clevr_data_generation.ipynb

clevr_data_generation.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "clevr_data_generation.ipynb",
      "private_outputs": true,
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyOiaq0p/OYpNIjNqEMZTVCj",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/nanlliu/ccaa9beacfbb627b2da15790c0275fa6/clevr_data_generation.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "y0RtoucqCRZc"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iumxS_FEDL3q"
      },
      "source": [
        "%cd /content/gdrive/MyDrive/clevr-dataset-gen"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ErCuPfVSEpgp"
      },
      "source": [
        "%cd /content/gdrive/MyDrive/clevr-dataset-gen/image_generation"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NT-LW2iBQ2sJ"
      },
      "source": [
        "!apt install blender\n",
        "!apt install libboost-all-dev\n",
        "!apt install libgl1-mesa-dev"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ojIwubdnROwZ"
      },
      "source": [
        "blender_version = 'blender2.79' #@param [\"blender2.79\", \"blender2.80\", \"blender2.81\", \"blender2.82\", \"blender2.83\", \"blender2.90.1\", \"blender2.91.2\"] {allow-input: false}\n",
        "gpu_enabled = True #@param {type:\"boolean\"}\n",
        "cpu_enabled = False #@param {type:\"boolean\"}"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BxAsAPz9SBUa"
      },
      "source": [
        "if blender_version == \"blender2.79\":\n",
        "    download_path=\"https://download.blender.org/release/Blender2.79/blender-2.79-linux-glibc219-x86_64.tar.bz2\"\n",
        "else:\n",
        "  raise NotImplementedError"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AAX05CUVYyM9"
      },
      "source": [
        "!mkdir $blender_version\n",
        "if blender_version == \"blender2.79\":\n",
        "    !wget -O '{blender_version}.tar.xz' -nc $download_path\n",
        "    !tar xf '{blender_version}.tar.xz' -C ./$blender_version --strip-components=1\n",
        "else:\n",
        "  raise NotImplementedError"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Bw4p_etoY5LE"
      },
      "source": [
        "import os\n",
        "\n",
        "os.environ[\"LD_PRELOAD\"] = \"\"\n",
        "\n",
        "!apt update\n",
        "!apt remove libtcmalloc-minimal4\n",
        "!apt install libtcmalloc-minimal4\n",
        "os.environ[\"LD_PRELOAD\"] = \"/usr/lib/x86_64-linux-gnu/libtcmalloc_minimal.so.4.3.0\"\n",
        "\n",
        "!echo $LD_PRELOAD"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mo2mXUKbZPTN"
      },
      "source": [
        "!apt install libboost-all-dev\n",
        "!apt install libgl1-mesa-dev\n",
        "!apt install libglu1-mesa libsm-dev"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KG-U_Ym9aGm6"
      },
      "source": [
        "%cd /content/gdrive/MyDrive/clevr-dataset-gen/image_generation/ \n",
        "!echo $PWD >> blender2.79/2.79/python/lib/python3.5/site-packages/clevr.pth"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zpVm5OzsUJ8h"
      },
      "source": [
        "output_image_dir = YOUR_IMAGE_DIR\n",
        "output_scene_dir = YOUR_SCENE_DIR\n",
        "output_scene_file_path = YOUR_OVERALL_SCENE_FILE_PATH\n",
        "output_blend_dir = YOUR_OUTPUT_BLENDER_DIR[OPTIONAL]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3Dc2q2_aDrit"
      },
      "source": [
        "!sudo ./$blender_version/blender \\\n",
        "--background --python render_images.py -- --num_images=9 --width=128 --height=128 \\\n",
        "--render_num_samples=64 --min_objects=1 --max_objects=5 --min_pixels_per_object=100 \\\n",
        "--output_image_dir=$output_image_dir \\\n",
        "--output_scene_dir=$output_scene_dir \\\n",
        "--output_scene_file=$output_scene_file_path \\\n",
        "--output_blend_dir=$output_blend_dir \\\n",
        "--min_dist=1 --margin=1 --use_gpu=1 &> /dev/null"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jMKmx3nNwY5g"
      },
      "source": [
        "import os\n",
        "import json\n",
        "import numpy as np\n",
        "from PIL import Image\n",
        "from matplotlib import pyplot as plt\n",
        "\n",
        "img_id = 0\n",
        "img_path = os.path.join(output_image_dir, 'CLEVR_new_{:06}.png'.format(img_id))\n",
        "im = Image.open(img_path).convert('RGB')\n",
        "im = np.array(im)\n",
        "\n",
        "scene_path = os.path.join(output_scene_dir, 'CLEVR_new_{:06}.json'.format(img_id))\n",
        "with open(scene_path, 'r') as f:\n",
        "  scene = json.load(f)\n",
        "\n",
        "obj_names = []\n",
        "for obj in scene['objects']:\n",
        "  name = ' '.join([obj['size'], obj['color'], obj['material'], obj['shape']])\n",
        "  obj_names.append(name)\n",
        "\n",
        "for relation, indices in scene['relationships'].items():\n",
        "  for i, js in enumerate(indices):\n",
        "    for j in js:\n",
        "      print(obj_names[j], relation, obj_names[i])\n",
        "\n",
        "if len(obj_names) == 1:\n",
        "  print(obj_names[0])\n",
        "\n",
        "plt.figure()\n",
        "plt.imshow(im)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8NDj0rURX0c1"
      },
      "source": [
        "from PIL import Image\n",
        "import torchvision\n",
        "import torch\n",
        "import numpy as np\n",
        "from matplotlib import pyplot as plt\n",
        "\n",
        "images = []\n",
        "\n",
        "for i in range(9):\n",
        "  img_path = os.path.join(output_image_dir, 'CLEVR_new_{:06}.png'.format(i))\n",
        "  im = Image.open(img_path).convert('RGB')\n",
        "  im = np.array(im).transpose(2, 0, 1)\n",
        "  images.append(im)\n",
        "\n",
        "images = torch.from_numpy(np.array(images))\n",
        "grid = torchvision.utils.make_grid(images, nrow=3)\n",
        "\n",
        "plt.figure(figsize = (20,20))\n",
        "plt.imshow(grid.permute(1, 2, 0), interpolation='nearest')"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}

Hi, thanks for providing the convenient colab code. I tried to run your code to render Clevr images, however after following the steps and to the point where I ran this chunk:

!sudo ./$blender_version/blender
--background --python render_images.py -- --num_images=9 --width=128 --height=128
--render_num_samples=64 --min_objects=1 --max_objects=5 --min_pixels_per_object=100
--output_image_dir= a
output_scene_dir
--output_scene_file= b
output_blend_dir
--min_dist=1 --margin=1 --use_gpu=1 &> /dev/null

it actually didn't render any images at all, but it didn't prompt me any error messages either, could you assist me with this issue? Thanks.

As pointed out, this code doesn't work anymore. Here is my updated version of the code.