{ "cells": [ { "cell_type": "markdown", "metadata": { "id": "CUOFrZPwTMrY" }, "source": [ "# [DreamGaussian](https://github.com/dreamgaussian/dreamgaussian) image-to-3D demo" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "PYWv9tzDF98_", "outputId": "89ed949c-2cb9-40e7-f7c5-c5234934ec8e" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Python 3.10.12\n" ] } ], "source": [ "!python --version" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "c:\\Users\\ASUS\\OneDrive\\桌面\\專題2\\dreamgaussian\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "c:\\Users\\ASUS\\anaconda2024.6\\envs\\test4\\lib\\site-packages\\IPython\\core\\magics\\osm.py:417: UserWarning: This is now an optional IPython functionality, setting dhist requires you to install the `pickleshare` library.\n", " self.shell.db['dhist'] = compress_dhist(dhist)[-100:]\n" ] } ], "source": [ "#@title install (only run once)\n", "#!git clone https://github.com/dreamgaussian/dreamgaussian\n", "%cd dreamgaussian\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "nvcc: NVIDIA (R) Cuda compiler driver\n", "Copyright (c) 2005-2022 NVIDIA Corporation\n", "Built on Wed_Sep_21_10:41:10_Pacific_Daylight_Time_2022\n", "Cuda compilation tools, release 11.8, V11.8.89\n", "Build cuda_11.8.r11.8/compiler.31833905_0\n" ] } ], "source": [ "!nvcc --version" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "import os\n", "os.environ['CUDA_HOME'] = r'C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v11.8'\n", "os.environ['PATH'] = os.environ['CUDA_HOME'] + r'\\bin;' + os.environ['PATH']\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Note: you may need to restart the kernel to use updated packages.\n", "Note: you may need to restart the kernel to use updated packages.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ " error: subprocess-exited-with-error\n", " \n", " × python setup.py egg_info did not run successfully.\n", " │ exit code: 1\n", " ╰─> [12 lines of output]\n", " Traceback (most recent call last):\n", " File \"\", line 2, in \n", " File \"\", line 34, in \n", " File \"C:\\Users\\ASUS\\OneDrive\\桌面\\專題2\\dreamgaussian\\diff-gaussian-rasterization\\setup.py\", line 21, in \n", " CUDAExtension(\n", " File \"c:\\Users\\ASUS\\anaconda2024.6\\envs\\test4\\lib\\site-packages\\torch\\utils\\cpp_extension.py\", line 1076, in CUDAExtension\n", " library_dirs += library_paths(cuda=True)\n", " File \"c:\\Users\\ASUS\\anaconda2024.6\\envs\\test4\\lib\\site-packages\\torch\\utils\\cpp_extension.py\", line 1214, in library_paths\n", " paths.append(_join_cuda_home(lib_dir))\n", " File \"c:\\Users\\ASUS\\anaconda2024.6\\envs\\test4\\lib\\site-packages\\torch\\utils\\cpp_extension.py\", line 2416, in _join_cuda_home\n", " raise OSError('CUDA_HOME environment variable is not set. '\n", " OSError: CUDA_HOME environment variable is not set. Please set it to your CUDA install root.\n", " [end of output]\n", " \n", " note: This error originates from a subprocess, and is likely not a problem with pip.\n", "error: metadata-generation-failed\n", "\n", "× Encountered error while generating package metadata.\n", "╰─> See above for output.\n", "\n", "note: This is an issue with the package mentioned above, not pip.\n", "hint: See above for details.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Note: you may need to restart the kernel to use updated packages.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ " error: subprocess-exited-with-error\n", " \n", " × python setup.py egg_info did not run successfully.\n", " │ exit code: 1\n", " ╰─> [12 lines of output]\n", " Traceback (most recent call last):\n", " File \"\", line 2, in \n", " File \"\", line 34, in \n", " File \"C:\\Users\\ASUS\\OneDrive\\桌面\\專題2\\dreamgaussian\\simple-knn\\setup.py\", line 24, in \n", " CUDAExtension(\n", " File \"c:\\Users\\ASUS\\anaconda2024.6\\envs\\test4\\lib\\site-packages\\torch\\utils\\cpp_extension.py\", line 1076, in CUDAExtension\n", " library_dirs += library_paths(cuda=True)\n", " File \"c:\\Users\\ASUS\\anaconda2024.6\\envs\\test4\\lib\\site-packages\\torch\\utils\\cpp_extension.py\", line 1214, in library_paths\n", " paths.append(_join_cuda_home(lib_dir))\n", " File \"c:\\Users\\ASUS\\anaconda2024.6\\envs\\test4\\lib\\site-packages\\torch\\utils\\cpp_extension.py\", line 2416, in _join_cuda_home\n", " raise OSError('CUDA_HOME environment variable is not set. '\n", " OSError: CUDA_HOME environment variable is not set. Please set it to your CUDA install root.\n", " [end of output]\n", " \n", " note: This error originates from a subprocess, and is likely not a problem with pip.\n", "error: metadata-generation-failed\n", "\n", "× Encountered error while generating package metadata.\n", "╰─> See above for output.