{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 9,
      "id": "593f43b1-8665-42e0-bac7-c8b5e073ce6d",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "593f43b1-8665-42e0-bac7-c8b5e073ce6d",
        "outputId": "8e3ab548-4a3d-4e93-a26d-c02e91e0788f"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting git+http://hf.co/usm3d/tools.git\n",
            "  Cloning http://hf.co/usm3d/tools.git to /tmp/pip-req-build-f68pznqf\n",
            "  Running command git clone --filter=blob:none --quiet http://hf.co/usm3d/tools.git /tmp/pip-req-build-f68pznqf\n",
            "  warning: redirecting to https://huggingface.co/usm3d/tools.git/\n",
            "  Resolved http://hf.co/usm3d/tools.git to commit 0614af07256edd3fc13b8b606b58ee2c3f0804d0\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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          ]
        }
      ],
      "source": [
        "!pip install git+http://hf.co/usm3d/tools.git"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "id": "503c6bcb-aa46-46c6-8b86-566b0a470b43",
      "metadata": {
        "id": "503c6bcb-aa46-46c6-8b86-566b0a470b43"
      },
      "outputs": [],
      "source": [
        "import webdataset as wds\n",
        "import numpy as np\n",
        "from huggingface_hub import hf_hub_download\n",
        "from hoho import proc\n",
        "from tqdm import tqdm\n",
        "import sys\n",
        "sys.path.append('..')\n",
        "from vishesh_solution import *"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "b6c8c1d8",
      "metadata": {
        "id": "b6c8c1d8"
      },
      "source": [
        "# Loading part of training data\n",
        "\n",
        "For simplicity we are showing example only on a once shard of data"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from huggingface_hub import notebook_login\n",
        "\n",
        "notebook_login()\n"
      ],
      "metadata": {
        "colab": {
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      },
      "id": "x6yjrN6TF3IC",
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a21542b2591f43bda2d96733f83ca928"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "id": "88f4fc8f-efa9-404b-9073-c7d4a73f9075",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
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      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "hoho_v3_000-of-032.tar.gz:   0%|          | 0.00/1.01G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "8d7f7fb6fd5e4726854c8e086a36513d"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "dict_keys(['__key__', '__imagekey__', '__url__', 'ade20k', 'depthcm', 'gestalt', 'wf_vertices', 'wf_edges', 'edge_semantics', 'mesh_vertices', 'mesh_faces', 'face_semantics', 'K', 'R', 't', 'images', 'points3d', 'cameras'])\n"
          ]
        }
      ],
      "source": [
        "# One shard of the dataset\n",
        "dataset = wds.WebDataset(hf_hub_download(repo_id='usm3d/hoho-train-set',\n",
        "            filename='data/train/hoho_v3_000-of-032.tar.gz',\n",
        "            repo_type=\"dataset\"))\n",
        "\n",
        "dataset = dataset.decode()\n",
        "dataset = dataset.map(proc)\n",
        "\n",
        "for entry in dataset:\n",
        "    human_entry = convert_entry_to_human_readable(entry)\n",
        "    print (entry.keys())\n",
        "    break\n"
      ]
    },
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            "\u001b[0;31mHTTPError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_errors.py\u001b[0m in \u001b[0;36mhf_raise_for_status\u001b[0;34m(response, endpoint_name)\u001b[0m\n\u001b[1;32m    303\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--> 304\u001b[0;31m         \u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mraise_for_status\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    305\u001b[0m     \u001b[0;32mexcept\u001b[0m \u001b[0mHTTPError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\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/requests/models.py\u001b[0m in \u001b[0;36mraise_for_status\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1020\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mhttp_error_msg\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1021\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mHTTPError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhttp_error_msg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresponse\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[0m\n\u001b[0m\u001b[1;32m   1022\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mHTTPError\u001b[0m: 404 Client Error: Not Found for url: https://huggingface.co/datasets/usm3d/hoho-train-set/resolve/main/data/train/hoho_v3_025-of-032.tar.gz",
            "\nThe above exception was the direct cause of the following exception:\n",
            "\u001b[0;31mEntryNotFoundError\u001b[0m                        Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-12-49d141b59cb5>\u001b[0m in \u001b[0;36m<cell line: 2>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# Download all the datasets:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m32\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----> 3\u001b[0;31m     dataset = wds.WebDataset(hf_hub_download(repo_id='usm3d/hoho-train-set',\n\u001b[0m\u001b[1;32m      4\u001b[0m             \u001b[0mfilename\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34mf'data/train/hoho_v3_{str(i).zfill(3)}-of-032.tar.gz'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m             repo_type=\"dataset\"))\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_validators.py\u001b[0m in \u001b[0;36m_inner_fn\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    112\u001b[0m             \u001b[0mkwargs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msmoothly_deprecate_use_auth_token\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn_name\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhas_token\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mhas_token\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    113\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 114\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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    115\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    116\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0m_inner_fn\u001b[0m  \u001b[0;31m# type: ignore\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/huggingface_hub/file_download.py\u001b[0m in \u001b[0;36mhf_hub_download\u001b[0;34m(repo_id, filename, subfolder, repo_type, revision, library_name, library_version, cache_dir, local_dir, user_agent, force_download, proxies, etag_timeout, token, local_files_only, headers, endpoint, legacy_cache_layout, resume_download, force_filename, local_dir_use_symlinks)\u001b[0m\n\u001b[1;32m   1219\u001b[0m         )\n\u001b[1;32m   1220\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-> 1221\u001b[0;31m         return _hf_hub_download_to_cache_dir(\n\u001b[0m\u001b[1;32m   1222\u001b[0m             \u001b[0;31m# Destination\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1223\u001b[0m             \u001b[0mcache_dir\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcache_dir\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/huggingface_hub/file_download.py\u001b[0m in \u001b[0;36m_hf_hub_download_to_cache_dir\u001b[0;34m(cache_dir, repo_id, filename, repo_type, revision, headers, proxies, etag_timeout, endpoint, local_files_only, force_download)\u001b[0m\n\u001b[1;32m   1280\u001b[0m     \u001b[0;31m# Try to get metadata (etag, commit_hash, url, size) from the server.