{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Instructions\n",
        "### 1) hit the white play button below \n",
        "### 2) grab yourself a coffee 🍹 (10min wait) \n",
        "### 3) scroll all the way to bottom of output and open link \"Running on public URL: https://xxxxxxxxx.gradio.live\" \n",
        "### 4) there are many parameters, read here what they mean: https://github.com/lunarring/latentblending/blob/main/parameters.md\n",
        "👇 (start here, move cursor below finger and play button will appear)"
      ],
      "metadata": {
        "id": "t9DPiP5BgqfF"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
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            "e541fae739584cc3b9bbbf490f8fa2cb",
            "e36754be14a6467e8afb564c87a53d51",
            "93fe3baa643548b185cc1bcb7e3945d8",
            "f3acd617d38740c480bc5d7470da1695",
            "ba4336f6577c45bea4af940ea08b57d1",
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            "15e76ca9be0d4f7484eba56d5a22a6ee",
            "2f09ee0caddb4a9d94a8616fc99607a5",
            "283eae336370485181bd8ea172debc9a",
            "51385d57b85d4440ada34a57f3bd945a",
            "5e3576e621584100ae7f8746cbcdf75c",
            "ab6d9d0cf3204fc9bf94e23b2ce22256",
            "baae00db06d1497eab6e1b5acda26c56",
            "7e77f56335944b30a408cdd2b6a7420b",
            "08ccfb2c004a46a995723d6e6395b345"
          ]
        },
        "id": "jgZQj-tE6GWW",
        "outputId": "3c820598-329a-4f8f-f09c-ce0163333a51",
        "collapsed": true,
        "cellView": "form"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
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            "Collecting open-clip-torch\n",
            "  Using cached open_clip_torch-2.9.3-py3-none-any.whl (1.4 MB)\n",
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            "Installing collected packages: sentencepiece, protobuf, ftfy, open-clip-torch\n",
            "  Attempting uninstall: protobuf\n",
            "    Found existing installation: protobuf 3.19.6\n",
            "    Uninstalling protobuf-3.19.6:\n",
            "      Successfully uninstalled protobuf-3.19.6\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",
            "tensorflow 2.9.2 requires protobuf<3.20,>=3.9.2, but you have protobuf 3.20.3 which is incompatible.\n",
            "tensorboardx 2.5.1 requires protobuf<=3.20.1,>=3.8.0, but you have protobuf 3.20.3 which is incompatible.\n",
            "tensorboard 2.9.1 requires protobuf<3.20,>=3.9.2, but you have protobuf 3.20.3 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed ftfy-6.1.1 open-clip-torch-2.9.3 protobuf-3.20.3 sentencepiece-0.1.97\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting gradio\n",
            "  Using cached gradio-3.16.1-py3-none-any.whl (14.2 MB)\n",
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            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "  Downloading uc_micro_py-1.0.1-py3-none-any.whl (6.2 kB)\n",
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            "Building wheels for collected packages: ffmpy, python-multipart\n",
            "  Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for ffmpy: filename=ffmpy-0.3.0-py3-none-any.whl size=4711 sha256=82adb5a05896febb2e0f4309bfa6bc4a2e5ca3b030415afd9d8676cc4a7c7ae4\n",
            "  Stored in directory: /root/.cache/pip/wheels/ff/5b/59/913b443e7369dc04b61f607a746b6f7d83fb65e2e19fcc958d\n",
            "  Building wheel for python-multipart (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for python-multipart: filename=python_multipart-0.0.5-py3-none-any.whl size=31678 sha256=337e866414b4cda885635ae14d369f3bfd215749e27dc7e4b7dcec7db43b1ff4\n",
            "  Stored in directory: /root/.cache/pip/wheels/9e/fc/1c/cf980e6413d3ee8e70cd8f39e2366b0f487e3e221aeb452eb0\n",
            "Successfully built ffmpy python-multipart\n",
            "Installing collected packages: rfc3986, pydub, ffmpy, websockets, uc-micro-py, sniffio, python-multipart, pycryptodome, orjson, mdurl, h11, uvicorn, markdown-it-py, linkify-it-py, anyio, starlette, mdit-py-plugins, httpcore, httpx, fastapi, gradio\n",
            "Successfully installed anyio-3.6.2 fastapi-0.89.1 ffmpy-0.3.0 gradio-3.16.1 h11-0.14.0 httpcore-0.16.3 httpx-0.23.3 linkify-it-py-1.0.3 markdown-it-py-2.1.0 mdit-py-plugins-0.3.3 mdurl-0.1.2 orjson-3.8.5 pycryptodome-3.16.0 pydub-0.25.1 python-multipart-0.0.5 rfc3986-1.5.0 sniffio-1.3.0 starlette-0.22.0 uc-micro-py-1.0.1 uvicorn-0.20.0 websockets-10.4\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
