tiny_nerf_ResNet.ipynb

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\n"
                },
                "metadata": {}
              }
            ]
          }
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      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/BoyoungH/2D-to-3D-Nerf/blob/main/tiny_nerf_ResNet.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
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        },
        "id": "9eIfAMiQblpi",
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      },
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          "text": [
            "Mounted at /content/drive\n"
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        }
      ]
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        "!pip install git+https://github.com/aliutkus/torchsearchsorted\n",
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      },
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          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting git+https://github.com/aliutkus/torchsearchsorted\n",
            "  Cloning https://github.com/aliutkus/torchsearchsorted to /tmp/pip-req-build-pvtuv4ox\n",
            "  Running command git clone --filter=blob:none --quiet https://github.com/aliutkus/torchsearchsorted /tmp/pip-req-build-pvtuv4ox\n",
            "  Resolved https://github.com/aliutkus/torchsearchsorted to commit 22b628aa348abb854aef8660fed67d98b7676fc9\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Building wheels for collected packages: torchsearchsorted\n",
            "  Building wheel for torchsearchsorted (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for torchsearchsorted: filename=torchsearchsorted-1.1-cp310-cp310-linux_x86_64.whl size=6547191 sha256=5674748a4b5c9e1fc57fff7fedb150235cf2e3228d51429a5b0f21d1176ffdef\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-8n1_yra4/wheels/66/03/bf/287777e30536367f12403b7ecbb6eb92dc5045053c9132cece\n",
            "Successfully built torchsearchsorted\n",
            "Installing collected packages: torchsearchsorted\n",
            "Successfully installed torchsearchsorted-1.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "8hHZ0LnoFh_c"
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import torch\n",
        "\n",
        "from torch import nn, optim\n",
        "\n",
        "\n",
        "def get_coarse_query_points(ds, N_c, t_i_c_bin_edges, t_i_c_gap, os):\n",
        "    u_is_c = torch.rand(*list(ds.shape[:2]) + [N_c]).to(ds)\n",
        "    t_is_c = t_i_c_bin_edges + u_is_c * t_i_c_gap\n",
        "    r_ts_c = os[..., None, :] + t_is_c[..., :, None] * ds[..., None, :]\n",
        "    return (r_ts_c, t_is_c)\n",
        "\n",
        "\n",
        "def get_fine_query_points(w_is_c, N_f, t_is_c, t_f, os, ds, r_ts_c, N_d, d_std, t_n):\n",
        "    w_is_c = w_is_c + 1e-5\n",
        "    pdfs = w_is_c / torch.sum(w_is_c, dim=-1, keepdim=True)\n",
        "    cdfs = torch.cumsum(pdfs, dim=-1)\n",
        "    cdfs = torch.cat([torch.zeros_like(cdfs[..., :1]), cdfs[..., :-1]], dim=-1)\n",
        "\n",
        "    us = torch.rand(list(cdfs.shape[:-1]) + [N_f]).to(w_is_c)\n",
        "\n",
        "    idxs = torch.searchsorted(cdfs, us, right=True)\n",
        "    t_i_f_bottom_edges = torch.gather(t_is_c, 2, idxs - 1)\n",
        "    idxs_capped = idxs.clone()\n",
        "    max_ind = cdfs.shape[-1]\n",
        "    idxs_capped[idxs_capped == max_ind] = max_ind - 1\n",
        "    t_i_f_top_edges = torch.gather(t_is_c, 2, idxs_capped)\n",
        "    t_i_f_top_edges[idxs == max_ind] = t_f\n",
        "    t_i_f_gaps = t_i_f_top_edges - t_i_f_bottom_edges\n",
        "    u_is_f = torch.rand_like(t_i_f_gaps).to(os)\n",
        "    t_is_f = t_i_f_bottom_edges + u_is_f * t_i_f_gaps\n",
        "\n",
        "    # See Section B.1 in the Supplementary Materials and:\n",
        "    # https://github.com/sxyu/pixel-nerf/blob/a5a514224272a91e3ec590f215567032e1f1c260/src/render/nerf.py#L150.\n",
        "    t_is_d = (w_is_c * r_ts_c[..., 2]).sum(dim=-1)\n",
        "    t_is_d = t_is_d.unsqueeze(2).repeat((1, 1, N_d))\n",
        "    t_is_d = t_is_d + torch.normal(0, d_std, size=t_is_d.shape).to(t_is_d)\n",
        "    t_is_d = torch.clamp(t_is_d, t_n, t_f)\n",
        "\n",
        "    t_is_f = torch.cat([t_is_c, t_is_f.detach(), t_is_d], dim=-1)\n",
        "    (t_is_f, _) = torch.sort(t_is_f, dim=-1)\n",
        "    r_ts_f = os[..., None, :] + t_is_f[..., :, None] * ds[..., None, :]\n",
        "\n",
        "    return (r_ts_f, t_is_f)\n",
        "\n",
        "def get_image_features_for_query_points(r_ts, camera_distance, scale, W_i):\n",
        "    pi_x_is = r_ts[..., :2] / (camera_distance - r_ts[..., 2].unsqueeze(-1))\n",
        "    pi_x_is = pi_x_is / scale\n",
        "    pi_x_is[..., 1] = -1 * pi_x_is[..., 1]\n",