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1281\u001b[0m     \u001b[0;31m# If we can't, a HEAD request error is returned.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1282\u001b[0;31m     (url_to_download, etag, commit_hash, expected_size, head_call_error) = _get_metadata_or_catch_error(\n\u001b[0m\u001b[1;32m   1283\u001b[0m         \u001b[0mrepo_id\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mrepo_id\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1284\u001b[0m         \u001b[0mfilename\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfilename\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/huggingface_hub/file_download.py\u001b[0m in \u001b[0;36m_get_metadata_or_catch_error\u001b[0;34m(repo_id, filename, repo_type, revision, endpoint, proxies, etag_timeout, headers, local_files_only, relative_filename, storage_folder)\u001b[0m\n\u001b[1;32m   1720\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[1;32m   1721\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-> 1722\u001b[0;31m                 \u001b[0mmetadata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_hf_file_metadata\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mproxies\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mproxies\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0metag_timeout\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheaders\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   1723\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mEntryNotFoundError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mhttp_error\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1724\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mstorage_folder\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mrelative_filename\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/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_validators.py\u001b[0m in \u001b[0;36m_inner_fn\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    112\u001b[0m             \u001b[0mkwargs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msmoothly_deprecate_use_auth_token\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn_name\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhas_token\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mhas_token\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    113\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 114\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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    115\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    116\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0m_inner_fn\u001b[0m  \u001b[0;31m# type: ignore\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/huggingface_hub/file_download.py\u001b[0m in \u001b[0;36mget_hf_file_metadata\u001b[0;34m(url, token, proxies, timeout, library_name, library_version, user_agent, headers)\u001b[0m\n\u001b[1;32m   1643\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1644\u001b[0m     \u001b[0;31m# Retrieve metadata\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1645\u001b[0;31m     r = _request_wrapper(\n\u001b[0m\u001b[1;32m   1646\u001b[0m         \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"HEAD\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1647\u001b[0m         \u001b[0murl\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0murl\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/huggingface_hub/file_download.py\u001b[0m in \u001b[0;36m_request_wrapper\u001b[0;34m(method, url, follow_relative_redirects, **params)\u001b[0m\n\u001b[1;32m    370\u001b[0m     \u001b[0;31m# Recursively follow relative redirects\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    371\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mfollow_relative_redirects\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 372\u001b[0;31m         response = _request_wrapper(\n\u001b[0m\u001b[1;32m    373\u001b[0m             \u001b[0mmethod\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[1;32m    374\u001b[0m             \u001b[0murl\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0murl\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/huggingface_hub/file_download.py\u001b[0m in \u001b[0;36m_request_wrapper\u001b[0;34m(method, url, follow_relative_redirects, **params)\u001b[0m\n\u001b[1;32m    394\u001b[0m     \u001b[0;31m# Perform request and return if status_code is not in the retry list.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    395\u001b[0m     \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_session\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\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[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 396\u001b[0;31m     \u001b[0mhf_raise_for_status\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresponse\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    397\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    398\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_errors.py\u001b[0m in \u001b[0;36mhf_raise_for_status\u001b[0;34m(response, endpoint_name)\u001b[0m\n\u001b[1;32m    313\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0merror_code\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"EntryNotFound\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    314\u001b[0m             \u001b[0mmessage\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34mf\"{response.status_code} Client Error.\"\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m\"\\n\\n\"\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34mf\"Entry Not Found for url: {response.url}.\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 315\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mEntryNotFoundError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmessage\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    316\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    317\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0merror_code\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"GatedRepo\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mEntryNotFoundError\u001b[0m: 404 Client Error. (Request ID: Root=1-6650f1f1-0da907fe25b4cf1e24b628d1;4f1139b9-d8c5-4472-b9e9-00c209883f2c)\n\nEntry Not Found for url: https://huggingface.co/datasets/usm3d/hoho-train-set/resolve/main/data/train/hoho_v3_025-of-032.tar.gz."