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            "Installing collected packages: protobuf\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",
            "\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",
            "tensorflow 2.9.2 requires protobuf<3.20,>=3.9.2, but you have protobuf 3.20.1 which is incompatible.\n",
            "tensorboard 2.9.1 requires protobuf<3.20,>=3.9.2, but you have protobuf 3.20.1 which is incompatible.\n",
            "googleapis-common-protos 1.57.1 requires protobuf!=3.20.0,!=3.20.1,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.1 which is incompatible.\n",
            "google-cloud-translate 3.8.4 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.1 which is incompatible.\n",
            "google-cloud-language 2.6.1 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.1 which is incompatible.\n",
            "google-cloud-firestore 2.7.3 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.1 which is incompatible.\n",
            "google-cloud-datastore 2.11.1 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.1 which is incompatible.\n",
            "google-cloud-bigquery 3.4.1 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.1 which is incompatible.\n",
            "google-cloud-bigquery-storage 2.17.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.1 which is incompatible.\n",
            "google-api-core 2.11.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.1 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed protobuf-3.20.1\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
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            "remote: Enumerating objects: 492, done.\u001b[K\n",
            "remote: Counting objects: 100% (12/12), done.\u001b[K\n",
            "remote: Compressing objects: 100% (9/9), done.\u001b[K\n",
            "remote: Total 492 (delta 8), reused 3 (delta 3), pack-reused 480\u001b[K\n",
            "Receiving objects: 100% (492/492), 8.31 MiB | 38.32 MiB/s, done.\n",
            "Resolving deltas: 100% (285/285), done.\n",
            "Already up to date.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/pytorch_lightning/utilities/distributed.py:258: LightningDeprecationWarning: `pytorch_lightning.utilities.distributed.rank_zero_only` has been deprecated in v1.8.1 and will be removed in v1.10.0. You can import it from `pytorch_lightning.utilities` instead.\n",
            "  rank_zero_deprecation(\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "Resolving cdn-lfs.huggingface.co (cdn-lfs.huggingface.co)... 108.156.83.35, 108.156.83.76, 108.156.83.97, ...\n",
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            "Saving to: ‘v2-1_512-ema-pruned.ckpt’\n",
            "\n",
            "v2-1_512-ema-pruned 100%[===================>]   4.86G   152MB/s    in 33s     \n",
            "\n",
            "2023-01-14 11:35:10 (151 MB/s) - ‘v2-1_512-ema-pruned.ckpt’ saved [5214865159/5214865159]\n",
            "\n",
            "--2023-01-14 11:35:10--  http://v2-1_512-ema-pruned.ckpt/\n",
            "Resolving v2-1_512-ema-pruned.ckpt (v2-1_512-ema-pruned.ckpt)... failed: Name or service not known.\n",
            "wget: unable to resolve host address ‘v2-1_512-ema-pruned.ckpt’\n",
            "FINISHED --2023-01-14 11:35:10--\n",
            "Total wall clock time: 33s\n",
            "Downloaded: 1 files, 4.9G in 33s (151 MB/s)\n",
            "LatentDiffusion: Running in eps-prediction mode\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\n",
            "DiffusionWrapper has 865.91 M params.\n",
            "making attention of type 'vanilla-xformers' with 512 in_channels\n",
            "building MemoryEfficientAttnBlock with 512 in_channels...\n",
            "Working with z of shape (1, 4, 32, 32) = 4096 dimensions.\n",
            "making attention of type 'vanilla-xformers' with 512 in_channels\n",
            "building MemoryEfficientAttnBlock with 512 in_channels...\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading:   0%|          | 0.00/3.94G [00:00<?, ?B/s]"
            ],
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        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Colab notebook detected. This cell will run indefinitely so that you can see errors and logs. To turn off, set debug=False in launch().\n",
            "Running on public URL: https://be577a0c-1c52-4507.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades (NEW!), check out Spaces: https://huggingface.co/spaces\n",
            "STARTING DIFFUSION!\n",
