(Batch2-GDRIVE) Colab_4_(zcxu_eric_magicanimate).ipynb

{
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  "metadata": {
    "colab": {
      "provenance": [],
      "machine_shape": "hm",
      "gpuType": "A100",
      "authorship_tag": "ABX9TyPleE8Pp7gm0t6YBHiH8MBA",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/DragonFarts/Video-EZY/blob/main/(Batch2-GDRIVE)%20Colab_4_(zcxu_eric_magicanimate).ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZCcAlG1Zym1W",
        "outputId": "f06410c1-fcea-4a89-e89d-c908cbe22940"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into '/content/magicanimate'...\n",
            "remote: Enumerating objects: 120, done.\u001b[K\n",
            "remote: Counting objects: 100% (116/116), done.\u001b[K\n",
            "remote: Compressing objects: 100% (103/103), done.\u001b[K\n",
            "remote: Total 120 (delta 21), reused 0 (delta 0), pack-reused 4\u001b[K\n",
            "Receiving objects: 100% (120/120), 5.50 MiB | 7.30 MiB/s, done.\n",
            "Resolving deltas: 100% (21/21), done.\n"
          ]
        }
      ],
      "source": [
        "!git clone https://huggingface.co/spaces/zcxu-eric/magicanimate /content/magicanimate"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install -r /content/magicanimate/requirements.txt"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "3m-OqYjly7_V",
        "outputId": "76cf4077-a84b-4627-9b4b-d97bab33d73c"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "\u001b[?25hCollecting torchvision==0.15.2 (from -r /content/magicanimate/requirements.txt (line 125))\n",
            "  Downloading torchvision-0.15.2-cp310-cp310-manylinux1_x86_64.whl (6.0 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.0/6.0 MB\u001b[0m \u001b[31m118.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting xformers==0.0.22 (from -r /content/magicanimate/requirements.txt (line 126))\n",
            "  Downloading xformers-0.0.22-cp310-cp310-manylinux2014_x86_64.whl (211.6 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m211.6/211.6 MB\u001b[0m \u001b[31m8.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting diffusers==0.21.4 (from -r /content/magicanimate/requirements.txt (line 127))\n",
            "  Downloading diffusers-0.21.4-py3-none-any.whl (1.5 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.5/1.5 MB\u001b[0m \u001b[31m87.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from accelerate==0.22.0->-r /content/magicanimate/requirements.txt (line 2)) (23.2)\n",
            "Requirement already satisfied: typing-extensions>=4.0.1 in /usr/local/lib/python3.10/dist-packages (from altair==5.0.1->-r /content/magicanimate/requirements.txt (line 6)) (4.5.0)\n",
            "Requirement already satisfied: six>=1.9.0 in /usr/local/lib/python3.10/dist-packages (from google-auth==2.22.0->-r /content/magicanimate/requirements.txt (line 29)) (1.16.0)\n",
            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib==3.7.2->-r /content/magicanimate/requirements.txt (line 50)) (2.8.2)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->-r /content/magicanimate/requirements.txt (line 56)) (67.7.2)\n",
            "Requirement already satisfied: wheel in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->-r /content/magicanimate/requirements.txt (line 56)) (0.42.0)\n",
            "Collecting typing-extensions>=4.0.1 (from altair==5.0.1->-r /content/magicanimate/requirements.txt (line 6))\n",
            "  Downloading typing_extensions-4.8.0-py3-none-any.whl (31 kB)\n",
            "Requirement already satisfied: tifffile>=2019.7.26 in /usr/local/lib/python3.10/dist-packages (from scikit-image->-r /content/magicanimate/requirements.txt (line 119)) (2023.9.26)\n",
            "Requirement already satisfied: PyWavelets>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from scikit-image->-r /content/magicanimate/requirements.txt (line 119)) (1.5.0)\n",
            "Requirement already satisfied: Shapely in /usr/local/lib/python3.10/dist-packages (from imgaug->-r /content/magicanimate/requirements.txt (line 121)) (2.0.2)\n",
            "Requirement already satisfied: future in /usr/local/lib/python3.10/dist-packages (from ffmpeg-python->-r /content/magicanimate/requirements.txt (line 123)) (0.18.3)\n",
            "Building wheels for collected packages: antlr4-python3-runtime, ffmpy, lit\n",
            "  Building wheel for antlr4-python3-runtime (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for antlr4-python3-runtime: filename=antlr4_python3_runtime-4.9.3-py3-none-any.whl size=144554 sha256=e3a994bddfb4f921ef32bd848150ac0b7884bc94356200e41c0dcced57b55cd9\n",
            "  Stored in directory: /root/.cache/pip/wheels/12/93/dd/1f6a127edc45659556564c5730f6d4e300888f4bca2d4c5a88\n",
            "  Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for ffmpy: filename=ffmpy-0.3.1-py3-none-any.whl size=5579 sha256=f38ef3c5fd19f888a0dd5a1213991356f3e5b43ee67524ceee1906b2ff77efaa\n",
            "  Stored in directory: /root/.cache/pip/wheels/01/a6/d1/1c0828c304a4283b2c1639a09ad86f83d7c487ef34c6b4a1bf\n",
            "  Building wheel for lit (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for lit: filename=lit-16.0.6-py3-none-any.whl size=93584 sha256=b1f1f1d8adc57ba02170514575d0ec9db779241670a5d867b1dbceecd106c148\n",
            "  Stored in directory: /root/.cache/pip/wheels/14/f9/07/bb2308587bc2f57158f905a2325f6a89a2befa7437b2d7e137\n",
            "Successfully built antlr4-python3-runtime ffmpy lit\n",
            "Installing collected packages: tokenizers, safetensors, pytz, pydub, lit, ffmpy, cmake, antlr4-python3-runtime, zipp, xxhash, werkzeug, websockets, urllib3, tzdata, typing-extensions, tensorboard-data-server, semantic-version, rpds-py, regex, python-multipart, pyparsing, pyasn1, protobuf, pkgutil-resolve-name, pillow, orjson, omegaconf, nvidia-nvtx-cu11, nvidia-nccl-cu11, nvidia-cusparse-cu11, nvidia-curand-cu11, nvidia-cufft-cu11, nvidia-cuda-runtime-cu11, nvidia-cuda-nvrtc-cu11, nvidia-cuda-cupti-cu11, nvidia-cublas-cu11, numpy, networkx, markdown, importlib-resources, imageio-ffmpeg, idna, h11, grpcio, fonttools, filelock, ffmpeg-python, exceptiongroup, einops, dill, cycler, charset-normalizer, certifi, cachetools, av, annotated-types, aiofiles, yarl, uvicorn, referencing, pydantic-core, pyarrow, pandas, nvidia-cusolver-cu11, nvidia-cudnn-cu11, multiprocess, lightning-utilities, imageio, decord, contourpy, starlette, pydantic, matplotlib, jsonschema-specifications, huggingface-hub, httpcore, google-auth, aiohttp, transformers, jsonschema, httpx, fastapi, diffusers, tensorboard, gradio-client, datasets, altair, gradio, triton, torch, torchvision, torchmetrics, xformers, timm, pytorch-lightning, lpips, accelerate\n",
            "  Attempting uninstall: tokenizers\n",
            "    Found existing installation: tokenizers 0.15.0\n",
            "    Uninstalling tokenizers-0.15.0:\n",
            "      Successfully uninstalled tokenizers-0.15.0\n",
            "  Attempting uninstall: safetensors\n",
            "    Found existing installation: safetensors 0.4.1\n",
            "    Uninstalling safetensors-0.4.1:\n",
            "      Successfully uninstalled safetensors-0.4.1\n",
            "  Attempting uninstall: pytz\n",
            "    Found existing installation: pytz 2023.3.post1\n",
            "    Uninstalling pytz-2023.3.post1:\n",
            "      Successfully uninstalled pytz-2023.3.post1\n",
            "  Attempting uninstall: cmake\n",
            "    Found existing installation: cmake 3.27.7\n",
            "    Uninstalling cmake-3.27.7:\n",
            "      Successfully uninstalled cmake-3.27.7\n",
            "  Attempting uninstall: zipp\n",
            "    Found existing installation: zipp 3.17.0\n",
            "    Uninstalling zipp-3.17.0:\n",
            "      Successfully uninstalled zipp-3.17.0\n",
            "  Attempting uninstall: xxhash\n",
            "    Found existing installation: xxhash 3.4.1\n",
            "    Uninstalling xxhash-3.4.1:\n",
