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{
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"cells": [
{
"cell_type": "markdown",
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"metadata": {
"id": "t9DPiP5BgqfF"
},
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"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)"
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]
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},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
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"cellView": "form",
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"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000,
"referenced_widgets": [
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"cb1224fc26f546ba801641e8fa1fd886",
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"610d37336d6d4fb29ccf7add5f031136",
"0e5aa1e9d09a49c98836059467085af9",
"480afd6353a342d89e4c94e862b4886b",
"baee0201374a495085e24fb57e2a2021",
"b2b87327203e41a4a9655cdd96843f8e",
"22da2842f1194df7b13dd88403aa6863"
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]
},
"collapsed": true,
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"id": "jgZQj-tE6GWW",
"outputId": "9c4ee706-b620-43d4-fdee-412fba47f32e"
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},
"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 omegaconf\n",
" Downloading omegaconf-2.3.0-py3-none-any.whl (79 kB)\n",
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"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
"Building wheels for collected packages: antlr4-python3-runtime\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=144575 sha256=0628fded204cc90e08bd2ad25cdb360e7f5019eb3b6b2daa8dd3ca9b8b58402f\n",
" Stored in directory: /root/.cache/pip/wheels/b1/a3/c2/6df046c09459b73cc9bb6c4401b0be6c47048baf9a1617c485\n",
"Successfully built antlr4-python3-runtime\n",
"Installing collected packages: antlr4-python3-runtime, omegaconf\n",
"Successfully installed antlr4-python3-runtime-4.9.3 omegaconf-2.3.0\n"
]
},
{
"output_type": "display_data",
"data": {
"application/vnd.colab-display-data+json": {
"pip_warning": {
"packages": [
"pydevd_plugins"
]
}
}
},
"metadata": {}
},
{
"output_type": "stream",
"name": "stdout",
"text": [
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"Successfully installed ffmpeg-python-0.2.0\n",
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"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
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"Installing collected packages: sentencepiece, protobuf, ftfy, huggingface-hub, open-clip-torch\n",
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" 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",
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"\u001b[0mSuccessfully installed ftfy-6.1.1 huggingface-hub-0.11.1 open-clip-torch-2.9.3 protobuf-3.20.3 sentencepiece-0.1.97\n",
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"Collecting uc-micro-py\n",
" 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",
2023-01-15 16:07:29 +00:00
" Created wheel for ffmpy: filename=ffmpy-0.3.0-py3-none-any.whl size=4711 sha256=8d8a7d8e0bc815999aeb702025059b8683e80d8b3c84e8abb2b8262c59394671\n",
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" Stored in directory: /root/.cache/pip/wheels/ff/5b/59/913b443e7369dc04b61f607a746b6f7d83fb65e2e19fcc958d\n",
" Building wheel for python-multipart (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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" Created wheel for python-multipart: filename=python_multipart-0.0.5-py3-none-any.whl size=31678 sha256=e973c59a971e6192be3d9611b458cc2a171dcd6eb05bc604c98439b70e2b9b48\n",
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" 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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"Collecting pytorch_lightning\n",
" Downloading pytorch_lightning-1.8.6-py3-none-any.whl (800 kB)\n",
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"Collecting protobuf<=3.20.1,>=3.8.0\n",
" Downloading protobuf-3.20.1-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl (1.0 MB)\n",
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"Installing collected packages: protobuf, torchmetrics, tensorboardX, lightning-utilities, pytorch_lightning\n",
2023-01-14 11:41:51 +00:00
" 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",
2023-01-15 16:07:29 +00:00
"\u001b[0mSuccessfully installed lightning-utilities-0.5.0 protobuf-3.20.1 pytorch_lightning-1.8.6 tensorboardX-2.5.1 torchmetrics-0.11.0\n",
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"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
2023-01-15 16:07:29 +00:00
"Collecting transformers\n",
" Downloading transformers-4.25.1-py3-none-any.whl (5.8 MB)\n",
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"Installing collected packages: tokenizers, transformers\n",
"Successfully installed tokenizers-0.13.2 transformers-4.25.1\n",
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"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)... 65.9.86.27, 65.9.86.11, 65.9.86.14, ...\n",
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"Total wall clock time: 42s\n",
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"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",
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"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",
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"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",
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"Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\n",
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"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": [
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],
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"version_major": 2,
"version_minor": 0,
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"model_id": "cb1224fc26f546ba801641e8fa1fd886"
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}
},
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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",
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"Running on public URL: https://014826da-2448-4ebf.gradio.live\n",
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"\n",
"This share link expires in 72 hours. For free permanent hosting and GPU upgrades (NEW!), check out Spaces: https://huggingface.co/spaces\n",
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"Keyboard interruption in main thread... closing server.\n",
"Killing tunnel 127.0.0.1:7860 <> https://014826da-2448-4ebf.gradio.live\n"
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]
}
],
"source": [
"#@title\n",
"# installs\n",
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"!pip install open-clip-torch\n",
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"!pip install omegaconf\n",
"!pip install fastcore -U\n",
"!pip install Pillow\n",
"!pip install ffmpeg-python\n",
"!pip install einops\n",
"!pip install gradio\n",
"\n",
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"import os, sys\n",
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"from subprocess import getoutput\n",
"\n",
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"# Xformers\n",
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"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",
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"# Get Latent Blending from git / pull \n",
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"!git clone https://github.com/lunarring/latentblending\n",
"!cd latentblending; git pull; cd ..\n",
"sys.path.append(\"/content/latentblending\")\n",
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"\n",
"# Imports\n",
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"import torch\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 torch\n",
"from typing import Callable, List, Optional, Union\n",
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"from latent_blending import LatentBlending, add_frames_linear_interp, get_time, yml_save, LatentBlending, compare_dicts\n",
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"from stable_diffusion_holder import StableDiffusionHolder\n",
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"from gradio_ui import BlendingFrontend\n",
"import gradio as gr\n",
"\n",
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"torch.set_grad_enabled(False)\n",
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"torch.backends.cudnn.benchmark = False\n",
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"\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",
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" \n",
" self = BlendingFrontend(sdh) # Yes this is possible in python and yes it is an awesome trick\n",
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" \n",
" with gr.Blocks() as demo:\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",
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" duration = gr.Slider(0.1, 30, self.duration, step=0.1, label='video duration', interactive=True) \n",
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" 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",
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" \n",
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" with gr.Row():\n",
" seed1 = gr.Number(42, label=\"seed 1\", interactive=True)\n",
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" b_newseed1 = gr.Button(\"randomize seed 1\", variant='secondary')\n",
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" seed2 = gr.Number(420, label=\"seed 2\", interactive=True)\n",
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" b_newseed2 = gr.Button(\"randomize seed 2\", variant='secondary')\n",
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" with gr.Row():\n",
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" b_compute_transition = gr.Button('compute transition', variant='primary')\n",
" \n",
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" 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",
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" vid_transition = gr.Video()\n",
" \n",
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" # 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",
" \n",
" height.change(fn=self.change_height, inputs=height)\n",
" width.change(fn=self.change_width, inputs=width)\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",
" 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",
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" b_compute_transition.click(self.compute_transition, \n",
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" \n",
" demo.launch(share=self.share, inbrowser=True, inline=False, debug=True)\n"
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]
}
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