            "autosetup_branching: num_inference_steps: 20 list_nmb_branches: [2, 3, 5, 9] list_injection_idx: [0, 5, 11, 17]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "computing transition:   0%|          | 0/21 [00:00<?, ?it/s]"
            ],
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        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "DONE DIFFUSION! Resulted in 9 images\n",
            "save is called!\n",
            "MovieSaver initialized. fps=30 crf=24 pix_fmt=yuv420p codec=libx264 preset=fast\n"
          ]
        },
        {
          "output_type": "display_data",
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            ],
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              "version_major": 2,
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              "model_id": "1eb11001041144859375d5feb1b4c5bc"
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          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Initialization done. Movie shape: (512, 512, 3)\n",
            "Movie saved, 10s playtime, watch here: \n",
            "movie_230114_114003.mp4\n"
          ]
        }
      ],
      "source": [
        "#@title\n",
        "# installs\n",
        "!pip install omegaconf\n",
        "!pip install fastcore -U\n",
        "!pip install Pillow\n",
        "!pip install ffmpeg-python\n",
        "!pip install einops\n",
        "\n",
        "!pip install open-clip-torch\n",
        "!pip install gradio\n",
        "\n",
        "import os\n",
        "from subprocess import getoutput\n",
        "\n",
        "os.system(\"pip install --extra-index-url https://download.pytorch.org/whl/cu113 torch torchvision==0.13.1+cu113\")\n",
        "os.system(\"pip install triton==2.0.0.dev20220701\")\n",
        "gpu_info = getoutput('nvidia-smi')\n",
        "if(\"A10G\" in gpu_info):\n",
        "    os.system(f\"pip install -q https://github.com/camenduru/stable-diffusion-webui-colab/releases/download/0.0.15/xformers-0.0.15.dev0+4c06c79.d20221205-cp38-cp38-linux_x86_64.whl\")\n",
        "elif(\"T4\" in gpu_info):\n",
        "    os.system(f\"pip install -q https://github.com/camenduru/stable-diffusion-webui-colab/releases/download/0.0.15/xformers-0.0.15.dev0+1515f77.d20221130-cp38-cp38-linux_x86_64.whl\")\n",
        "\n",
        "!pip install pytorch_lightning\n",
        "!pip install transformers\n",
        "\n",
        "# git\n",
        "!git clone https://github.com/lunarring/latentblending\n",
        "!cd latentblending; git pull; cd ..\n",
        "\n",
        "\n",
        "\n",
        "import sys\n",
        "sys.path.append(\"/content/latentblending\")\n",
        "import torch\n",
        "torch.backends.cudnn.benchmark = False\n",
        "import numpy as np\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')\n",
        "import warnings\n",
        "import torch\n",
        "from tqdm.auto import tqdm\n",
        "from PIL import Image\n",
        "# import matplotlib.pyplot as plt\n",
        "import torch\n",
        "from movie_util import MovieSaver\n",
        "from typing import Callable, List, Optional, Union\n",
        "from latent_blending import LatentBlending, add_frames_linear_interp\n",
        "from stable_diffusion_holder import StableDiffusionHolder\n",
        "torch.set_grad_enabled(False)\n",
        "\n",
        "\n",
        "#%% First let us spawn a stable diffusion holder\n",
        "device = \"cuda\" \n",
        "\n",
        "# ckpt download\n",
        "if not os.path.isfile('v2-1_512-ema-pruned.ckpt'):\n",
        "  !wget https://huggingface.co/stabilityai/stable-diffusion-2-1-base/resolve/main/v2-1_512-ema-pruned.ckpt v2-1_512-ema-pruned.ckpt\n",
        "\n",
        "fp_ckpt = \"v2-1_512-ema-pruned.ckpt\"\n",
        "fp_config = 'latentblending/configs/v2-inference.yaml'\n",
        "\n",
        "sdh = StableDiffusionHolder(fp_ckpt, fp_config, device) \n",
        "\n",
        "from latent_blending import get_time, yml_save, LatentBlending, add_frames_linear_interp, compare_dicts\n",
        "from gradio_ui import BlendingFrontend\n",
        "\n",
        "import gradio as gr\n",
        "\n",
        "if __name__ == \"__main__\":    \n",
        "   \n",
        "    self = BlendingFrontend(sdh)\n",
        "    \n",
        "    with gr.Blocks() as demo:\n",
        "        \n",
        "        with gr.Row():\n",
        "            prompt1 = gr.Textbox(label=\"prompt 1\")\n",
        "            prompt2 = gr.Textbox(label=\"prompt 2\")\n",
        "            negative_prompt = gr.Textbox(label=\"negative prompt\")          \n",
        "            \n",
        "        with gr.Row():\n",