            "      Successfully uninstalled xxhash-3.4.1\n",
            "  Attempting uninstall: werkzeug\n",
            "    Found existing installation: Werkzeug 3.0.1\n",
            "    Uninstalling Werkzeug-3.0.1:\n",
            "      Successfully uninstalled Werkzeug-3.0.1\n",
            "  Attempting uninstall: urllib3\n",
            "    Found existing installation: urllib3 2.0.7\n",
            "    Uninstalling urllib3-2.0.7:\n",
            "      Successfully uninstalled urllib3-2.0.7\n",
            "  Attempting uninstall: typing-extensions\n",
            "    Found existing installation: typing_extensions 4.5.0\n",
            "    Uninstalling typing_extensions-4.5.0:\n",
            "      Successfully uninstalled typing_extensions-4.5.0\n",
            "  Attempting uninstall: tensorboard-data-server\n",
            "    Found existing installation: tensorboard-data-server 0.7.2\n",
            "    Uninstalling tensorboard-data-server-0.7.2:\n",
            "      Successfully uninstalled tensorboard-data-server-0.7.2\n",
            "  Attempting uninstall: rpds-py\n",
            "    Found existing installation: rpds-py 0.13.2\n",
            "    Uninstalling rpds-py-0.13.2:\n",
            "      Successfully uninstalled rpds-py-0.13.2\n",
            "  Attempting uninstall: regex\n",
            "    Found existing installation: regex 2023.6.3\n",
            "    Uninstalling regex-2023.6.3:\n",
            "      Successfully uninstalled regex-2023.6.3\n",
            "  Attempting uninstall: pyparsing\n",
            "    Found existing installation: pyparsing 3.1.1\n",
            "    Uninstalling pyparsing-3.1.1:\n",
            "      Successfully uninstalled pyparsing-3.1.1\n",
            "  Attempting uninstall: pyasn1\n",
            "    Found existing installation: pyasn1 0.5.1\n",
            "    Uninstalling pyasn1-0.5.1:\n",
            "      Successfully uninstalled pyasn1-0.5.1\n",
            "  Attempting uninstall: protobuf\n",
            "    Found existing installation: protobuf 3.20.3\n",
            "    Uninstalling protobuf-3.20.3:\n",
            "      Successfully uninstalled protobuf-3.20.3\n",
            "  Attempting uninstall: pillow\n",
            "    Found existing installation: Pillow 9.4.0\n",
            "    Uninstalling Pillow-9.4.0:\n",
            "      Successfully uninstalled Pillow-9.4.0\n",
            "  Attempting uninstall: numpy\n",
            "    Found existing installation: numpy 1.23.5\n",
            "    Uninstalling numpy-1.23.5:\n",
            "      Successfully uninstalled numpy-1.23.5\n",
            "  Attempting uninstall: networkx\n",
            "    Found existing installation: networkx 3.2.1\n",
            "    Uninstalling networkx-3.2.1:\n",
            "      Successfully uninstalled networkx-3.2.1\n",
            "  Attempting uninstall: markdown\n",
            "    Found existing installation: Markdown 3.5.1\n",
            "    Uninstalling Markdown-3.5.1:\n",
            "      Successfully uninstalled Markdown-3.5.1\n",
            "  Attempting uninstall: importlib-resources\n",
            "    Found existing installation: importlib-resources 6.1.1\n",
            "    Uninstalling importlib-resources-6.1.1:\n",
            "      Successfully uninstalled importlib-resources-6.1.1\n",
            "  Attempting uninstall: imageio-ffmpeg\n",
            "    Found existing installation: imageio-ffmpeg 0.4.9\n",
            "    Uninstalling imageio-ffmpeg-0.4.9:\n",
            "      Successfully uninstalled imageio-ffmpeg-0.4.9\n",
            "  Attempting uninstall: idna\n",
            "    Found existing installation: idna 3.6\n",
            "    Uninstalling idna-3.6:\n",
            "      Successfully uninstalled idna-3.6\n",
            "  Attempting uninstall: grpcio\n",
            "    Found existing installation: grpcio 1.59.3\n",
            "    Uninstalling grpcio-1.59.3:\n",
            "      Successfully uninstalled grpcio-1.59.3\n",
            "  Attempting uninstall: fonttools\n",
            "    Found existing installation: fonttools 4.45.1\n",
            "    Uninstalling fonttools-4.45.1:\n",
            "      Successfully uninstalled fonttools-4.45.1\n",
            "  Attempting uninstall: filelock\n",
            "    Found existing installation: filelock 3.13.1\n",
            "    Uninstalling filelock-3.13.1:\n",
            "      Successfully uninstalled filelock-3.13.1\n",
            "  Attempting uninstall: exceptiongroup\n",
            "    Found existing installation: exceptiongroup 1.2.0\n",
            "    Uninstalling exceptiongroup-1.2.0:\n",
            "      Successfully uninstalled exceptiongroup-1.2.0\n",
            "  Attempting uninstall: cycler\n",
            "    Found existing installation: cycler 0.12.1\n",
            "    Uninstalling cycler-0.12.1:\n",
            "      Successfully uninstalled cycler-0.12.1\n",
            "  Attempting uninstall: charset-normalizer\n",
            "    Found existing installation: charset-normalizer 3.3.2\n",
            "    Uninstalling charset-normalizer-3.3.2:\n",
            "      Successfully uninstalled charset-normalizer-3.3.2\n",
            "  Attempting uninstall: certifi\n",
            "    Found existing installation: certifi 2023.11.17\n",
            "    Uninstalling certifi-2023.11.17:\n",
            "      Successfully uninstalled certifi-2023.11.17\n",
            "  Attempting uninstall: cachetools\n",
            "    Found existing installation: cachetools 5.3.2\n",
            "    Uninstalling cachetools-5.3.2:\n",
            "      Successfully uninstalled cachetools-5.3.2\n",
            "  Attempting uninstall: yarl\n",
            "    Found existing installation: yarl 1.9.3\n",
            "    Uninstalling yarl-1.9.3:\n",
            "      Successfully uninstalled yarl-1.9.3\n",
            "  Attempting uninstall: referencing\n",
            "    Found existing installation: referencing 0.31.1\n",
            "    Uninstalling referencing-0.31.1:\n",
            "      Successfully uninstalled referencing-0.31.1\n",
            "  Attempting uninstall: pyarrow\n",
            "    Found existing installation: pyarrow 9.0.0\n",
            "    Uninstalling pyarrow-9.0.0:\n",
            "      Successfully uninstalled pyarrow-9.0.0\n",
            "  Attempting uninstall: pandas\n",
            "    Found existing installation: pandas 1.5.3\n",
            "    Uninstalling pandas-1.5.3:\n",
            "      Successfully uninstalled pandas-1.5.3\n",
            "  Attempting uninstall: imageio\n",
            "    Found existing installation: imageio 2.31.6\n",
            "    Uninstalling imageio-2.31.6:\n",
            "      Successfully uninstalled imageio-2.31.6\n",
            "  Attempting uninstall: contourpy\n",
            "    Found existing installation: contourpy 1.2.0\n",
            "    Uninstalling contourpy-1.2.0:\n",
            "      Successfully uninstalled contourpy-1.2.0\n",
            "  Attempting uninstall: pydantic\n",
            "    Found existing installation: pydantic 1.10.13\n",
            "    Uninstalling pydantic-1.10.13:\n",
            "      Successfully uninstalled pydantic-1.10.13\n",
            "  Attempting uninstall: matplotlib\n",
            "    Found existing installation: matplotlib 3.7.1\n",
            "    Uninstalling matplotlib-3.7.1:\n",
            "      Successfully uninstalled matplotlib-3.7.1\n",
            "  Attempting uninstall: jsonschema-specifications\n",
            "    Found existing installation: jsonschema-specifications 2023.11.2\n",
            "    Uninstalling jsonschema-specifications-2023.11.2:\n",
            "      Successfully uninstalled jsonschema-specifications-2023.11.2\n",
            "  Attempting uninstall: huggingface-hub\n",
            "    Found existing installation: huggingface-hub 0.19.4\n",
            "    Uninstalling huggingface-hub-0.19.4:\n",