\n", "\n", "note: This is an issue with the package mentioned above, not pip.\n", "hint: See above for details.\n" ] } ], "source": [ "# install dependencies\n", "%pip install -q einops plyfile dearpygui huggingface_hub diffusers accelerate transformers xatlas trimesh PyMCubes pymeshlab rembg[gpu,cli] omegaconf ninja\n", "\n", "#build extension from source (can be slow)\n", "#!git clone --recursive https://github.com/ashawkey/diff-gaussian-rasterization\n", "%pip install -q ./diff-gaussian-rasterization\n", "%pip install -q ./simple-knn\n", "\n", "# pre-built wheels (faster)\n", "#!pip install -q https://github.com/camenduru/diff-gaussian-rasterization/releases/download/v1.0/diff_gaussian_rasterization-0.0.0-cp310-cp310-linux_x86_64.1.whl\n", "#!pip install -q https://github.com/camenduru/diff-gaussian-rasterization/releases/download/v1.0/simple_knn-0.0.0-cp310-cp310-linux_x86_64.1.whl\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "1pBDI44pTJNg", "outputId": "8d35d061-5cc2-4148-af3d-6984c435b0f7" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "'rm' ���O�����Υ~���R�O�B�i���檺�{���Χ妸�ɡC\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "c:\\Users\\ASUS\\OneDrive\\桌面\\專題2\\dreamgaussian\\dreamgaussian\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Cloning into 'dreamgaussian'...\n", "c:\\Users\\ASUS\\anaconda2024.6\\envs\\test4\\lib\\site-packages\\IPython\\core\\magics\\osm.py:417: UserWarning: This is now an optional IPython functionality, setting dhist requires you to install the `pickleshare` library.\n", " self.shell.db['dhist'] = compress_dhist(dhist)[-100:]\n", "ERROR: diff_gaussian_rasterization-0.0.0-cp310-cp310-linux_x86_64.1.whl is not a supported wheel on this platform.\n", "ERROR: simple_knn-0.0.0-cp310-cp310-linux_x86_64.1.whl is not a supported wheel on this platform.\n", "�l�ؿ����ɮ� data �w�g�s�b�C\n", "�B�z�ɵo�Ϳ��~: data�C\n" ] } ], "source": [ "\n", "# nvdiffrast\n", "!pip install -q git+https://github.com/NVlabs/nvdiffrast\n", "\n", "# kiuikit\n", "!pip install -q git+https://github.com/ashawkey/kiuikit\n", "\n", "%mkdir -p data" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 365 }, "id": "5X5IhWpnTyzv", "outputId": "7afcb9af-7391-4e35-e409-157a51c388c7" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "/content/dreamgaussian/data\n" ] }, { "data": { "text/html": [ "\n", " \n", " \n", " Upload widget is only available when the cell has been executed in the\n", " current browser session. Please rerun this cell to enable.\n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Saving 6_0.jpg to 6_0.jpg\n", "/content/dreamgaussian\n" ] }, { "data": { "image/jpeg": 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", "text/plain": [ "" ] }, "metadata": { "image/jpeg": { "height": 256, "width": 256 } }, "output_type": "display_data" } ], "source": [ "#@title upload image\n", "\n", "import os\n", "\n", "%cd data/\n", "%rm * # remove all old files!\n", "from google.colab import files\n", "uploaded = files.upload()\n", "IMAGE = os.path.basename(next(iter(uploaded))) # filename\n", "%cd ..\n", "\n", "# display image\n", "from IPython.display import Image, display\n", "display(Image(f'data/{IMAGE}', width=256, height=256))" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "tdJYQF1RXRvf", "outputId": "4ca0b436-627e-497b-aabb-bb2176677ff2" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Downloading data from 'https://github.com/danielgatis/rembg/releases/download/v0.0.0/u2net.onnx' to file '/root/.u2net/u2net.onnx'.\n" ] }, { "ename": "ConnectTimeout", "evalue": "HTTPSConnectionPool(host='github.com', port=443): Max retries exceeded with url: /danielgatis/rembg/releases/download/v0.0.0/u2net.onnx (Caused by ConnectTimeoutError(, 'Connection to github.com timed out. (connect timeout=30)'))", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mTimeoutError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/urllib3/connection.py\u001b[0m in \u001b[0;36m_new_conn\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 202\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 203\u001b[0;31m sock = connection.create_connection(\n\u001b[0m\u001b[1;32m 204\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_dns_host\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mport\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/urllib3/util/connection.py\u001b[0m in \u001b[0;36mcreate_connection\u001b[0;34m(address, timeout, source_address, socket_options)\u001b[0m\n\u001b[1;32m 84\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 85\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 86\u001b[0m \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/urllib3/util/connection.py\u001b[0m in \u001b[0;36mcreate_connection\u001b[0;34m(address, timeout, source_address, socket_options)\u001b[0m\n\u001b[1;32m 72\u001b[0m \u001b[0msock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbind\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msource_address\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 73\u001b[0;31m \u001b[0msock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msa\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 74\u001b[0m \u001b[0;31m# Break explicitly a reference cycle\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mTimeoutError\u001b[0m: timed out", "\nThe above exception was the direct cause of the following exception:\n", "\u001b[0;31mConnectTimeoutError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/urllib3/connectionpool.py\u001b[0m in \u001b[0;36murlopen\u001b[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)\u001b[0m\n\u001b[1;32m 790\u001b[0m \u001b[0;31m# Make the request on the HTTPConnection object\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 791\u001b[0;31m response = self._make_request(\n\u001b[0m\u001b[1;32m 792\u001b[0m \u001b[0mconn\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/urllib3/connectionpool.py\u001b[0m in \u001b[0;36m_make_request\u001b[0;34m(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length)\u001b[0m\n\u001b[1;32m 491\u001b[0m \u001b[0mnew_e\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_wrap_proxy_error\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnew_e\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mproxy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscheme\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 492\u001b[0;31m \u001b[0;32mraise\u001b[0m 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(connect timeout=30)')", "\nThe above exception was the direct cause of the following exception:\n", "\u001b[0;31mMaxRetryError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/requests/adapters.py\u001b[0m in \u001b[0;36msend\u001b[0;34m(self, request, stream, timeout, verify, cert, proxies)\u001b[0m\n\u001b[1;32m 666\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 667\u001b[0;31m resp = conn.urlopen(\n\u001b[0m\u001b[1;32m 668\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/urllib3/connectionpool.py\u001b[0m in \u001b[0;36murlopen\u001b[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)\u001b[0m\n\u001b[1;32m 844\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 845\u001b[0;31m retries = retries.increment(\n\u001b[0m\u001b[1;32m 846\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merror\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnew_e\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_pool\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_stacktrace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexc_info\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/urllib3/util/retry.py\u001b[0m in \u001b[0;36mincrement\u001b[0;34m(self, method, url, response, error, _pool, _stacktrace)\u001b[0m\n\u001b[1;32m 514\u001b[0m \u001b[0mreason\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0merror\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mResponseError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcause\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 515\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mMaxRetryError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_pool\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreason\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mreason\u001b[0m \u001b[0;31m# type: ignore[arg-type]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 516\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mMaxRetryError\u001b[0m: HTTPSConnectionPool(host='github.com', port=443): Max retries exceeded with url: /danielgatis/rembg/releases/download/v0.0.0/u2net.onnx (Caused by ConnectTimeoutError(, 'Connection to github.com timed out. (connect timeout=30)'))", "\nDuring handling of the above exception, another exception occurred:\n", "\u001b[0;31mConnectTimeout\u001b[0m Traceback (most recent call last)", "\u001b[0;32m/content/dreamgaussian/process.