        "    pi_x_is = pi_x_is.permute(2, 0, 1, 3)\n",
        "    W_i = W_i.repeat(pi_x_is.shape[0], 1, 1, 1)\n",
        "    z_is = nn.functional.grid_sample(W_i, pi_x_is, align_corners=True, padding_mode=\"border\")\n",
        "    z_is = z_is.permute(2, 3, 0, 1)\n",
        "    return z_is\n",
        "\n",
        "\n",
        "def render_radiance_volume(r_ts, ds, z_is, chunk_size, F, t_is):\n",
        "    r_ts_flat = r_ts.reshape((-1, 3))\n",
        "    ds_rep = ds.unsqueeze(2).repeat(1, 1, r_ts.shape[-2], 1)\n",
        "    ds_flat = ds_rep.reshape((-1, 3))\n",
        "    z_is_flat = z_is.reshape((ds_flat.shape[0], -1))\n",
        "    c_is = []\n",
        "    sigma_is = []\n",
        "    for chunk_start in range(0, r_ts_flat.shape[0], chunk_size):\n",
        "        r_ts_batch = r_ts_flat[chunk_start : chunk_start + chunk_size]\n",
        "        ds_batch = ds_flat[chunk_start : chunk_start + chunk_size]\n",
        "        w_is_batch = z_is_flat[chunk_start : chunk_start + chunk_size]\n",
        "        preds = F(r_ts_batch, ds_batch, w_is_batch)\n",
        "        c_is.append(preds[\"c_is\"])\n",
        "        sigma_is.append(preds[\"sigma_is\"])\n",
        "\n",
        "    c_is = torch.cat(c_is)\n",
        "    c_is = torch.reshape(c_is, r_ts.shape)\n",
        "    sigma_is = torch.cat(sigma_is)\n",
        "    sigma_is = torch.reshape(sigma_is, r_ts.shape[:-1])\n",
        "\n",
        "    delta_is = t_is[..., 1:] - t_is[..., :-1]\n",
        "    one_e_10 = torch.Tensor([1e10]).expand(delta_is[..., :1].shape)\n",
        "    delta_is = torch.cat([delta_is, one_e_10.to(delta_is)], dim=-1)\n",
        "    delta_is = delta_is * ds.norm(dim=-1).unsqueeze(-1)\n",
        "\n",
        "    alpha_is = 1.0 - torch.exp(-sigma_is * delta_is)\n",
        "\n",
        "    T_is = torch.cumprod(1.0 - alpha_is + 1e-10, -1)\n",
        "    T_is = torch.roll(T_is, 1, -1)\n",
        "    T_is[..., 0] = 1.0\n",
        "\n",
        "    w_is = T_is * alpha_is\n",
        "\n",
        "    C_rs = (w_is[..., None] * c_is).sum(dim=-2)\n",
        "\n",
        "    return (C_rs, w_is)\n",
        "\n",
        "\n",
        "def run_one_iter_of_nerf(\n",
        "    ds,\n",
        "    N_c,\n",
        "    t_i_c_bin_edges,\n",
        "    t_i_c_gap,\n",
        "    os,\n",
        "    camera_distance,\n",
        "    scale,\n",
        "    W_i,\n",
        "    chunk_size,\n",
        "    F_c,\n",
        "    N_f,\n",
        "    t_f,\n",
        "    N_d,\n",
        "    d_std,\n",
        "    t_n,\n",
        "    F_f,\n",
        "):\n",
        "    (r_ts_c, t_is_c) = get_coarse_query_points(ds, N_c, t_i_c_bin_edges, t_i_c_gap, os)\n",
        "    z_is_c = get_image_features_for_query_points(r_ts_c, camera_distance, scale,  W_i)\n",
        "    (C_rs_c, w_is_c) = render_radiance_volume(\n",
        "        r_ts_c, ds, z_is_c, chunk_size, F_c, t_is_c\n",
        "    )\n",
        "\n",
        "    (r_ts_f, t_is_f) = get_fine_query_points(\n",
        "        w_is_c, N_f, t_is_c, t_f, os, ds, r_ts_c, N_d, d_std, t_n\n",
        "    )\n",
        "    z_is_f = get_image_features_for_query_points(r_ts_f, camera_distance, scale, W_i)\n",
        "    (C_rs_f, _) = render_radiance_volume(r_ts_f, ds, z_is_f, chunk_size, F_f, t_is_f)\n",
        "    return (C_rs_c, C_rs_f)\n",
        "\n",
        "\n",
        "class NeRFMLP(nn.Module):\n",
        "    def __init__(self):\n",
        "        super().__init__()\n",
        "        self.L_pos = 6\n",
        "        self.L_dir = 0\n",
        "        pos_enc_feats = 3 + 3 * 2 * self.L_pos\n",
        "        dir_enc_feats = 3 + 3 * 2 * self.L_dir\n",
        "        # Set up ResNet MLP.\n",
        "        net_width = 512\n",
        "        self.first_layer = nn.Sequential(\n",
        "            nn.Linear(pos_enc_feats + dir_enc_feats, net_width)\n",
        "        )\n",
        "        self.n_resnet_blocks = 5\n",
        "        z_linears = []\n",
        "        mlps = []\n",
        "        for resnet_block in range(self.n_resnet_blocks):\n",
        "            z_linears.append(nn.Linear(net_width, net_width))\n",
        "            mlps.append(\n",
        "                nn.Sequential(\n",
        "                    nn.Linear(net_width, net_width),\n",
        "                    nn.ReLU(),\n",
        "                    nn.Linear(net_width, net_width),\n",
        "                    nn.ReLU(),\n",
        "                )\n",
        "            )\n",
        "\n",
        "        self.z_linears = nn.ModuleList(z_linears)\n",
        "        self.mlps = nn.ModuleList(mlps)\n",
        "        self.final_layer = nn.Linear(net_width, 4)\n",
        "\n",
        "    def forward(self, xs, ds, zs):\n",