            "      Successfully uninstalled huggingface-hub-0.19.4\n",
            "  Attempting uninstall: google-auth\n",
            "    Found existing installation: google-auth 2.17.3\n",
            "    Uninstalling google-auth-2.17.3:\n",
            "      Successfully uninstalled google-auth-2.17.3\n",
            "  Attempting uninstall: aiohttp\n",
            "    Found existing installation: aiohttp 3.9.1\n",
            "    Uninstalling aiohttp-3.9.1:\n",
            "      Successfully uninstalled aiohttp-3.9.1\n",
            "  Attempting uninstall: transformers\n",
            "    Found existing installation: transformers 4.35.2\n",
            "    Uninstalling transformers-4.35.2:\n",
            "      Successfully uninstalled transformers-4.35.2\n",
            "  Attempting uninstall: jsonschema\n",
            "    Found existing installation: jsonschema 4.19.2\n",
            "    Uninstalling jsonschema-4.19.2:\n",
            "      Successfully uninstalled jsonschema-4.19.2\n",
            "  Attempting uninstall: tensorboard\n",
            "    Found existing installation: tensorboard 2.14.1\n",
            "    Uninstalling tensorboard-2.14.1:\n",
            "      Successfully uninstalled tensorboard-2.14.1\n",
            "  Attempting uninstall: altair\n",
            "    Found existing installation: altair 4.2.2\n",
            "    Uninstalling altair-4.2.2:\n",
            "      Successfully uninstalled altair-4.2.2\n",
            "  Attempting uninstall: triton\n",
            "    Found existing installation: triton 2.1.0\n",
            "    Uninstalling triton-2.1.0:\n",
            "      Successfully uninstalled triton-2.1.0\n",
            "  Attempting uninstall: torch\n",
            "    Found existing installation: torch 2.1.0+cu118\n",
            "    Uninstalling torch-2.1.0+cu118:\n",
            "      Successfully uninstalled torch-2.1.0+cu118\n",
            "  Attempting uninstall: torchvision\n",
            "    Found existing installation: torchvision 0.16.0+cu118\n",
            "    Uninstalling torchvision-0.16.0+cu118:\n",
            "      Successfully uninstalled torchvision-0.16.0+cu118\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "lida 0.0.10 requires kaleido, which is not installed.\n",
            "llmx 0.0.15a0 requires cohere, which is not installed.\n",
            "llmx 0.0.15a0 requires openai, which is not installed.\n",
            "llmx 0.0.15a0 requires tiktoken, which is not installed.\n",
            "google-colab 1.0.0 requires google-auth==2.17.3, but you have google-auth 2.22.0 which is incompatible.\n",
            "google-colab 1.0.0 requires pandas==1.5.3, but you have pandas 2.0.3 which is incompatible.\n",
            "ibis-framework 6.2.0 requires pyarrow<13,>=2, but you have pyarrow 13.0.0 which is incompatible.\n",
            "pandas-gbq 0.17.9 requires pyarrow<10.0dev,>=3.0.0, but you have pyarrow 13.0.0 which is incompatible.\n",
            "tensorflow-metadata 1.14.0 requires protobuf<4.21,>=3.20.3, but you have protobuf 4.24.2 which is incompatible.\n",
            "tensorflow-probability 0.22.0 requires typing-extensions<4.6.0, but you have typing-extensions 4.8.0 which is incompatible.\n",
            "torchaudio 2.1.0+cu118 requires torch==2.1.0, but you have torch 2.0.1 which is incompatible.\n",
            "torchdata 0.7.0 requires torch==2.1.0, but you have torch 2.0.1 which is incompatible.\n",
            "torchtext 0.16.0 requires torch==2.1.0, but you have torch 2.0.1 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed accelerate-0.22.0 aiofiles-23.2.1 aiohttp-3.8.5 altair-5.0.1 annotated-types-0.5.0 antlr4-python3-runtime-4.9.3 av-11.0.0 cachetools-5.3.1 certifi-2023.7.22 charset-normalizer-3.2.0 cmake-3.27.2 contourpy-1.1.0 cycler-0.11.0 datasets-2.14.4 decord-0.6.0 diffusers-0.21.4 dill-0.3.7 einops-0.6.1 exceptiongroup-1.1.3 fastapi-0.103.0 ffmpeg-python-0.2.0 ffmpy-0.3.1 filelock-3.12.2 fonttools-4.42.1 google-auth-2.22.0 gradio-3.41.2 gradio-client-0.5.0 grpcio-1.57.0 h11-0.14.0 httpcore-0.17.3 httpx-0.24.1 huggingface-hub-0.16.4 idna-3.4 imageio-2.9.0 imageio-ffmpeg-0.4.3 importlib-resources-6.0.1 jsonschema-4.19.0 jsonschema-specifications-2023.7.1 lightning-utilities-0.9.0 lit-16.0.6 lpips-0.1.4 markdown-3.4.4 matplotlib-3.7.2 multiprocess-0.70.15 networkx-3.1 numpy-1.24.4 nvidia-cublas-cu11-11.10.3.66 nvidia-cuda-cupti-cu11-11.7.101 nvidia-cuda-nvrtc-cu11-11.7.99 nvidia-cuda-runtime-cu11-11.7.99 nvidia-cudnn-cu11-8.5.0.96 nvidia-cufft-cu11-10.9.0.58 nvidia-curand-cu11-10.2.10.91 nvidia-cusolver-cu11-11.4.0.1 nvidia-cusparse-cu11-11.7.4.91 nvidia-nccl-cu11-2.14.3 nvidia-nvtx-cu11-11.7.91 omegaconf-2.3.0 orjson-3.9.5 pandas-2.0.3 pillow-9.5.0 pkgutil-resolve-name-1.3.10 protobuf-4.24.2 pyarrow-13.0.0 pyasn1-0.5.0 pydantic-2.3.0 pydantic-core-2.6.3 pydub-0.25.1 pyparsing-3.0.9 python-multipart-0.0.6 pytorch-lightning-2.0.7 pytz-2023.3 referencing-0.30.2 regex-2023.8.8 rpds-py-0.9.2 safetensors-0.3.3 semantic-version-2.10.0 starlette-0.27.0 tensorboard-2.14.0 tensorboard-data-server-0.7.1 timm-0.9.12 tokenizers-0.13.3 torch-2.0.1 torchmetrics-1.1.0 torchvision-0.15.2 transformers-4.32.0 triton-2.0.0 typing-extensions-4.8.0 tzdata-2023.3 urllib3-1.26.16 uvicorn-0.23.2 websockets-11.0.3 werkzeug-2.3.7 xformers-0.0.22 xxhash-3.3.0 yarl-1.9.2 zipp-3.16.2\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "PIL",
                  "certifi",
                  "cycler",
                  "google",
                  "matplotlib",
                  "mpl_toolkits",
                  "numpy",
                  "pydevd_plugins"
                ]
              }
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd /content/magicanimate/"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9sKQGciu2KYJ",
        "outputId": "994e2083-83be-40d8-c7b8-fdfc37577b49"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/magicanimate\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python /content/magicanimate/app.py"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "odt_be6_zDOd",
        "outputId": "01918620-d1b9-4659-8396-cf957b678757"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2023-12-05 01:40:00.037993: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
            "2023-12-05 01:40:00.038056: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
            "2023-12-05 01:40:00.038084: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
            "2023-12-05 01:40:01.367269: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
            "/content/magicanimate/magicanimate/pipelines/pipeline_animation.py:43: FutureWarning: Importing `DiffusionPipeline` or `ImagePipelineOutput` from diffusers.pipeline_utils is deprecated. Please import from diffusers.pipelines.pipeline_utils instead.\n",
            "  from diffusers.pipeline_utils import DiffusionPipeline\n",
            "Fetching 36 files: 100% 36/36 [00:02<00:00, 13.74it/s]\n",
            "Fetching 5 files: 100% 5/5 [00:00<00:00, 18.16it/s]\n",
            "Fetching 7 files: 100% 7/7 [00:00<00:00, 16.52it/s]\n",
            "Initializing MagicAnimate Pipeline...\n",
            "loaded temporal unet's pretrained weights from stable-diffusion-v1-5/unet ...\n",
            "### missing keys: 560; \n",
            "### unexpected keys: 0;\n",
            "### Temporal Module Parameters: 417.1376 M\n",
            "The config attributes {'addition_embed_type': None, 'addition_embed_type_num_heads': 64, 'addition_time_embed_dim': None, 'conditioning_channels': 3, 'encoder_hid_dim': None, 'encoder_hid_dim_type': None, 'global_pool_conditions': False, 'num_attention_heads': None, 'transformer_layers_per_block': 1} were passed to ControlNetModel, but are not expected and will be ignored. Please verify your config.json configuration file.\n",
            "It is recommended to provide `attention_head_dim` when calling `get_down_block`. Defaulting `attention_head_dim` to 8.\n",
            "It is recommended to provide `attention_head_dim` when calling `get_down_block`. Defaulting `attention_head_dim` to 8.\n",
