(fn=fn_vis_traj, inputs=None, outputs=[vis_traj, step3_prompt_generate, prompt, n_samples, seed, start, gen_video]) | |
| traj_input.select(fn=add_traj_point, inputs=None, outputs=traj_args) | |
| traj_droplast.click(fn=fn_traj_droplast, inputs=None, outputs=traj_args) | |
| traj_reset.click(fn=fn_traj_reset, inputs=None, outputs=traj_args) | |
| start.click(fn=model_run, inputs=[prompt, infer_mode, seed, n_samples], outputs=gen_video) | |
| gr.Markdown(article) | |
| # demo.launch(server_name='0.0.0.0', share=False, server_port=args.port) | |
| demo.queue(concurrency_count=1, max_size=10) | |
| demo.launch() | |
| if __name__=="__main__": | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--port", type=int, default=12345) | |
| args = parser.parse_args() | |
| main(args) | |