        "        xs_encoded = [xs]\n",
        "        for l_pos in range(self.L_pos):\n",
        "            xs_encoded.append(torch.sin(2 ** l_pos * torch.pi * xs))\n",
        "            xs_encoded.append(torch.cos(2 ** l_pos * torch.pi * xs))\n",
        "\n",
        "        xs_encoded = torch.cat(xs_encoded, dim=-1)\n",
        "\n",
        "        ds = ds / ds.norm(p=2, dim=-1).unsqueeze(-1)\n",
        "        ds_encoded = [ds]\n",
        "        for l_dir in range(self.L_dir):\n",
        "            ds_encoded.append(torch.sin(2 ** l_dir * torch.pi * ds))\n",
        "            ds_encoded.append(torch.cos(2 ** l_dir * torch.pi * ds))\n",
        "\n",
        "        ds_encoded = torch.cat(ds_encoded, dim=-1)\n",
        "\n",
        "        outputs = self.first_layer(torch.cat([xs_encoded, ds_encoded], dim=-1))\n",
        "        for block_idx in range(self.n_resnet_blocks):\n",
        "            resnet_zs = self.z_linears[block_idx](zs)\n",
        "            outputs = outputs + resnet_zs\n",
        "            outputs = self.mlps[block_idx](outputs) + outputs\n",
        "\n",
        "        outputs = self.final_layer(outputs)\n",
        "        sigma_is = torch.relu(outputs[:, 0])\n",
        "        c_is = torch.sigmoid(outputs[:, 1:])\n",
        "        return {\"c_is\": c_is, \"sigma_is\": sigma_is}\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import torch\n",
        "import torch.nn as nn\n",
        "import torch.nn.functional as F\n",
        "\n",
        "from torchvision.models import resnet34\n",
        "class ImageEncoder(nn.Module):\n",
        "    def __init__(self):\n",
        "        super().__init__()\n",
        "        self.resnet = resnet34(True)\n",
        "\n",
        "    def forward(self, x):\n",
        "        x = self.resnet.conv1(x)\n",
        "        x = self.resnet.bn1(x)\n",
        "        feats1 = self.resnet.relu(x)\n",
        "\n",
        "        feats2 = self.resnet.layer1(self.resnet.maxpool(feats1))\n",
        "        feats3 = self.resnet.layer2(feats2)\n",
        "        feats4 = self.resnet.layer3(feats3)\n",
        "\n",
        "        latents = [feats1, feats2, feats3, feats4]\n",
        "        latent_sz = latents[0].shape[-2:]\n",
        "        for i in range(len(latents)):\n",
        "            latents[i] = F.interpolate(\n",
        "                latents[i], latent_sz, mode=\"bilinear\", align_corners=True\n",
        "            )\n",
        "\n",
        "        latents = torch.cat(latents, dim=1)\n",
        "        return latents"
      ],
      "metadata": {
        "id": "9jE7hcKl6PMw"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Set seed.\n",
        "seed = 9458\n",
        "torch.manual_seed(seed)\n",
        "np.random.seed(seed)\n",
        "\n",
        "device = \"cuda:0\"\n",
        "F_c = NeRFMLP().to(device)\n",
        "F_f = NeRFMLP().to(device)\n",
        "E = ImageEncoder().to(device)\n",
        "chunk_size = 1024 * 32\n",
        "batch_img_size = 12 #64\n",
        "n_batch_pix = batch_img_size ** 2\n",
        "\n",
        "lr = 1e-4 #5e-4\n",
        "optimizer = optim.Adam(list(F_c.parameters()) + list(F_f.parameters()), lr=lr)\n",
        "criterion = nn.MSELoss()\n",
        "#lrate_decay = 250\n",
        "#decay_steps = lrate_decay * 1000\n",
        "#decay_rate = 0.1\n",
        "# Load dataset.\n",
        "data_f = \"/content/drive/MyDrive/nooo.npz\"\n",
        "data = np.load(data_f)\n",
        "\n",
        "images = data[\"normalized_array\"] #spongee->rgb\n",
        "img_size = images.shape[1]\n",
        "xs = torch.arange(img_size) - (img_size / 2 - 0.5)\n",
        "ys = torch.arange(img_size) - (img_size / 2 - 0.5)\n",
        "(xs, ys) = torch.meshgrid(xs, -ys, indexing=\"xy\")\n",
        "focal = float(data[\"focal\"])\n",
        "pixel_coords = torch.stack([xs, ys, torch.full_like(xs, -focal)], dim=-1)\n",
        "camera_coords = pixel_coords / focal\n",
        "init_ds = camera_coords.to(device)\n",
        "init_o = torch.Tensor(np.array([0, 0, 2.25])).to(device)\n",
        "\n",
        "test_idx = 0\n",
        "plt.imshow(images[test_idx])\n",
        "plt.show()\n",
        "test_img = torch.Tensor(images[test_idx]).to(device)\n",
        "\n",
        "source_img=images[test_idx]\n",
        "\n",
        "poses = data[\"poses\"]\n",
        "test_R = torch.Tensor(poses[test_idx, :3, :3]).to(device)\n",
        "test_ds = torch.einsum(\"ij,hwj->hwi\", test_R, init_ds)\n",
        "test_os = (test_R @ init_o).expand(test_ds.shape)\n",
        "\n",
        "camera_distance=2.25\n",
        "scale = (img_size / 2) / focal\n",
        "\n",
        "t_n = 1.0\n",
        "t_f = 4.0\n",
        "N_c = 64\n",
        "N_f = 16#128\n",
        "N_d = 16\n",
        "d_std = 0.01\n",