            "It is recommended to provide `attention_head_dim` when calling `get_down_block`. Defaulting `attention_head_dim` to 8.\n",
            "It is recommended to provide `attention_head_dim` when calling `get_down_block`. Defaulting `attention_head_dim` to 8.\n",
            "/content/magicanimate/magicanimate/pipelines/pipeline_animation.py:103: FutureWarning: The configuration file of this scheduler: DDIMScheduler {\n",
            "  \"_class_name\": \"DDIMScheduler\",\n",
            "  \"_diffusers_version\": \"0.21.4\",\n",
            "  \"beta_end\": 0.012,\n",
            "  \"beta_schedule\": \"linear\",\n",
            "  \"beta_start\": 0.00085,\n",
            "  \"clip_sample\": true,\n",
            "  \"clip_sample_range\": 1.0,\n",
            "  \"dynamic_thresholding_ratio\": 0.995,\n",
            "  \"num_train_timesteps\": 1000,\n",
            "  \"prediction_type\": \"epsilon\",\n",
            "  \"rescale_betas_zero_snr\": false,\n",
            "  \"sample_max_value\": 1.0,\n",
            "  \"set_alpha_to_one\": true,\n",
            "  \"steps_offset\": 0,\n",
            "  \"thresholding\": false,\n",
            "  \"timestep_spacing\": \"leading\",\n",
            "  \"trained_betas\": null\n",
            "}\n",
            " is outdated. `steps_offset` should be set to 1 instead of 0. Please make sure to update the config accordingly as leaving `steps_offset` might led to incorrect results in future versions. If you have downloaded this checkpoint from the Hugging Face Hub, it would be very nice if you could open a Pull request for the `scheduler/scheduler_config.json` file\n",
            "  deprecate(\"steps_offset!=1\", \"1.0.0\", deprecation_message, standard_warn=False)\n",
            "/content/magicanimate/magicanimate/pipelines/pipeline_animation.py:116: FutureWarning: The configuration file of this scheduler: DDIMScheduler {\n",
            "  \"_class_name\": \"DDIMScheduler\",\n",
            "  \"_diffusers_version\": \"0.21.4\",\n",
            "  \"beta_end\": 0.012,\n",
            "  \"beta_schedule\": \"linear\",\n",
            "  \"beta_start\": 0.00085,\n",
            "  \"clip_sample\": true,\n",
            "  \"clip_sample_range\": 1.0,\n",
            "  \"dynamic_thresholding_ratio\": 0.995,\n",
            "  \"num_train_timesteps\": 1000,\n",
            "  \"prediction_type\": \"epsilon\",\n",
            "  \"rescale_betas_zero_snr\": false,\n",
            "  \"sample_max_value\": 1.0,\n",
            "  \"set_alpha_to_one\": true,\n",
            "  \"steps_offset\": 1,\n",
            "  \"thresholding\": false,\n",
            "  \"timestep_spacing\": \"leading\",\n",
            "  \"trained_betas\": null\n",
            "}\n",
            " has not set the configuration `clip_sample`. `clip_sample` should be set to False in the configuration file. Please make sure to update the config accordingly as not setting `clip_sample` in the config might lead to incorrect results in future versions. If you have downloaded this checkpoint from the Hugging Face Hub, it would be very nice if you could open a Pull request for the `scheduler/scheduler_config.json` file\n",
            "  deprecate(\"clip_sample not set\", \"1.0.0\", deprecation_message, standard_warn=False)\n",
            "Initialization Done!\n",
            "Running on local URL:  http://127.0.0.1:7860\n",
            "Running on public URL: https://7990df47f76a42793f.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n",
            "/content/magicanimate/magicanimate/pipelines/pipeline_animation.py:624: FutureWarning: Accessing config attribute `in_channels` directly via 'UNet3DConditionModel' object attribute is deprecated. Please access 'in_channels' over 'UNet3DConditionModel's config object instead, e.g. 'unet.config.in_channels'.\n",
            "  num_channels_latents = self.unet.in_channels\n",
            "100% 54/54 [01:48<00:00,  2.01s/it]\n",
            "100% 48/48 [00:01<00:00, 28.02it/s]\n",
            "IMAGEIO FFMPEG_WRITER WARNING: input image is not divisible by macro_block_size=16, resizing from (1544, 516) to (1552, 528) to ensure video compatibility with most codecs and players. To prevent resizing, make your input image divisible by the macro_block_size or set the macro_block_size to 1 (risking incompatibility).\n",
            "\u001b[1;34m[swscaler @ 0x57f1cc0] \u001b[0m\u001b[0;33mWarning: data is not aligned! This can lead to a speed loss\n",
            " 35% 19/54 [01:33<02:51,  4.91s/it]"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%writefile /content/magicanimate/app.py\n",
        "import argparse\n",
        "import imageio\n",
        "import numpy as np\n",
        "import gradio as gr\n",
        "from PIL import Image\n",
        "import os\n",
        "from pathlib import Path\n",
        "\n",
        "from demo.animate import MagicAnimate\n",
        "from huggingface_hub import snapshot_download\n",
        "\n",
        "snapshot_download(repo_id=\"runwayml/stable-diffusion-v1-5\", local_dir=\"./stable-diffusion-v1-5\")\n",
        "snapshot_download(repo_id=\"stabilityai/sd-vae-ft-mse\", local_dir=\"./sd-vae-ft-mse\")\n",
        "snapshot_download(repo_id=\"zcxu-eric/MagicAnimate\", local_dir=\"./MagicAnimate\")\n",
        "\n",
        "animator = MagicAnimate()\n",
        "\n",
        "def animate(reference_image, motion_sequence_state, seed, steps, guidance_scale):\n",
        "    return animator(reference_image, motion_sequence_state, seed, steps, guidance_scale)\n",
        "\n",
        "def read_video(video, size=512):\n",
        "    reader = imageio.get_reader(video)\n",
        "    fps = reader.get_meta_data()['fps']\n",
        "    assert fps == 25.0, f'Expected video fps: 25, but {fps} fps found'\n",
        "    return video\n",
        "\n",
        "def read_image(image, size=512):\n",
        "    return np.array(Image.fromarray(image).resize((size, size)))\n",
        "\n",
        "def animate_batch(image_batch_path, motion_sequence_batch_path, seed, steps, guidance_scale):\n",
        "    image_files = os.listdir(image_batch_path)\n",
        "    motion_sequence_files = os.listdir(motion_sequence_batch_path)\n",
        "\n",
        "    results = []\n",
        "    for image_file in image_files:\n",
        "        if image_file.endswith('.png') or image_file.endswith('.jpg'):\n",
        "            image_path = Path(image_batch_path) / image_file\n",
        "            reference_image = read_image(imageio.imread(str(image_path)))\n",
        "\n",
        "            for motion_sequence_file in motion_sequence_files:\n",
        "                if motion_sequence_file.endswith('.mp4'):\n",
        "                    motion_sequence_path = Path(motion_sequence_batch_path) / motion_sequence_file\n",
        "                    motion_sequence = read_video(str(motion_sequence_path))\n",
        "                    result = animate(reference_image, motion_sequence, seed, steps, guidance_scale)\n",
        "                    results.append(result)\n",
        "\n",
        "    return results\n",
        "\n",
        "with gr.Blocks() as demo:\n",
        "    gr.HTML(\"\"\"\n",
        "        <div style=\"text-align: center; max-width: 1200px; margin: 20px auto;\">\n",
        "        <h1 style=\"font-weight: 800; font-size: 2rem; margin: 0rem\">\n",
        "            MagicAnimate: Temporally Consistent Human Image Animation\n",
        "        </h1>\n",
        "        <br>\n",
        "        <h2 style=\"font-weight: 450; font-size: 1rem; margin: 0rem\">\n",
        "            <a href=\"https://showlab.github.io/magicanimate\">Project page</a> |\n",
        "            <a href=\"https://github.com/magic-research/magic-animate\"> GitHub </a> |\n",
        "            <a href=\"https://arxiv.org/abs/2311.16498\"> arXiv </a>\n",
        "        </h2>\n",
        "        </div>\n",
        "    \"\"\")\n",