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 42\u001b[0m \u001b[0mopt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mparser\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparse_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 43\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 44\u001b[0;31m \u001b[0msession\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrembg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnew_session\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel_name\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mopt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 45\u001b[0m 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(Caused by ConnectTimeoutError(, 'Connection to github.com timed out. (connect timeout=30)'))" ] }, { "ename": "FileNotFoundError", "evalue": "No such file or directory: 'data/6_0_rgba.png'", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/display.py\u001b[0m in \u001b[0;36m_data_and_metadata\u001b[0;34m(self, always_both)\u001b[0m\n\u001b[1;32m 1299\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1300\u001b[0;31m \u001b[0mb64_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mb2a_base64\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdecode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'ascii'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1301\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mTypeError\u001b[0m: a bytes-like object is required, not 'str'", "\nDuring handling of the above exception, another exception occurred:\n", "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/formatters.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, obj, include, exclude)\u001b[0m\n\u001b[1;32m 968\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 969\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mmethod\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 970\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minclude\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minclude\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexclude\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mexclude\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 971\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 972\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/display.py\u001b[0m in \u001b[0;36m_repr_mimebundle_\u001b[0;34m(self, include, exclude)\u001b[0m\n\u001b[1;32m 1288\u001b[0m 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\u001b[0;34m{\u001b[0m\u001b[0mmimetype\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mmetadata\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/display.py\u001b[0m in \u001b[0;36m_data_and_metadata\u001b[0;34m(self, always_both)\u001b[0m\n\u001b[1;32m 1300\u001b[0m \u001b[0mb64_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mb2a_base64\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdecode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'ascii'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1301\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1302\u001b[0;31m raise FileNotFoundError(\n\u001b[0m\u001b[1;32m 1303\u001b[0m \"No such file or directory: '%s'\" % (self.data))\n\u001b[1;32m 1304\u001b[0m \u001b[0mmd\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mFileNotFoundError\u001b[0m: No such file or directory: 'data/6_0_rgba.png'" ] }, { "ename": "FileNotFoundError", "evalue": "No such file or directory: 'data/6_0_rgba.png'", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/display.py\u001b[0m in \u001b[0;36m_data_and_metadata\u001b[0;34m(self, always_both)\u001b[0m\n\u001b[1;32m 1299\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1300\u001b[0;31m \u001b[0mb64_data\u001b[0m \u001b[0;34m=\u001b[0m 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\u001b[0mget_real_method\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprint_method\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 344\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mmethod\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 345\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 346\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 347\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/display.py\u001b[0m in \u001b[0;36m_repr_png_\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1318\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_repr_png_\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1319\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0membed\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_FMT_PNG\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1320\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data_and_metadata\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1321\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1322\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_repr_jpeg_\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/display.py\u001b[0m in \u001b[0;36m_data_and_metadata\u001b[0;34m(self, always_both)\u001b[0m\n\u001b[1;32m 1300\u001b[0m \u001b[0mb64_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mb2a_base64\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdecode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'ascii'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1301\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1302\u001b[0;31m