        "t_i_c_gap = (t_f - t_n) / N_c\n",
        "t_i_c_bin_edges = (t_n + torch.arange(N_c) * t_i_c_gap).to(device)\n",
        "\n",
        "# Start training model.\n",
        "train_idxs = np.arange(len(images)) != test_idx\n",
        "images = torch.Tensor(images[train_idxs])\n",
        "poses = torch.Tensor(poses[train_idxs])\n",
        "n_pix = img_size ** 2\n",
        "pixel_ps = torch.full((n_pix,), 1 / n_pix).to(device)\n",
        "psnrs = []\n",
        "iternums = []\n",
        "# See Section 5.3.\n",
        "num_iters = 300000\n",
        "display_every = 100\n",
        "F_c.train()\n",
        "F_f.train()\n",
        "E.eval()"
      ],
      "metadata": {
        "id": "Z9eVXoDjFoRn",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "997c6c03-ae9e-4f75-c792-2746de8dccb0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/torchvision/models/_utils.py:135: UserWarning: Using 'weights' as positional parameter(s) is deprecated since 0.13 and may be removed in the future. Please use keyword parameter(s) instead.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet34_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet34_Weights.DEFAULT` to get the most up-to-date weights.\n",
            "  warnings.warn(msg)\n",
            "Downloading: \"https://download.pytorch.org/models/resnet34-b627a593.pth\" to /root/.cache/torch/hub/checkpoints/resnet34-b627a593.pth\n",
            "100%|██████████| 83.3M/83.3M [00:00<00:00, 270MB/s]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ImageEncoder(\n",
              "  (resnet): ResNet(\n",
              "    (conv1): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)\n",
              "    (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "    (relu): ReLU(inplace=True)\n",
              "    (maxpool): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)\n",
              "    (layer1): Sequential(\n",
              "      (0): BasicBlock(\n",
              "        (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (relu): ReLU(inplace=True)\n",
              "        (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "      )\n",
              "      (1): BasicBlock(\n",
              "        (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (relu): ReLU(inplace=True)\n",
              "        (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "      )\n",
              "      (2): BasicBlock(\n",
              "        (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (relu): ReLU(inplace=True)\n",
              "        (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "      )\n",
              "    )\n",
              "    (layer2): Sequential(\n",
              "      (0): BasicBlock(\n",
              "        (conv1): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
              "        (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (relu): ReLU(inplace=True)\n",
              "        (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (downsample): Sequential(\n",
              "          (0): Conv2d(64, 128, kernel_size=(1, 1), stride=(2, 2), bias=False)\n",
              "          (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        )\n",
              "      )\n",
              "      (1): BasicBlock(\n",
              "        (conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (relu): ReLU(inplace=True)\n",
              "        (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "      )\n",
              "      (2): BasicBlock(\n",
              "        (conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (relu): ReLU(inplace=True)\n",
              "        (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "      )\n",
              "      (3): BasicBlock(\n",
              "        (conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (relu): ReLU(inplace=True)\n",
              "        (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "      )\n",
              "    )\n",
              "    (layer3): Sequential(\n",
              "      (0): BasicBlock(\n",
              "        (conv1): Conv2d(128, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
              "        (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (relu): ReLU(inplace=True)\n",
              "        (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (downsample): Sequential(\n",
              "          (0): Conv2d(128, 256, kernel_size=(1, 1), stride=(2, 2), bias=False)\n",
              "          (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        )\n",
              "      )\n",
              "      (1): BasicBlock(\n",
              "        (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (relu): ReLU(inplace=True)\n",
              "        (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "      )\n",