        "    animation = gr.Video(format=\"mp4\", label=\"Animation Results\", autoplay=True)\n",
        "\n",
        "    with gr.Row():\n",
        "        reference_image  = gr.Image(label=\"Reference Image\")\n",
        "        motion_sequence  = gr.Video(format=\"mp4\", label=\"Motion Sequence\")\n",
        "\n",
        "        with gr.Column():\n",
        "            random_seed         = gr.Textbox(label=\"Random seed\", value=\"1\", info=\"default: -1\")\n",
        "            sampling_steps      = gr.Textbox(label=\"Sampling steps\", value=\"25\", info=\"default: 25\")\n",
        "            guidance_scale      = gr.Textbox(label=\"Guidance scale\", value=\"7.5\", info=\"default: 7.5\")\n",
        "            submit              = gr.Button(\"Animate\")\n",
        "            image_batch_path    = gr.Textbox(label=\"Image Batch Path\", placeholder=\"Enter the path to your image batch files\")\n",
        "            motion_sequence_batch_path = gr.Textbox(label=\"Motion Sequence Batch Path\", placeholder=\"Enter the path to your motion sequence batch files\")\n",
        "            batch_submit        = gr.Button(\"Animate Batch\")\n",
        "\n",
        "    motion_sequence.upload(\n",
        "        read_video,\n",
        "        motion_sequence,\n",
        "        motion_sequence\n",
        "    )\n",
        "\n",
        "    reference_image.upload(\n",
        "        read_image,\n",
        "        reference_image,\n",
        "        reference_image\n",
        "    )\n",
        "\n",
        "    submit.click(\n",
        "        animate,\n",
        "        [reference_image, motion_sequence, random_seed, sampling_steps, guidance_scale],\n",
        "        animation\n",
        "    )\n",
        "\n",
        "    batch_submit.click(\n",
        "        animate_batch,\n",
        "        [image_batch_path, motion_sequence_batch_path, random_seed, sampling_steps, guidance_scale],\n",
        "        animation\n",
        "    )\n",
        "\n",
        "    gr.Markdown(\"## Examples\")\n",
        "    gr.Examples(\n",
        "        examples=[\n",
        "            [\"inputs/applications/source_image/monalisa.png\", \"inputs/applications/driving/densepose/running.mp4\"],\n",
        "            [\"inputs/applications/source_image/demo4.png\", \"inputs/applications/driving/densepose/demo4.mp4\"],\n",
        "            [\"inputs/applications/source_image/0002.png\", \"inputs/applications/driving/densepose/demo4.mp4\"],\n",
        "            [\"inputs/applications/source_image/dalle2.jpeg\", \"inputs/applications/driving/densepose/running2.mp4\"],\n",
        "            [\"inputs/applications/source_image/dalle8.jpeg\", \"inputs/applications/driving/densepose/dancing2.mp4\"],\n",
        "            [\"inputs/applications/source_image/multi1_source.png\", \"inputs/applications/driving/densepose/multi_dancing.mp4\"]\n",
        "        ],\n",
        "        inputs=[reference_image, motion_sequence],\n",
        "        outputs=animation\n",
        "    )\n",
        "\n",
        "demo.launch(share=True)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nd4lPhfLbn9U",
        "outputId": "00096f2e-b438-4ef9-b61a-476fecc5569a"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Overwriting /content/magicanimate/app.py\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%writefile /content/magicanimate/demo/animate.py\n",
        "import argparse\n",
        "import argparse\n",
        "import datetime\n",
        "import inspect\n",
        "import os\n",
        "import numpy as np\n",
        "from PIL import Image\n",
        "from omegaconf import OmegaConf\n",
        "from collections import OrderedDict\n",
        "\n",
        "import torch\n",
        "\n",
        "from diffusers import AutoencoderKL, DDIMScheduler, UniPCMultistepScheduler\n",
        "\n",
        "from tqdm import tqdm\n",
        "from transformers import CLIPTextModel, CLIPTokenizer\n",
        "\n",
        "from magicanimate.models.unet_controlnet import UNet3DConditionModel\n",
        "from magicanimate.models.controlnet import ControlNetModel\n",
        "from magicanimate.models.appearance_encoder import AppearanceEncoderModel\n",
        "from magicanimate.models.mutual_self_attention import ReferenceAttentionControl\n",
        "from magicanimate.pipelines.pipeline_animation import AnimationPipeline\n",
        "from magicanimate.utils.util import save_videos_grid\n",
        "from accelerate.utils import set_seed\n",
        "\n",
        "from magicanimate.utils.videoreader import VideoReader\n",
        "\n",
        "from einops import rearrange, repeat\n",
        "\n",
        "import csv, pdb, glob\n",
        "from safetensors import safe_open\n",
        "import math\n",
        "from pathlib import Path\n",
        "\n",
        "class MagicAnimate():\n",
        "    def __init__(self, config=\"configs/prompts/animation.yaml\") -> None:\n",
        "        print(\"Initializing MagicAnimate Pipeline...\")\n",
        "        *_, func_args = inspect.getargvalues(inspect.currentframe())\n",
        "        func_args = dict(func_args)\n",
        "\n",
        "        config  = OmegaConf.load(config)\n",
        "\n",
        "        inference_config = OmegaConf.load(config.inference_config)\n",
        "\n",
        "        motion_module = config.motion_module\n",
        "\n",
        "        ### >>> create animation pipeline >>> ###\n",
        "        tokenizer = CLIPTokenizer.from_pretrained(config.pretrained_model_path, subfolder=\"tokenizer\")\n",
        "        text_encoder = CLIPTextModel.from_pretrained(config.pretrained_model_path, subfolder=\"text_encoder\")\n",
        "        if config.pretrained_unet_path:\n",
        "            unet = UNet3DConditionModel.from_pretrained_2d(config.pretrained_unet_path, unet_additional_kwargs=OmegaConf.to_container(inference_config.unet_additional_kwargs))\n",
        "        else:\n",
        "            unet = UNet3DConditionModel.from_pretrained_2d(config.pretrained_model_path, subfolder=\"unet\", unet_additional_kwargs=OmegaConf.to_container(inference_config.unet_additional_kwargs))\n",
        "        self.appearance_encoder = AppearanceEncoderModel.from_pretrained(config.pretrained_appearance_encoder_path, subfolder=\"appearance_encoder\").cuda()\n",
        "        self.reference_control_writer = ReferenceAttentionControl(self.appearance_encoder, do_classifier_free_guidance=True, mode='write', fusion_blocks=config.fusion_blocks)\n",
        "        self.reference_control_reader = ReferenceAttentionControl(unet, do_classifier_free_guidance=True, mode='read', fusion_blocks=config.fusion_blocks)\n",
        "        if config.pretrained_vae_path is not None:\n",
        "            vae = AutoencoderKL.from_pretrained(config.pretrained_vae_path)\n",
        "        else:\n",
        "            vae = AutoencoderKL.from_pretrained(config.pretrained_model_path, subfolder=\"vae\")\n",
        "\n",
        "        ### Load controlnet\n",
        "        controlnet   = ControlNetModel.from_pretrained(config.pretrained_controlnet_path)\n",
        "\n",
        "        vae.to(torch.float16)\n",
        "        unet.to(torch.float16)\n",
        "        text_encoder.to(torch.float16)\n",
        "        controlnet.to(torch.float16)\n",
        "        self.appearance_encoder.to(torch.float16)\n",
        "\n",
        "        unet.enable_xformers_memory_efficient_attention()\n",
        "        self.appearance_encoder.enable_xformers_memory_efficient_attention()\n",
        "        controlnet.enable_xformers_memory_efficient_attention()\n",
        "\n",
        "        self.pipeline = AnimationPipeline(\n",
        "            vae=vae, text_encoder=text_encoder, tokenizer=tokenizer, unet=unet, controlnet=controlnet,\n",
        "            scheduler=DDIMScheduler(**OmegaConf.to_container(inference_config.noise_scheduler_kwargs)),\n",
        "            # NOTE: UniPCMultistepScheduler\n",
