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Nerfstudio Colab
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| { | |
| "nbformat": 4, | |
| "nbformat_minor": 0, | |
| "metadata": { | |
| "colab": { | |
| "provenance": [], | |
| "include_colab_link": true | |
| }, | |
| "kernelspec": { | |
| "name": "python3", | |
| "display_name": "Python 3" | |
| }, | |
| "language_info": { | |
| "name": "python" | |
| }, | |
| "accelerator": "GPU", | |
| "gpuClass": "standard" | |
| }, | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "view-in-github", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "<a href=\"https://colab.research.google.com/gist/l0g1c-80m8/9186a549f24083fdea0b92d9bff49376/nerfstudio-colab.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "<p align=\"center\">\n", | |
| " <picture>\n", | |
| " <source media=\"(prefers-color-scheme: dark)\" srcset=\"https://docs.nerf.studio/en/latest/_images/logo-dark.png\">\n", | |
| " <source media=\"(prefers-color-scheme: light)\" srcset=\"https://docs.nerf.studio/en/latest/_images/logo.png\">\n", | |
| " <img alt=\"nerfstudio\" src=\"https://docs.nerf.studio/en/latest/_images/logo.png\" width=\"400\">\n", | |
| " </picture>\n", | |
| "</p>\n", | |
| "\n", | |
| "\n", | |
| "# Nerfstudio: A collaboration friendly studio for NeRFs\n", | |
| "\n", | |
| "\n", | |
| "\n", | |
| "\n", | |
| "This colab shows how to train and view NeRFs from Nerfstudio both on pre-made datasets or from your own videos/images.\n", | |
| "\n", | |
| "\\\\\n", | |
| "\n", | |
| "Credit to [NeX](https://nex-mpi.github.io/) for Google Colab format." | |
| ], | |
| "metadata": { | |
| "id": "SiiXJ7K_fePG" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "## Frequently Asked Questions\n", | |
| "\n", | |
| "* **Downloading custom data is stalling (no output):**\n", | |
| " * This is a bug in Colab. The data is processing, but may take a while to complete. You will know processing completed if `data/nerfstudio/custom_data/transforms.json` exists.\n", | |
| "* **Training is not showing progress**:\n", | |
| " * The lack of output is a bug in Colab. You can see the training progress from the viewer.\n", | |
| "\n", | |
| "* **Viewer Quality is bad / Low resolution**:\n", | |
| " * This may be because more GPU is being used on training that rendering the viewer. Try pausing training or decreasing training utilization.\n", | |
| "\n", | |
| "* **Other problems?**\n", | |
| " * Feel free to create an issue on our [GitHub repo](https://github.com/nerfstudio-project/nerfstudio).\n" | |
| ], | |
| "metadata": { | |
| "id": "Yyx5h6kz5ga7" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "#@title # Install Conda (requires runtime restart) { vertical-output: true, display-mode: \"form\" }\n", | |
| "\n", | |
| "!pip install -q condacolab\n", | |
| "import condacolab\n", | |
| "condacolab.install()" | |
| ], | |
| "metadata": { | |
| "id": "RGr33zHaHak0" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "#@title # Install Nerfstudio and Dependencies (~10 min) { vertical-output: true, display-mode: \"form\" }\n", | |
| "\n", | |
| "%cd /content/\n", | |
| "!pip install --upgrade pip\n", | |
| "!pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 -f https://download.pytorch.org/whl/torch_stable.html\n", | |
| "\n", | |
| "# Installing TinyCuda\n", | |
| "%cd /content/\n", | |
| "!gdown \"https://drive.google.com/u/1/uc?id=1q8fuc-Mqiev5GTBTRA5UPgCaQDzuqKqj\"\n", | |
| "!pip install tinycudann-1.6-cp37-cp37m-linux_x86_64.whl\n", | |
| "\n", | |
| "# Installing COLMAP\n", | |
| "%cd /content/\n", | |
| "!conda install -c conda-forge colmap\n", | |
| "\n", | |
| "# Install nerfstudio\n", | |
| "%cd /content/\n", | |
| "!pip install nerfstudio" | |
| ], | |
| "metadata": { | |
| "id": "9oyLHl8QfYwP" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "#@markdown <h1> Downloading Data</h1>\n", | |
| "#@markdown <h3>Pick the preset scene or upload your own images/video</h3>\n", | |
| "import os\n", | |
| "from google.colab import files\n", | |
| "from IPython.core.display import display, HTML\n", | |
| "\n", | |
| "scene = '\\uD83D\\uDDBC poster' #@param ['🖼 poster', '🚜 dozer', '🌄 desolation', '📤 upload your images' , '🎥 upload your own video']\n", | |
| "scene = ' '.join(scene.split(' ')[1:])\n", | |
| "\n", | |
| "if scene not in ['upload your images', 'upload your own video']:\n", | |
| " %cd /content/\n", | |
| " !ns-download-data --dataset=nerfstudio --capture=$scene\n", | |
| "else:\n", | |
| " display(HTML('<h3>Select your custom data</h3>'))\n", | |