              "      (2): BasicBlock(\n",
              "        (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (relu): ReLU(inplace=True)\n",
              "        (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "      )\n",
              "      (3): BasicBlock(\n",
              "        (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (relu): ReLU(inplace=True)\n",
              "        (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "      )\n",
              "      (4): BasicBlock(\n",
              "        (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (relu): ReLU(inplace=True)\n",
              "        (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "      )\n",
              "      (5): BasicBlock(\n",
              "        (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (relu): ReLU(inplace=True)\n",
              "        (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "      )\n",
              "    )\n",
              "    (layer4): Sequential(\n",
              "      (0): BasicBlock(\n",
              "        (conv1): Conv2d(256, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
              "        (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (relu): ReLU(inplace=True)\n",
              "        (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (downsample): Sequential(\n",
              "          (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False)\n",
              "          (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        )\n",
              "      )\n",
              "      (1): BasicBlock(\n",
              "        (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (relu): ReLU(inplace=True)\n",
              "        (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "      )\n",
              "      (2): BasicBlock(\n",
              "        (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "        (relu): ReLU(inplace=True)\n",
              "        (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
              "        (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
              "      )\n",
              "    )\n",
              "    (avgpool): AdaptiveAvgPool2d(output_size=(1, 1))\n",
              "    (fc): Linear(in_features=512, out_features=1000, bias=True)\n",
              "  )\n",
              ")"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "source_image = torch.Tensor(test_img)\n",
        "channel_means = torch.Tensor([0.485, 0.456, 0.406]).to(device)\n",
        "channel_stds = torch.Tensor([0.229, 0.224, 0.225]).to(device)\n",
        "source_image = (source_image - channel_means) / channel_stds\n",
        "source_image = source_image.to(device).unsqueeze(0).permute(0, 3, 1, 2)\n",
        "for i in range(num_iters):\n",
        "    target_img_idx = np.random.randint(images.shape[0])\n",
        "    target_pose = poses[target_img_idx].to(device)\n",
        "    R = target_pose[:3, :3]\n",
        "    loss = 0\n",
        "\n",
        "    ds = torch.einsum(\"ij,hwj->hwi\", R, init_ds)\n",
        "    os = (R @ init_o).expand(ds.shape)\n",
        "\n",
        "    pix_idxs = pixel_ps.multinomial(n_batch_pix, False)\n",
        "    pix_idx_rows = pix_idxs // img_size\n",
        "    pix_idx_cols = pix_idxs % img_size\n",
        "    ds_batch = ds[pix_idx_rows, pix_idx_cols].reshape(\n",
        "        batch_img_size, batch_img_size, -1\n",
        "    )\n",
        "    os_batch = os[pix_idx_rows, pix_idx_cols].reshape(\n",
        "        batch_img_size, batch_img_size, -1\n",
        "    )\n",
        "\n",
        "    with torch.no_grad():\n",
        "        W_i = E(test_img.unsqueeze(0).permute(0, 3, 1, 2).to(device))\n",
        "\n",
        "    # Run NeRF.\n",
        "    (C_rs_c, C_rs_f) = run_one_iter_of_nerf(\n",
        "        ds_batch,\n",
        "        N_c,\n",
        "        t_i_c_bin_edges,\n",
        "        t_i_c_gap,\n",
        "        os_batch,\n",
        "        camera_distance,\n",
        "        scale,\n",
        "        W_i,\n",
        "        chunk_size,\n",
        "        F_c,\n",
        "        N_f,\n",
        "        t_f,\n",
        "        N_d,\n",
        "        d_std,\n",
        "        t_n,\n",
        "        F_f,\n",
        "    )\n",
        "    target_img = images[target_img_idx].to(device)\n",
        "    target_img_batch = target_img[pix_idx_rows, pix_idx_cols].reshape(C_rs_f.shape)\n",
        "    #loss = criterion(C_rs_c, target_img_batch) + criterion(C_rs_f, target_img_batch)\n",
        "    loss += criterion(C_rs_c, target_img_batch)\n",
        "    loss += criterion(C_rs_f, target_img_batch)\n",
        "    optimizer.zero_grad()\n",
        "    loss.backward()\n",
        "    optimizer.step()\n",
        "\n",