raise FileNotFoundError(\n\u001b[0m\u001b[1;32m 1303\u001b[0m \"No such file or directory: '%s'\" % (self.data))\n\u001b[1;32m 1304\u001b[0m \u001b[0mmd\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mFileNotFoundError\u001b[0m: No such file or directory: 'data/6_0_rgba.png'" ] }, { "data": { "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#@title preprocess image\n", "\n", "# preprocess\n", "%run process.py data/{IMAGE}\n", "\n", "NAME = os.path.splitext(IMAGE)[0]\n", "IMAGE_PROCESSED = NAME + '_rgba.png'\n", "\n", "# display processed image\n", "from IPython.display import Image, display\n", "display(Image(f'data/{IMAGE_PROCESSED}', width=256, height=256))" ] }, { "cell_type": "markdown", "metadata": { "id": "DPRUSiFCW0DX" }, "source": [ "# Settings\n", "* Elevation: estimated elevation angle, default to 0 (horizontal), range from [-90, 90]. If you upload a look-down image, try a value like -30." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "0UG5zvnpWrlH" }, "outputs": [], "source": [ "#@markdown ####**Settings:**\n", "Elevation = 0 #@param {type: 'integer'}" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 933, "referenced_widgets": [ "f490c73e504647f4bccee6953fa9aeda", "ed862afe0eff4e01af7f86886173c405", "3d89678f50c94139800274cb37ab9df5", "8e5765be21e34aa98f33fc49fc1c78f2", "968a4b8ee71c481faff667426c7769b0", "447cb8a54f2e4d08a3c3b61a2d258d89", "4c7a437918bb49d9abb4315861f6ccea", "425c48d4cc1d48598bb1837b5ba6129d", "042fcc3f41c24f36a5379961f65bc34a", "b7cea0a29c6145f88ba8edd19961148e", "ebcaca47d3e445dabe21b4cdf2a1adb9", "5f89e6eeff1c48f4bdb830824249f671", "374fff14d0c94557a3339fedca238d84", "20ceeb52044545dea8dc22a83715a6e1", "76d1f9225dbb4b3faad99de943ec12a8", "5f78e64dcb5b47d9969168515c1720dc", "33690626d88c4e77af7f816702984792", "48da44ff484145ba82e65035f1931a07", "f8f8dfb8b06146bda1f79c4a24e2d2a3", "58d59acbd34d4f989138a71704c9ae79", "a9fb1d135c1e43a7adb343bb0e039328", "b5a56ecb17764eb4acf6a03b4f6739b3", "8062725180394e95b2ff5faa72ea6486", "a45be1baaae34a23b4429a05fc8e271d", "56c5dd0b620148eea403d57fac271810", "e8408a23a37b4b9f92ccf337dc955a86", "bcc51d97ea9143f7afd92185a393b628", "298e152029644e3b9a5dbb013584d6d9", "db76cbab13c246f09861a4aaf62ac0c6", "1e862b5f35594edc8e1867a4397def84", "db63b2c7df494fc6aba87bc53bd5faf5", "9f030cb8659a4012baa548c3a4468eb1", "28572265077d43028e9417e4b180cc09", "914d7ff36c2d46e2970fae991cb53625", "ec3115abe4b44f8ab1876e73aa972708", "70b9571ec05748e887e1df05cf2d3aba", "4a93fbbbb5d84f41aa28e9def692f219", "603a4666afbb47c49b84cf971ac0b91c", "ebc454c3d71f478480f951b06d70cacd", "e23838c27c214c05ace953637776fbd3", "ab86ac252f0d4e95a8dbdb5a7b4e0065", "3288a581faa04ab79fadbf7b926b18cf", "44a0a625a9344ffe85cfc33ce4116d47", 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torch.float32 cu\u001b[1;92mda:0\u001b[0m∈ \u001b[1m[\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m52.851417541503906\u001b[0m\u001b[1m]\u001b[0m μ = \u001b[1;36m0.3021411895751953\u001b[0m σ = \n", "\u001b[1;36m1.8155286312103271\u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "[INFO] mesh cleaning: (25642, 3) --> (13743, 3), (51268, 3) --> (27482, 3)\n", "[INFO] marching cubes result: torch.Size([13743, 3]) (-0.6841578483581543-0.7001096606254578), torch.Size([27482, 3])\n", "[INFO] unwrap uv...\n", "[INFO] save model to logs/test_mesh.obj.\n", "[load_obj] use texture from: logs/test_mesh_albedo.png\n", "[load_obj] load texture: (1024, 1024, 3)\n", "[Mesh loading] v: torch.Size([13743, 3]), f: torch.Size([27482, 3])\n", "[Mesh loading] vn: torch.Size([13743, 3]), fn: torch.Size([27482, 3])\n", "[Mesh loading] vt: torch.Size([16725, 2]), ft: torch.Size([27482, 3])\n", "[INFO] load image from data/test_rgba.png...\n", "[INFO] loading zero123...\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "448e8b3721d5431bb025575c643b668b", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Loading pipeline components...: 0%| | 0/6 [00:00" ], "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#@title render a video for displaying\n", "\n", "# the final mesh is saved to ./logs/NAME.obj\n", "%run -m kiui.render logs/{NAME}.obj --save_video {NAME}.mp4 --wogui --force_cuda_rast\n", "\n", "from IPython.display import HTML\n", "from base64 import b64encode\n", "\n", "def show_video(video_path, video_width=450):\n", " video_file = open(video_path, \"r+b\").read()\n", " video_url = f\"data:video/mp4;base64,{b64encode(video_file).decode()}\"\n", " return HTML(f\"\"\"\"\"\")\n", "\n", "show_video(f'{NAME}.mp4')" ] } ], "metadata": { "accelerator": "GPU", "colab": { "gpuType": "T4", "provenance": [] 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