mirror of
https://github.com/nerfstudio-project/nerfstudio.git
synced 2026-11-13 19:33:46 +08:00
evonneng
86b1011ae1
* added skeleton for terminal logger * done skeleton terminal writer logic... todo: actual calls to the write classes * moved lambda to top function * added logic to support timing * prettier printing * prettier printing * lint * separated out timing and other stats variables. printing in dict format * keeping logging history and wiping rest * updated logic to calculate total times instead of average times * made stats tracker configurable * moved stats tracker and profiler to own class file; implemented basic functionality for profiler * lint removing duplicate function * update readme; moved around config variables * profiler prints on sig kill
77 lines
2.2 KiB
Markdown
77 lines
2.2 KiB
Markdown
# MattPort
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# Quickstart
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## Installation: Setup the environment
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```
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# Clone the repo
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git clone --recurse-submodules git@github.com:ethanweber/mattport.git
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# Create the python environment
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conda create --name mattport python=3.8.13
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conda activate mattport
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pip install -r environment/requirements.txt
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# Install mattport as a library
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python setup.py develop
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# Running the test cases
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pytest tests
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```
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## Getting the data
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Download the original NeRF dataset and put it in the following format.
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```
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- data/
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- blender/
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- fern/
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- lego/
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```
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## Training a model
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```
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# Run with the default config
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python scripts/run_train.py
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# Run with config changes
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python scripts/run_train.py machine_config.num_gpus=1
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```
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# Logging and profiling features
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We provide many logging functionalities for timing and/or tracking losses during training. All of these loggers are configurable via `configs/logging_configs.yml`
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1. **Writer**: Logs losses and generated images during training to a specified output stream. Specify the type of writer (Tensorboard, local directory, Weights and Biases), and how often to log in the config.
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2. **StatsTracker**: Computes select statistics and prints to the terminal for local debugging. Specify the kinds of statistics to be logged, how often to log, and the maximum history buffer size in the config.
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3. **Profiler**: Computes the average total time of execution for any function with the `@profiler.time_function` decorator. Prints out the full profile at the termination of training or the program.
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# Setting up Jupyter
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```
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python -m jupyter lab build
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bash environments/run_jupyter.sh
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```
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# Tooling
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We use [autoenv](https://github.com/hyperupcall/autoenv) to make setting up the environment and environment variables easier. This will run the `.envrc` file upon entering the `/path/to/mattport` folder. It will also remove the set environment parameters upon leaving.
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```
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# Install direnv.
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sudo apt install direnv
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# Add the following line to the bottom of your ~/.bashrc file.
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eval "$(direnv hook bash)"
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# Populate your .envrc with commands you want to run. Then, run the following to allow updates.
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cd /path/to/mattport
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direnv allow .
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```
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<!-- Our PyTorch version uses cuda-11.3. -->
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<!-- export PATH=/usr/local/cuda-11.3/bin:$PATH --> |