        "    #for g in optimizer.param_groups:\n",
        "    #    g[\"lr\"] = lr * decay_rate ** (i / decay_steps)\n",
        "\n",
        "    if i % display_every == 0:\n",
        "        F_c.eval()\n",
        "        F_f.eval()\n",
        "        with torch.no_grad():\n",
        "            test_W_i = E(source_image)\n",
        "            (_, C_rs_f) = run_one_iter_of_nerf(\n",
        "                test_ds,\n",
        "                N_c,\n",
        "                t_i_c_bin_edges,\n",
        "                t_i_c_gap,\n",
        "                test_os,\n",
        "                camera_distance,\n",
        "                scale,\n",
        "                test_W_i,\n",
        "                #W_i,\n",
        "                chunk_size,\n",
        "                F_c,\n",
        "                N_f,\n",
        "                t_f,\n",
        "                N_d,\n",
        "                d_std,\n",
        "                t_n,\n",
        "                F_f,\n",
        "            )\n",
        "\n",
        "        loss = criterion(C_rs_f, test_img)\n",
        "        print(f\"Loss: {loss.item()}\")\n",
        "        psnr = -10.0 * torch.log10(loss)\n",
        "\n",
        "        psnrs.append(psnr.item())\n",
        "        iternums.append(i)\n",
        "\n",
        "        plt.figure(figsize=(10, 4))\n",
        "        plt.subplot(121)\n",
        "        plt.imshow(C_rs_f.detach().cpu().numpy())\n",
        "        plt.title(f\"Iteration {i}\")\n",
        "        plt.subplot(122)\n",
        "        plt.plot(iternums, psnrs)\n",
        "        plt.title(\"PSNR\")\n",
        "        plt.show()\n",
        "\n",
        "        F_c.train()\n",
        "        F_f.train()\n",
        "\n",
        "print(\"Done!\")"
      ],
      "metadata": {
        "id": "VWextW26Fvem",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "outputId": "d47ce7c2-3f15-4fa1-b5d9-c9e1dab8c339"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "OutOfMemoryError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mOutOfMemoryError\u001b[0m                          Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-8-a29937c9c086>\u001b[0m in \u001b[0;36m<cell line: 6>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     62\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mno_grad\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[1;32m     63\u001b[0m             \u001b[0mtest_W_i\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mE\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msource_image\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 64\u001b[0;31m             (_, C_rs_f) = run_one_iter_of_nerf(\n\u001b[0m\u001b[1;32m     65\u001b[0m                 \u001b[0mtest_ds\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     66\u001b[0m                 \u001b[0mN_c\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m<ipython-input-2-2d2a1e2bf6a0>\u001b[0m in \u001b[0;36mrun_one_iter_of_nerf\u001b[0;34m(ds, N_c, t_i_c_bin_edges, t_i_c_gap, os, camera_distance, scale, W_i, chunk_size, F_c, N_f, t_f, N_d, d_std, t_n, F_f)\u001b[0m\n\u001b[1;32m    114\u001b[0m     \u001b[0;34m(\u001b[0m\u001b[0mr_ts_c\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt_is_c\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_coarse_query_points\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mN_c\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt_i_c_bin_edges\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt_i_c_gap\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    115\u001b[0m     \u001b[0mz_is_c\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_image_features_for_query_points\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr_ts_c\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcamera_distance\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscale\u001b[0m\u001b[0;34m,\u001b[0m  \u001b[0mW_i\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 116\u001b[0;31m     (C_rs_c, w_is_c) = render_radiance_volume(\n\u001b[0m\u001b[1;32m    117\u001b[0m         \u001b[0mr_ts_c\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mz_is_c\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mchunk_size\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mF_c\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt_is_c\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    118\u001b[0m     )\n",