        "        ).to(\"cuda\")\n",
        "\n",
        "        # 1. unet ckpt\n",
        "        # 1.1 motion module\n",
        "        motion_module_state_dict = torch.load(motion_module, map_location=\"cpu\")\n",
        "        if \"global_step\" in motion_module_state_dict: func_args.update({\"global_step\": motion_module_state_dict[\"global_step\"]})\n",
        "        motion_module_state_dict = motion_module_state_dict['state_dict'] if 'state_dict' in motion_module_state_dict else motion_module_state_dict\n",
        "        try:\n",
        "            # extra steps for self-trained models\n",
        "            state_dict = OrderedDict()\n",
        "            for key in motion_module_state_dict.keys():\n",
        "                if key.startswith(\"module.\"):\n",
        "                    _key = key.split(\"module.\")[-1]\n",
        "                    state_dict[_key] = motion_module_state_dict[key]\n",
        "                else:\n",
        "                    state_dict[key] = motion_module_state_dict[key]\n",
        "            motion_module_state_dict = state_dict\n",
        "            del state_dict\n",
        "            missing, unexpected = self.pipeline.unet.load_state_dict(motion_module_state_dict, strict=False)\n",
        "            assert len(unexpected) == 0\n",
        "        except:\n",
        "            _tmp_ = OrderedDict()\n",
        "            for key in motion_module_state_dict.keys():\n",
        "                if \"motion_modules\" in key:\n",
        "                    if key.startswith(\"unet.\"):\n",
        "                        _key = key.split('unet.')[-1]\n",
        "                        _tmp_[_key] = motion_module_state_dict[key]\n",
        "                    else:\n",
        "                        _tmp_[key] = motion_module_state_dict[key]\n",
        "            missing, unexpected = unet.load_state_dict(_tmp_, strict=False)\n",
        "            assert len(unexpected) == 0\n",
        "            del _tmp_\n",
        "        del motion_module_state_dict\n",
        "\n",
        "        self.pipeline.to(\"cuda\")\n",
        "        self.L = config.L\n",
        "\n",
        "        print(\"Initialization Done!\")\n",
        "\n",
        "    def __call__(self, source_image, motion_sequence, random_seed, step, guidance_scale, size=512):\n",
        "            prompt = n_prompt = \"\"\n",
        "            random_seed = int(random_seed)\n",
        "            step = int(step)\n",
        "            guidance_scale = float(guidance_scale)\n",
        "            samples_per_video = []\n",
        "            # manually set random seed for reproduction\n",
        "            if random_seed != -1:\n",
        "                torch.manual_seed(random_seed)\n",
        "                set_seed(random_seed)\n",
        "            else:\n",
        "                torch.seed()\n",
        "\n",
        "            if motion_sequence.endswith('.mp4'):\n",
        "                control = VideoReader(motion_sequence).read()\n",
        "                if control[0].shape[0] != size:\n",
        "                    control = [np.array(Image.fromarray(c).resize((size, size))) for c in control]\n",
        "                control = np.array(control)\n",
        "\n",
        "            if source_image.shape[0] != size:\n",
        "                source_image = np.array(Image.fromarray(source_image).resize((size, size)))\n",
        "            H, W, C = source_image.shape\n",
        "\n",
        "            init_latents = None\n",
        "            original_length = control.shape[0]\n",
        "            if control.shape[0] % self.L > 0:\n",
        "                control = np.pad(control, ((0, self.L-control.shape[0] % self.L), (0, 0), (0, 0), (0, 0)), mode='edge')\n",
        "            generator = torch.Generator(device=torch.device(\"cuda:0\"))\n",
        "            generator.manual_seed(torch.initial_seed())\n",
        "            sample = self.pipeline(\n",
        "                prompt,\n",
        "                negative_prompt         = n_prompt,\n",
        "                num_inference_steps     = step,\n",
        "                guidance_scale          = guidance_scale,\n",
        "                width                   = W,\n",
        "                height                  = H,\n",
        "                video_length            = len(control),\n",
        "                controlnet_condition    = control,\n",
        "                init_latents            = init_latents,\n",
        "                generator               = generator,\n",
        "                appearance_encoder       = self.appearance_encoder,\n",
        "                reference_control_writer = self.reference_control_writer,\n",
        "                reference_control_reader = self.reference_control_reader,\n",
        "                source_image             = source_image,\n",
        "            ).videos\n",
        "\n",
        "            source_images = np.array([source_image] * original_length)\n",
        "            source_images = rearrange(torch.from_numpy(source_images), \"t h w c -> 1 c t h w\") / 255.0\n",
        "            samples_per_video.append(source_images)\n",
        "\n",
        "            control = control / 255.0\n",
        "            control = rearrange(control, \"t h w c -> 1 c t h w\")\n",
        "            control = torch.from_numpy(control)\n",
        "            samples_per_video.append(control[:, :, :original_length])\n",
        "\n",
        "            samples_per_video.append(sample[:, :, :original_length])\n",
        "\n",
        "            samples_per_video = torch.cat(samples_per_video)\n",
        "\n",
        "            time_str = datetime.datetime.now().strftime(\"%Y-%m-%dT%H-%M-%S\")\n",
        "            savedir = \"/content/drive/MyDrive/#magicout\"  # Updated save directory\n",
        "            animation_path = f\"{savedir}/{time_str}.mp4\"\n",
        "\n",
        "            os.makedirs(savedir, exist_ok=True)\n",
        "            save_videos_grid(samples_per_video, animation_path)\n",
        "\n",
        "            return animation_path\n",
        ""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fP-LtjJnhix2",
        "outputId": "f752a96d-6228-48fc-da95-6e081dba1b2a"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Overwriting /content/magicanimate/demo/animate.py\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Restart Runtime to conver a Vid with OpenPose"
      ],
      "metadata": {
        "id": "UDQNQ6fcmYDx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "from os.path import exists, join, basename, splitext\n",
        "\n",
        "#@markdown ### ▶️ Setup\n",
        "#@markdown Run this first.\n",
        "if not os.path.exists('/content/drive'):\n",
        "  from google.colab import drive\n",
        "  print(\"📂 Connecting to Google Drive...\")\n",
        "  drive.mount('/content/drive')\n",
        "\n",
        "!pip install controlnet_aux\n",
        "!pip install diffusers transformers accelerate\n",
        "!pip install ffmpeg-python\n",
        "\n",
        "\n",
        "gDir = \"/content/drive/MyDrive/openpose\"\n",
        "\n",
        "if not os.path.exists('/content/drive/MyDrive/openpose'):\n",
        "  !mkdir '/content/drive/MyDrive/openpose'\n",
        "\n"
      ],
      "metadata": {
        "id": "HezVrfdlgneW",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "06ecc668-57cc-491a-9860-26fbd340ed4b"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "📂 Connecting to Google Drive...\n",
            "Mounted at /content/drive\n",
            "Collecting controlnet_aux\n",
            "  Downloading controlnet_aux-0.0.7.tar.gz (202 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m202.4/202.4 kB\u001b[0m \u001b[31m4.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (from controlnet_aux) (2.0.1)\n",