| " display(HTML('<p/>You can select multiple images by pressing ctrl, cmd or shift and click.<p>'))\n", | |
| " display(HTML('<p/>Note: This may take time, especially on hires inputs, so we recommend to download dataset after creation.<p>'))\n", | |
| " !mkdir -p /content/data/nerfstudio/custom_data\n", | |
| " if scene == 'upload your images':\n", | |
| " !mkdir -p /content/data/nerfstudio/custom_data/raw_images\n", | |
| " %cd /content/data/nerfstudio/custom_data/raw_images\n", | |
| " uploaded = files.upload()\n", | |
| " dir = os.getcwd()\n", | |
| " else:\n", | |
| " %cd /content/data/nerfstudio/custom_data/\n", | |
| " uploaded = files.upload()\n", | |
| " dir = os.getcwd()\n", | |
| " preupload_datasets = [os.path.join(dir, f) for f in uploaded.keys()]\n", | |
| " del uploaded\n", | |
| " %cd /content/\n", | |
| "\n", | |
| " if scene == 'upload your images':\n", | |
| " !ns-process-data images --data /content/data/nerfstudio/custom_data/raw_images --output-dir /content/data/nerfstudio/custom_data/\n", | |
| " else:\n", | |
| " video_path = preupload_datasets[0]\n", | |
| " !ns-process-data video --data $video_path --output-dir /content/data/nerfstudio/custom_data/\n", | |
| "\n", | |
| " scene = \"custom_data\"" | |
| ], | |
| "metadata": { | |
| "id": "msVLprI4gRA4", | |
| "cellView": "form" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "#@title # Set Up Viewer\n", | |
| "\n", | |
| "%cd /content\n", | |
| "\n", | |
| "# Install localtunnel\n", | |
| "# We are using localtunnel https://github.com/localtunnel/localtunnel but ngrok could also be used\n", | |
| "!npm install -g localtunnel\n", | |
| "\n", | |
| "# Tunnel port 7007, the default for\n", | |
| "!rm url.txt 2> /dev/null\n", | |
| "get_ipython().system_raw('lt --port 7007 >> url.txt 2>&1 &')" | |
| ], | |
| "metadata": { | |
| "id": "Eju-3p2hjcB2", | |
| "cellView": "form" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "#@title # Start Viewer\n", | |
| "\n", | |
| "with open('url.txt') as f:\n", | |
| " lines = f.readlines()\n", | |
| "websocket_url = lines[0].split(\": \")[1].strip().replace(\"https\", \"wss\")\n", | |
| "# from nerfstudio.utils.io import load_from_json\n", | |
| "# from pathlib import Path\n", | |
| "# json_filename = \"nerfstudio/nerfstudio/viewer/app/package.json\"\n", | |
| "# version = load_from_json(Path(json_filename))[\"version\"]\n", | |
| "url = f\"https://viewer.nerf.studio/?websocket_url={websocket_url}\"\n", | |
| "print(url)\n", | |
| "print(\"You may need to click Refresh Page after you start training!\")\n", | |
| "from IPython import display\n", | |
| "display.IFrame(src=url, height=800, width=\"100%\")" | |
| ], | |
| "metadata": { | |
| "id": "VoKDxqEcjmfC", | |
| "cellView": "form" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "#@title # Start Training { vertical-output: true }\n", | |
| "\n", | |
| "%cd /content\n", | |
| "!ns-train nerfacto --viewer.websocket-port 7007 nerfstudio-data --data data/nerfstudio/$scene --downscale-factor 4" | |
| ], | |
| "metadata": { | |
| "id": "m_N8_cLfjoXD", | |
| "cellView": "form" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "#@title # Render Video { vertical-output: true }\n", | |
| "#@markdown <h3>Export the camera path from within the viewer, then run this cell.</h3>\n", | |
| "#@markdown <h5>The rendered video should be at renders/output.mp4!</h5>\n", | |
| "\n", | |
| "\n", | |
| "base_dir = \"/content/outputs/data-nerfstudio-\" + scene + \"/nerfacto/\"\n", | |
| "training_run_dir = base_dir + os.listdir(base_dir)[0]\n", | |
| "\n", | |
| "from IPython.core.display import display, HTML\n", | |
| "display(HTML('<h3>Upload the camera path JSON.</h3>'))\n", | |
| "%cd $training_run_dir\n", | |
| "uploaded = files.upload()\n", | |
| "uploaded_camera_path_filename = list(uploaded.keys())[0]\n", | |
| "\n", | |
| "config_filename = training_run_dir + \"/config.yml\"\n", | |
| "camera_path_filename = training_run_dir + \"/\" + uploaded_camera_path_filename\n", | |
| "camera_path_filename = camera_path_filename.replace(\" \", \"\\\\ \").replace(\"(\", \"\\\\(\").replace(\")\", \"\\\\)\")\n", | |
| "\n", | |
| "%cd /content/\n", | |
| "!ns-render --load-config $config_filename --traj filename --camera-path-filename $camera_path_filename --output-path renders/output.mp4" | |
| ], | |
| "metadata": { | |
| "id": "WGt8ukG6Htg3", | |
| "cellView": "form" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| } | |
| ] | |
| } |
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