            "\u001b[0;32m<ipython-input-2-2d2a1e2bf6a0>\u001b[0m in \u001b[0;36mrender_radiance_volume\u001b[0;34m(r_ts, ds, z_is, chunk_size, F, t_is)\u001b[0m\n\u001b[1;32m     60\u001b[0m     \u001b[0mds_rep\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munsqueeze\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrepeat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mr_ts\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\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;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     61\u001b[0m     \u001b[0mds_flat\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mds_rep\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m3\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---> 62\u001b[0;31m     \u001b[0mz_is_flat\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mz_is\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mds_flat\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m1\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     63\u001b[0m     \u001b[0mc_is\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[1;32m     64\u001b[0m     \u001b[0msigma_is\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;31mOutOfMemoryError\u001b[0m: CUDA out of memory. Tried to allocate 4.88 GiB (GPU 0; 14.75 GiB total capacity; 12.08 GiB already allocated; 1.52 GiB free; 13.09 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%matplotlib inline\n",
        "from ipywidgets import interactive, widgets\n",
        "import numpy as np\n",
        "import torch\n",
        "import torchvision.transforms.functional as F\n",
        "from torchvision.transforms import InterpolationMode\n",
        "from torch.autograd import grad\n",
        "import torch.nn.functional as nnF\n",
        "\n",
        "# checkpoint = torch.load('/content/nerf_model.pth')\n",
        "# F_c.load_state_dict(checkpoint['model_state_dict'])\n",
        "# optimizer.load_state_dict(checkpoint['optimizer_state_dict'])\n",
        "# iteration = checkpoint['iteration']\n",
        "# loss = checkpoint['loss']\n",
        "# psnrs = checkpoint['psnrs']\n",
        "# iternums = checkpoint['iternums']\n",
        "# C_rs_c = checkpoint['C_rs_c']\n",
        "# C_rs_f = checkpoint['C_rs_f']\n",
        "\n",
        "\n",
        "def trans_t(t):\n",
        "  return torch.tensor([\n",
        "  [1,0,0,0],\n",
        "  [0,1,0,0],\n",
        "  [0,0,1,t],\n",
        "  [0,0,0,1],\n",
        "  ], dtype=torch.float32)\n",
        "\n",
        "def rot_phi(phi):\n",
        "    phi = torch.tensor(phi)\n",
        "    return torch.tensor([\n",
        "        [1, 0, 0, 0],\n",
        "        [0, torch.cos(phi), -torch.sin(phi), 0],\n",
        "        [0, torch.sin(phi), torch.cos(phi), 0],\n",
        "        [0, 0, 0, 1],\n",
        "    ], dtype=torch.float32)\n",
        "\n",
        "def rot_theta(th):\n",
        "    th = torch.tensor(th)\n",
        "    return torch.tensor([\n",
        "        [torch.cos(th), 0, -torch.sin(th), 0],\n",
        "        [0, 1, 0, 0],\n",
        "        [torch.sin(th), 0, torch.cos(th), 0],\n",
        "        [0, 0, 0, 1],\n",
        "    ], dtype=torch.float32)\n",
        "\n",
        "def pose_spherical(theta, phi, radius):\n",
        "  c2w = trans_t(radius)\n",
        "  c2w = rot_phi(phi/180.*np.pi) @ c2w\n",
        "  c2w = rot_theta(theta/180.*np.pi) @ c2w\n",
        "  c2w = torch.tensor([[-1,0,0,0],[0,0,1,0],[0,1,0,0],[0,0,0,1]], dtype=torch.float32) @ c2w\n",
        "  return c2w\n",
        "\n",
        "def f(**kwargs):\n",
        "  c2w = pose_spherical(**kwargs)\n",
        "  c2w = c2w.to(device)\n",
        "  test_R = torch.Tensor(poses[test_idx, :3, :3]).to(device)\n",
        "  test_R = c2w[:3, :3].to(device)\n",
        "  test_ds = torch.einsum(\"ij,hwj->hwi\", test_R, init_ds)\n",
        "  test_os = (test_R @ init_o).expand(test_ds.shape)\n",
        "  with torch.no_grad():\n",
        "            (_, C_rs_f) = run_one_iter_of_nerf(\n",
        "                test_ds,\n",
        "                N_c,\n",
        "                t_i_c_bin_edges,\n",
        "                t_i_c_gap,\n",
        "                test_os,\n",
        "                chunk_size,\n",
        "                F_c,\n",
        "                N_f,\n",
        "                t_f,\n",
        "                F_f,\n",
        "                N_d,\n",
        "                d_std,\n",
        "            )\n",
        "  img = torch.clamp((C_rs_f.detach()), 0, 1)\n",
        "  img = img.permute(2, 0, 1)\n",
        "\n",
        "  img_np = img.cpu().numpy()\n",
        "  plt.figure(2, figsize=(20,6))\n",
        "  plt.imshow(img_np.transpose(1, 2, 0))\n",
        "  plt.show()\n",
        "\n",
        "sldr = lambda v, mi, ma: widgets.FloatSlider(\n",
        "  value=v,\n",
        "  min=mi,\n",
        "  max=ma,\n",
        "  step=.01,\n",
        ")\n",
        "\n",
        "names = [\n",
        "  ['theta', [100., 0., 360]],\n",
        "  ['phi', [-30., 0, 360]],\n",
        "  ['radius', [4., 3., 5.]],\n",
        "]\n",
        "\n",
        "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
