Spaces:
Runtime error
Runtime error
| # | |
| # Copyright (C) 2023, Inria | |
| # GRAPHDECO research group, https://team.inria.fr/graphdeco | |
| # All rights reserved. | |
| # | |
| # This software is free for non-commercial, research and evaluation use | |
| # under the terms of the LICENSE.md file. | |
| # | |
| # For inquiries contact george.drettakis@inria.fr | |
| # | |
| import torch | |
| import traceback | |
| import socket | |
| import json | |
| from scene.cameras import MiniCam | |
| host = "127.0.0.1" | |
| port = 6009 | |
| conn = None | |
| addr = None | |
| listener = socket.socket(socket.AF_INET, socket.SOCK_STREAM) | |
| def init(wish_host, wish_port): | |
| global host, port, listener | |
| host = wish_host | |
| port = wish_port | |
| listener.bind((host, port)) | |
| listener.listen() | |
| listener.settimeout(0) | |
| def try_connect(): | |
| global conn, addr, listener | |
| try: | |
| conn, addr = listener.accept() | |
| print(f"\nConnected by {addr}") | |
| conn.settimeout(None) | |
| except Exception as inst: | |
| pass | |
| def read(): | |
| global conn | |
| messageLength = conn.recv(4) | |
| messageLength = int.from_bytes(messageLength, 'little') | |
| message = conn.recv(messageLength) | |
| return json.loads(message.decode("utf-8")) | |
| def send(message_bytes, verify): | |
| global conn | |
| if message_bytes != None: | |
| conn.sendall(message_bytes) | |
| conn.sendall(len(verify).to_bytes(4, 'little')) | |
| conn.sendall(bytes(verify, 'ascii')) | |
| def receive(): | |
| message = read() | |
| width = message["resolution_x"] | |
| height = message["resolution_y"] | |
| if width != 0 and height != 0: | |
| try: | |
| do_training = bool(message["train"]) | |
| fovy = message["fov_y"] | |
| fovx = message["fov_x"] | |
| znear = message["z_near"] | |
| zfar = message["z_far"] | |
| do_shs_python = bool(message["shs_python"]) | |
| do_rot_scale_python = bool(message["rot_scale_python"]) | |
| keep_alive = bool(message["keep_alive"]) | |
| scaling_modifier = message["scaling_modifier"] | |
| world_view_transform = torch.reshape(torch.tensor(message["view_matrix"]), (4, 4)).cuda() | |
| world_view_transform[:,1] = -world_view_transform[:,1] | |
| world_view_transform[:,2] = -world_view_transform[:,2] | |
| full_proj_transform = torch.reshape(torch.tensor(message["view_projection_matrix"]), (4, 4)).cuda() | |
| full_proj_transform[:,1] = -full_proj_transform[:,1] | |
| custom_cam = MiniCam(width, height, fovy, fovx, znear, zfar, world_view_transform, full_proj_transform) | |
| except Exception as e: | |
| print("") | |
| traceback.print_exc() | |
| raise e | |
| return custom_cam, do_training, do_shs_python, do_rot_scale_python, keep_alive, scaling_modifier | |
| else: | |
| return None, None, None, None, None, None |