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import { exec } from "child_process"
/**
* Interface for the options for the `runGaussianSplattingCUDA` function.
*/
export interface Options {
/**
* Data path for the training data.
*/
dataPath?: string;
/**
* If set, forces the overwriting of the output folder. If not set,
* the program exits if the output folder already exists.
*/
force?: boolean;
/**
* Path where the trained model will be saved. If this option isn't specified,
* the model will be saved to the "output" folder in the root directory of the project.
*/
outputPath?: string;
/**
* Specifies the number of iterations to train the model.
*/
iterations?: number;
/**
* If set, CUDA memory is emptied every 100 iterations.
*/
emptyGpuCache?: boolean;
/**
* If set, the program monitors the average convergence rate throughout training.
* When the average convergence rate drops below 0.008 after 15k iterations,
* optimization stops, which speeds up training when the gain starts to diminish.
*/
enableCRMonitoring?: boolean;
/**
* When the `enableCRMonitoring` flag is set, this sets a custom average convergence rate for training.
*/
convergenceRate?: number;
}
/**
* Run 3D Gaussian Splatting CUDA Implementation.
*
* @param {Options} options - A set of configurations to be passed to the application
*/
export const runGaussianSplattingCUDA = (options: Options): Promise<string> => {
return new Promise((resolve, reject) => {
let command = './build/gaussian_splatting_cuda';
if (options.dataPath) command += ` -d ${options.dataPath}`;
if (options.force) command += ' -f';
if (options.outputPath) command += ` -o ${options.outputPath}`;
if (options.iterations) command += ` -i ${options.iterations}`;
if (options.emptyGpuCache) command += ' --empty-gpu-cache';
if (options.enableCRMonitoring) command += ' --enable-cr-monitoring';
if (options.convergenceRate) command += ` -c ${options.convergenceRate}`;
exec(command, (error, stdout, stderr) => {
if (error) {
reject(stderr);
} else {
resolve(stdout);
}
});
});
}; |