        "interactive_plot = interactive(f, **{s[0] : sldr(*s[1]) for s in names})\n",
        "output = interactive_plot.children[-1]\n",
        "output.layout.height = '350px'\n",
        "interactive_plot"
      ],
      "metadata": {
        "id": "XBMEelEmCcNa",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 463,
          "referenced_widgets": [
            "4891628d2fdb46dea3cd875cdc76c3c1",
            "41df9236526f4c139f673dc0af1e4e9b",
            "7a9604c105bc4ee482fa806bf5586a35",
            "2f18e426e63948979d39ba8dd37d0387",
            "5734c6bade5a48e9829157bbd95b8314",
            "669e9537701a440e832bfce29045b91e",
            "eb82a9a7362d412cbd1510f0c6f8edfb",
            "03c7b333d75f429d9234f321c36c2104",
            "8bc4176a5aee4bb88edc2032b6919c00",
            "69262207859749f6855f817d842a2728",
            "25de6c1c8ea14dedaaa93ea11f463f2f",
            "578365f1ad9748c8b6f38c638aebfe73",
            "45dc0fcdd10d43899649c7e68011e179"
          ]
        },
        "outputId": "d0fd821e-07f3-4904-a15f-ca768d05abd2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "interactive(children=(FloatSlider(value=100.0, description='theta', max=360.0, step=0.01), FloatSlider(value=0…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "4891628d2fdb46dea3cd875cdc76c3c1"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "frames = []\n",
        "from tqdm import tqdm_notebook as tqdm\n",
        "for th in tqdm(np.linspace(0., 360., 120, endpoint=False)):\n",
        "    c2w = pose_spherical(th, -30., 4.)\n",
        "    test_R = torch.Tensor(poses[test_idx, :3, :3]).to(device)\n",
        "    test_R = c2w[:3, :3].to(device)\n",
        "    test_ds = torch.einsum(\"ij,hwj->hwi\", test_R, init_ds)\n",
        "    test_os = (test_R @ init_o).expand(test_ds.shape)\n",
        "    with torch.no_grad():\n",
        "            (_, C_rs_f) = run_one_iter_of_nerf(\n",
        "                test_ds,\n",
        "                N_c,\n",
        "                t_i_c_bin_edges,\n",
        "                t_i_c_gap,\n",
        "                test_os,\n",
        "                chunk_size,\n",
        "                F_c,\n",
        "                N_f,\n",
        "                t_f,\n",
        "                F_f,\n",
        "                N_d,\n",
        "                d_std,\n",
        "            )\n",
        "    frames.append((C_rs_f.detach().cpu().numpy()).astype(np.uint8))\n",
        "\n",
        "import cv2\n",
        "\n",
        "frames_resized = []\n",
        "for frame in frames:\n",
        "    frame_resized = cv2.resize(frame, (304, 304))\n",
        "    frames_resized.append(frame_resized)\n",
        "\n",
        "import imageio\n",
        "f = 'video.mp4'\n",
        "imageio.mimwrite(f, frames_resized, fps=30, quality=7)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 123,
          "referenced_widgets": [
            "89faa9b4fc17459bb8936310a0b10580",
            "fdd8fdeae5f446abad4e7efe611b396d",
            "2061555f95f64020aad9033357350f1a",
            "41fe1c61f4ab410ab9f24c167f57689f",
            "7a5c8bdce10345c6bc169fc64a381d61",
            "04b8185d9d054ab48029e4c4c205d027",
            "c485480aed4a4661a8a0493d239a1ac9",
            "43698baa60334a5eabc509e80ec36bc0",
            "aa10223ecc8348ab89265f1bf202fc99",
            "c94c6b08ac3c43a4958bce709dd7a1f4",
            "4646ee74be044cde97d6ffdf60747202"
          ]
        },
        "id": "ugRNDkylf5NG",
        "outputId": "7399d7d3-0317-431a-e328-cc6194819082"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-8-a06c6cfa0d1f>:3: TqdmDeprecationWarning: This function will be removed in tqdm==5.0.0\n",
            "Please use `tqdm.notebook.tqdm` instead of `tqdm.tqdm_notebook`\n",
            "  for th in tqdm(np.linspace(0., 360., 120, endpoint=False)):\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/120 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "89faa9b4fc17459bb8936310a0b10580"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from IPython.display import HTML\n",
        "from base64 import b64encode\n",
        "mp4 = open('video.mp4','rb').read()\n",
        "data_url = \"data:video/mp4;base64,\" + b64encode(mp4).decode()\n",
        "HTML(\"\"\"\n",
        "<video width=400 controls autoplay loop>\n",
        "      <source src=\"%s\" type=\"video/mp4\">\n",
        "</video>\n",
        "\"\"\" % data_url)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 420
        },
        "id": "PMzXkyNSf6CY",
        "outputId": "ae1d0fba-3154-4163-be90-86862023c69c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "<video width=400 controls autoplay loop>\n",
              "      <source 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              "</video>\n"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    }
  ]
}