            "Requirement already satisfied: importlib_metadata in /usr/local/lib/python3.10/dist-packages (from controlnet_aux) (6.8.0)\n",
            "Requirement already satisfied: huggingface_hub in /usr/local/lib/python3.10/dist-packages (from controlnet_aux) (0.16.4)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.10/dist-packages (from controlnet_aux) (1.11.4)\n",
            "Requirement already satisfied: opencv-python in /usr/local/lib/python3.10/dist-packages (from controlnet_aux) (4.8.0.76)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from controlnet_aux) (3.12.2)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from controlnet_aux) (1.24.4)\n",
            "Requirement already satisfied: Pillow in /usr/local/lib/python3.10/dist-packages (from controlnet_aux) (9.5.0)\n",
            "Requirement already satisfied: einops in /usr/local/lib/python3.10/dist-packages (from controlnet_aux) (0.6.1)\n",
            "Requirement already satisfied: torchvision in /usr/local/lib/python3.10/dist-packages (from controlnet_aux) (0.15.2)\n",
            "Requirement already satisfied: timm in /usr/local/lib/python3.10/dist-packages (from controlnet_aux) (0.9.12)\n",
            "Requirement already satisfied: scikit-image in /usr/local/lib/python3.10/dist-packages (from controlnet_aux) (0.19.3)\n",
            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from huggingface_hub->controlnet_aux) (2023.6.0)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from huggingface_hub->controlnet_aux) (2.31.0)\n",
            "Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub->controlnet_aux) (4.66.1)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub->controlnet_aux) (6.0.1)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub->controlnet_aux) (4.8.0)\n",
            "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub->controlnet_aux) (23.2)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.10/dist-packages (from importlib_metadata->controlnet_aux) (3.16.2)\n",
            "Requirement already satisfied: networkx>=2.2 in /usr/local/lib/python3.10/dist-packages (from scikit-image->controlnet_aux) (3.1)\n",
            "Requirement already satisfied: imageio>=2.4.1 in /usr/local/lib/python3.10/dist-packages (from scikit-image->controlnet_aux) (2.9.0)\n",
            "Requirement already satisfied: tifffile>=2019.7.26 in /usr/local/lib/python3.10/dist-packages (from scikit-image->controlnet_aux) (2023.9.26)\n",
            "Requirement already satisfied: PyWavelets>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from scikit-image->controlnet_aux) (1.5.0)\n",
            "Requirement already satisfied: safetensors in /usr/local/lib/python3.10/dist-packages (from timm->controlnet_aux) (0.3.3)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch->controlnet_aux) (1.12)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch->controlnet_aux) (3.1.2)\n",
            "Requirement already satisfied: nvidia-cuda-nvrtc-cu11==11.7.99 in /usr/local/lib/python3.10/dist-packages (from torch->controlnet_aux) (11.7.99)\n",
            "Requirement already satisfied: nvidia-cuda-runtime-cu11==11.7.99 in /usr/local/lib/python3.10/dist-packages (from torch->controlnet_aux) (11.7.99)\n",
            "Requirement already satisfied: nvidia-cuda-cupti-cu11==11.7.101 in /usr/local/lib/python3.10/dist-packages (from torch->controlnet_aux) (11.7.101)\n",
            "Requirement already satisfied: nvidia-cudnn-cu11==8.5.0.96 in /usr/local/lib/python3.10/dist-packages (from torch->controlnet_aux) (8.5.0.96)\n",
            "Requirement already satisfied: nvidia-cublas-cu11==11.10.3.66 in /usr/local/lib/python3.10/dist-packages (from torch->controlnet_aux) (11.10.3.66)\n",
            "Requirement already satisfied: nvidia-cufft-cu11==10.9.0.58 in /usr/local/lib/python3.10/dist-packages (from torch->controlnet_aux) (10.9.0.58)\n",
            "Requirement already satisfied: nvidia-curand-cu11==10.2.10.91 in /usr/local/lib/python3.10/dist-packages (from torch->controlnet_aux) (10.2.10.91)\n",
            "Requirement already satisfied: nvidia-cusolver-cu11==11.4.0.1 in /usr/local/lib/python3.10/dist-packages (from torch->controlnet_aux) (11.4.0.1)\n",
            "Requirement already satisfied: nvidia-cusparse-cu11==11.7.4.91 in /usr/local/lib/python3.10/dist-packages (from torch->controlnet_aux) (11.7.4.91)\n",
            "Requirement already satisfied: nvidia-nccl-cu11==2.14.3 in /usr/local/lib/python3.10/dist-packages (from torch->controlnet_aux) (2.14.3)\n",
            "Requirement already satisfied: nvidia-nvtx-cu11==11.7.91 in /usr/local/lib/python3.10/dist-packages (from torch->controlnet_aux) (11.7.91)\n",
            "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch->controlnet_aux) (2.0.0)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch->controlnet_aux) (67.7.2)\n",
            "Requirement already satisfied: wheel in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch->controlnet_aux) (0.42.0)\n",
            "Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch->controlnet_aux) (3.27.2)\n",
            "Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch->controlnet_aux) (16.0.6)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch->controlnet_aux) (2.1.3)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub->controlnet_aux) (3.2.0)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub->controlnet_aux) (3.4)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub->controlnet_aux) (1.26.16)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub->controlnet_aux) (2023.7.22)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch->controlnet_aux) (1.3.0)\n",
            "Building wheels for collected packages: controlnet_aux\n",
            "  Building wheel for controlnet_aux (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for controlnet_aux: filename=controlnet_aux-0.0.7-py3-none-any.whl size=274340 sha256=800877f982f755edebeffb9e94728e9619e05123116c2265c220951ee75c1e33\n",
            "  Stored in directory: /root/.cache/pip/wheels/1e/3e/93/6678b4c0bc2ec31d53409b25d4189cbb08bae843e8b2b78e52\n",
            "Successfully built controlnet_aux\n",
            "Installing collected packages: controlnet_aux\n",
            "Successfully installed controlnet_aux-0.0.7\n",
            "Requirement already satisfied: diffusers in /usr/local/lib/python3.10/dist-packages (0.21.4)\n",
            "Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.32.0)\n",
            "Requirement already satisfied: accelerate in /usr/local/lib/python3.10/dist-packages (0.22.0)\n",
            "Requirement already satisfied: Pillow in /usr/local/lib/python3.10/dist-packages (from diffusers) (9.5.0)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from diffusers) (3.12.2)\n",
            "Requirement already satisfied: huggingface-hub>=0.13.2 in /usr/local/lib/python3.10/dist-packages (from diffusers) (0.16.4)\n",
            "Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.10/dist-packages (from diffusers) (6.8.0)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from diffusers) (1.24.4)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from diffusers) (2023.8.8)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from diffusers) (2.31.0)\n",
            "Requirement already satisfied: safetensors>=0.3.1 in /usr/local/lib/python3.10/dist-packages (from diffusers) (0.3.3)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (23.2)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (6.0.1)\n",
            "Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.13.3)\n",
            "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers) (4.66.1)\n",
            "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from accelerate) (5.9.5)\n",
            "Requirement already satisfied: torch>=1.10.0 in /usr/local/lib/python3.10/dist-packages (from accelerate) (2.0.1)\n",