        "            nmb_branches_final = gr.Slider(5, 125, self.nmb_branches_final, step=4, label='nmb trans images', interactive=True) \n",
        "            height = gr.Slider(256, 2048, self.height, step=128, label='height', interactive=True)\n",
        "            width = gr.Slider(256, 2048, self.width, step=128, label='width', interactive=True) \n",
        "            \n",
        "        with gr.Row():\n",
        "            num_inference_steps = gr.Slider(5, 100, self.num_inference_steps, step=1, label='num_inference_steps', interactive=True)\n",
        "            branch1_influence = gr.Slider(0.0, 1.0, self.branch1_influence, step=0.01, label='branch1_influence', interactive=True) \n",
        "            guidance_scale = gr.Slider(1, 25, self.guidance_scale, step=0.1, label='guidance_scale', interactive=True) \n",
        "    \n",
        "        with gr.Row():\n",
        "            depth_strength = gr.Slider(0.01, 0.99, self.depth_strength, step=0.01, label='depth_strength', interactive=True) \n",
        "            guidance_scale_mid_damper = gr.Slider(0.01, 2.0, self.guidance_scale_mid_damper, step=0.01, label='guidance_scale_mid_damper', interactive=True) \n",
        "            mid_compression_scaler = gr.Slider(1.0, 2.0, self.mid_compression_scaler, step=0.01, label='mid_compression_scaler', interactive=True) \n",
        "                \n",
        "        with gr.Row():\n",
        "            b_newseed1 = gr.Button(\"rand seed 1\")\n",
        "            seed1 = gr.Number(42, label=\"seed 1\", interactive=True)\n",
        "            b_newseed2 = gr.Button(\"rand seed 2\")\n",
        "            seed2 = gr.Number(420, label=\"seed 2\", interactive=True)\n",
        "            \n",
        "        with gr.Row():\n",
        "            b_run = gr.Button('step1: run preview')\n",
        "            \n",
        "        with gr.Row():\n",
        "            img1 = gr.Image(label=\"1/5\")\n",
        "            img2 = gr.Image(label=\"2/5\")\n",
        "            img3 = gr.Image(label=\"3/5\")\n",
        "            img4 = gr.Image(label=\"4/5\")\n",
        "            img5 = gr.Image(label=\"5/5\")\n",
        "            \n",
        "        with gr.Row():\n",
        "            b_save = gr.Button('step2: render video')\n",
        "            vid = gr.Video()\n",
        "        \n",
        "        with gr.Row():\n",
        "            duration = gr.Slider(0.1, 30, self.duration, step=0.1, label='duration', interactive=True) \n",
        "            fps = gr.Slider(1, 120, self.fps, step=1, label='fps', interactive=True)\n",
        "    \n",
        "        # Bind the on-change methods\n",
        "        depth_strength.change(fn=self.change_depth_strength, inputs=depth_strength)\n",
        "        num_inference_steps.change(fn=self.change_num_inference_steps, inputs=num_inference_steps)\n",
        "        nmb_branches_final.change(fn=self.change_nmb_branches_final, inputs=nmb_branches_final)\n",
        "        \n",
        "        guidance_scale.change(fn=self.change_guidance_scale, inputs=guidance_scale)\n",
        "        guidance_scale_mid_damper.change(fn=self.change_guidance_scale_mid_damper, inputs=guidance_scale_mid_damper)\n",
        "        mid_compression_scaler.change(fn=self.change_mid_compression_scaler, inputs=mid_compression_scaler)\n",
        "        \n",
        "        height.change(fn=self.change_height, inputs=height)\n",
        "        width.change(fn=self.change_width, inputs=width)\n",
        "        prompt1.change(fn=self.change_prompt1, inputs=prompt1)\n",
        "        prompt2.change(fn=self.change_prompt2, inputs=prompt2)\n",
        "        negative_prompt.change(fn=self.change_negative_prompt, inputs=negative_prompt)\n",
        "        seed1.change(fn=self.change_seed1, inputs=seed1)\n",
        "        seed2.change(fn=self.change_seed2, inputs=seed2)\n",
        "        fps.change(fn=self.change_fps, inputs=fps)\n",
        "        duration.change(fn=self.change_duration, inputs=duration)\n",
        "        branch1_influence.change(fn=self.change_branch1_influence, inputs=branch1_influence)\n",
        "    \n",
        "        b_newseed1.click(self.randomize_seed1, outputs=seed1)\n",
        "        b_newseed2.click(self.randomize_seed2, outputs=seed2)\n",
        "        b_run.click(self.run, outputs=[img1, img2, img3, img4, img5])\n",
        "        b_save.click(self.save, outputs=vid)\n",
        "    \n",
        "    demo.launch(share=self.share, inbrowser=True, debug=True, inline=False)\n"
      ]
    }
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