          ]
        }
      ],
      "source": [
        "# Download all the datasets:\n",
        "for i in range(32):\n",
        "    dataset = wds.WebDataset(hf_hub_download(repo_id='usm3d/hoho-train-set',\n",
        "            filename=f'data/train/hoho_v3_{str(i).zfill(3)}-of-032.tar.gz',\n",
        "            repo_type=\"dataset\"))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "id": "93156fd9",
      "metadata": {
        "id": "93156fd9",
        "outputId": "de4a76e4-18a3-4deb-a3a5-bb39966f4b0b",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Point3D(id=178, xyz=array([-112.43335521, -556.28305805,  228.37245189]), rgb=array([49, 57, 57]), error=array(2.09771263), image_ids=array([6, 7]), point2D_idxs=array([2156,  348]))"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ],
      "source": [
        "human_entry['points3d'][178]"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "0c7ce110",
      "metadata": {
        "id": "0c7ce110"
      },
      "source": [
        "# Visualizing inputs"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "id": "080f1a12-06bf-4b97-8a52-d7cf416adede",
      "metadata": {
        "id": "080f1a12-06bf-4b97-8a52-d7cf416adede",
        "outputId": "5fff8d70-21b9-4ca7-952b-7dfb2324ed37",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 904
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7c698e79e140>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "plt.figure()\n",
        "plt.imshow(human_entry['gestalt'][2])\n",
        "plt.title('Gestalt segmentation')\n",
        "\n",
        "plt.figure()\n",
        "depth = np.array(human_entry['depthcm'][2])/100.\n",
        "depth[depth>20] = 0\n",
        "depth = depth/depth.max()\n",
        "plt.title('Monodepth')\n",
        "plt.imshow(depth, cmap='rainbow')\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "id": "67368b9e",
      "metadata": {
        "id": "67368b9e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 834
        },
        "outputId": "8d942fd3-4e8e-41fd-d28b-c716f6775bfa"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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              "                            \n",
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              "var x = new MutationObserver(function (mutations, observer) {{\n",
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              "            console.log([gd, 'removed!']);\n",
              "            Plotly.purge(gd);\n",
              "            observer.disconnect();\n",
              "        }}\n",
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              "    x.observe(outputEl, {childList: true});\n",
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              "</body>\n",
              "</html>"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Here is the prediction and visualization of single entry\n",
        "key, vertices, edges = predict(entry, visualize=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "id": "cc797d2d-7c81-4783-86d2-856f974d3118",
      "metadata": {
        "id": "cc797d2d-7c81-4783-86d2-856f974d3118",
        "outputId": "f8e9896f-f3e8-453b-f9a2-32d361fc1504",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2.534572293655895"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ],
      "source": [
        "from hoho import compute_WED\n",
        "\n",
        "compute_WED(vertices,\n",
        "            edges,\n",
        "            np.array(entry['wf_vertices']),\n",
        "            np.array(entry['wf_edges']),\n",
        "            ce=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "id": "ea51c630-417a-4bfd-83f6-70e8d8d33cba",
      "metadata": {
        "id": "ea51c630-417a-4bfd-83f6-70e8d8d33cba",
        "outputId": "dae3d878-9069-4152-9709-e100a93ce1d2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2.534572293655895"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ],
      "source": [
        "compute_WED(vertices,\n",
        "            edges,\n",
        "            np.array(entry['wf_vertices']),\n",
        "            np.array(entry['wf_edges']),\n",
        "            ce=1)"
      ]
    },
    {
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      "execution_count": null,
      "id": "c2554807-4acb-4971-a94f-1f9046c2299b",
      "metadata": {
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      "source": []
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