            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.13.2->diffusers) (2023.6.0)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.13.2->diffusers) (4.8.0)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (1.12)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (3.1)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (3.1.2)\n",
            "Requirement already satisfied: nvidia-cuda-nvrtc-cu11==11.7.99 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (11.7.99)\n",
            "Requirement already satisfied: nvidia-cuda-runtime-cu11==11.7.99 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (11.7.99)\n",
            "Requirement already satisfied: nvidia-cuda-cupti-cu11==11.7.101 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (11.7.101)\n",
            "Requirement already satisfied: nvidia-cudnn-cu11==8.5.0.96 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (8.5.0.96)\n",
            "Requirement already satisfied: nvidia-cublas-cu11==11.10.3.66 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (11.10.3.66)\n",
            "Requirement already satisfied: nvidia-cufft-cu11==10.9.0.58 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (10.9.0.58)\n",
            "Requirement already satisfied: nvidia-curand-cu11==10.2.10.91 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (10.2.10.91)\n",
            "Requirement already satisfied: nvidia-cusolver-cu11==11.4.0.1 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (11.4.0.1)\n",
            "Requirement already satisfied: nvidia-cusparse-cu11==11.7.4.91 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (11.7.4.91)\n",
            "Requirement already satisfied: nvidia-nccl-cu11==2.14.3 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (2.14.3)\n",
            "Requirement already satisfied: nvidia-nvtx-cu11==11.7.91 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (11.7.91)\n",
            "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (2.0.0)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.10.0->accelerate) (67.7.2)\n",
            "Requirement already satisfied: wheel in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.10.0->accelerate) (0.42.0)\n",
            "Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=1.10.0->accelerate) (3.27.2)\n",
            "Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=1.10.0->accelerate) (16.0.6)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.10/dist-packages (from importlib-metadata->diffusers) (3.16.2)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->diffusers) (3.2.0)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->diffusers) (3.4)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->diffusers) (1.26.16)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->diffusers) (2023.7.22)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.10.0->accelerate) (2.1.3)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.10.0->accelerate) (1.3.0)\n",
            "Requirement already satisfied: ffmpeg-python in /usr/local/lib/python3.10/dist-packages (0.2.0)\n",
            "Requirement already satisfied: future in /usr/local/lib/python3.10/dist-packages (from ffmpeg-python) (0.18.3)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import ffmpeg\n",
        "import os\n",
        "from os.path import exists, join, basename, splitext\n",
        "from os import listdir\n",
        "from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler\n",
        "from controlnet_aux import OpenposeDetector\n",
        "from PIL import Image\n",
        "from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler\n",
        "import torch\n",
        "from diffusers.utils import load_image\n",
        "from tqdm import tqdm\n",
        "\n",
        "!rm -fr /content/frames\n",
        "\n",
        "#@markdown ### ▶️ Process Video\n",
        "#@markdown Video to process\n",
        "video_file = \"/content/Bubble Butt (3).mp4\" #@param {type:\"string\"}\n",
        "\n",
        "#@markdown Where to save your output under My Drive/openpose. Spaces aren't allowed.\n",
        "project_name = \"dancing\" #@param {type:\"string\"}\n",
        "gDir = \"/content/drive/MyDrive/openpose\"\n",
        "\n",
        "outputDir = os.path.join(gDir, project_name)\n",
        "\n",
        "if not os.path.exists(outputDir):\n",
        "  !mkdir {outputDir}\n",
        "\n",
        "folder_dir = '/content/frames'\n",
        "\n",
        "if not os.path.exists(folder_dir):\n",
        "  !mkdir {folder_dir}\n",
        "print(\"Extracting frames\")\n",
        "images_dir = os.path.join(folder_dir, 'frames-%d.jpg' )\n",
        "#chop up video with ffmpeg\n",
        "out, err = (\n",
        "    ffmpeg\n",
        "    .input(video_file, ss = 0, r = 1)\n",
        "    # .filter('fps', fps='25')\n",
        "    .output('/content/frames/test-%04d.jpg', start_number=0)\n",
        "    .overwrite_output()\n",
        "    .run()\n",
        ")\n",
        "\n",
        "if err:\n",
        "  print({err})\n",
        "\n",
        "# import the modules\n",
        "openpose = OpenposeDetector.from_pretrained('lllyasviel/ControlNet')\n",
        "\n",
        "ix=0\n",
        "image_files = os.listdir('/content/frames')\n",
        "print(\"Processing frames\")\n",
        "# get the path/directory\n",
        "for images in tqdm(sorted(image_files)):\n",
        "    # check if the image ends with png or jpg or jpeg\n",
        "    if (images.endswith(\".png\") or images.endswith(\".jpg\")\\\n",
        "        or images.endswith(\".jpeg\")):\n",
        "\n",
        "        filename = 'frame-' + f'{ix:05d}' + '.jpg'\n",
        "        ix = ix + 1\n",
        "        #print(images)\n",
        "        outfile = os.path.join(outputDir, filename)\n",
        "        #print(outfile)\n",
        "        image = load_image('/content/frames/' + images)\n",
        "        image = openpose(image)\n",
        "        image.save(outfile)\n",
        "\n"
      ],
      "metadata": {
        "id": "cnuSYUdK5hiJ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "24f1088f-7fac-4791-e92d-7f21918d8fbf"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Extracting frames\n",
            "Processing frames\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 71/71 [00:58<00:00,  1.21it/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "from os.path import exists, join, basename, splitext\n",
        "from os import listdir\n",
        "from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler\n",
        "from controlnet_aux import OpenposeDetector\n",
        "from PIL import Image\n",
        "from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler\n",
        "import torch\n",
        "from diffusers.utils import load_image\n",
        "from tqdm import tqdm\n",
        "\n",
        "!rm -fr /content/frames\n",
        "\n",
        "#@markdown ### ▶️ Process Folder\n",
        "#@markdown Folder to process\n",
        "folder_name = \"\" #@param {type:\"string\"}\n",
        "\n",
        "outputDir = os.path.join(folder_name, 'controlnet')\n",
        "\n",
        "if not os.path.exists(outputDir):\n",
        "  !mkdir {outputDir}\n",
        "\n",
        "# import the modules\n",
        "openpose = OpenposeDetector.from_pretrained('lllyasviel/ControlNet')\n",
        "\n",
        "print(\"Processing images\")\n",
        "# get the path/directory\n",
        "for images in tqdm(sorted(os.listdir(folder_name))):\n",
        "    #print(images)\n",
        "    # check if the image ends with png or jpg or jpeg\n",
        "    if (images.endswith(\".png\") or images.endswith(\".jpg\")\\\n",
        "        or images.endswith(\".jpeg\")):\n",
        "\n",
        "        outfile = os.path.join(outputDir, images)\n",
        "        #print(outfile)\n",
        "        image = load_image(os.path.join(folder_name,images))\n",
        "        image = openpose(image)\n",
        "        image.save(outfile)\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "cellView": "form",
        "id": "PYAFhb0gkbfD"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}