126 lines
3.2 KiB
Plaintext
126 lines
3.2 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"colab_type": "text",
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"id": "view-in-github"
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},
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"source": [
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"<a href=\"https://colab.research.google.com/github/hzwer/arXiv2020-RIFE/blob/main/Colab_demo.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "FypCcZkNNt2p"
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},
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"outputs": [],
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"source": [
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"!git clone https://github.com/hzwer/arXiv2020-RIFE"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "1wysVHxoN54f"
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},
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"outputs": [],
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"source": [
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"!mkdir /content/arXiv2020-RIFE/train_log\n",
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"%cd /content/arXiv2020-RIFE/train_log\n",
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"!gdown --id 1APIzVeI-4ZZCEuIRE1m6WYfSCaOsi_7_\n",
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"!7z e RIFE_trained_model_v3.6.zip"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "AhbHfRBJRAUt"
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},
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"outputs": [],
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"source": [
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"%cd /content/arXiv2020-RIFE/\n",
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"!gdown --id 1i3xlKb7ax7Y70khcTcuePi6E7crO_dFc\n",
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"!pip install scikit-video"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "rirngW5uRMdg"
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},
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"source": [
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"Please upload your video to content/arXiv2020-RIFE/video.mp4, or use our demo video."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "dnLn4aHHPzN3"
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},
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"outputs": [],
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"source": [
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"!nvidia-smi\n",
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"!python3 inference_video.py --exp=2 --video=demo.mp4 --montage"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "77KK6lxHgJhf"
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},
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"source": [
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"Our demo.mp4 is 25FPS. You can adjust the parameters for your own perference.\n",
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"For example: \n",
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"--fps=60 --exp=1 --video=mydemo.avi --png"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"cellView": "code",
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"id": "0zIBbVE3UfUD"
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},
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"outputs": [],
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"source": [
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"from IPython.display import display, Image\n",
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"import moviepy.editor as mpy\n",
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"display(mpy.ipython_display('demo_4X_100fps.mp4', height=256, max_duration=100.))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "tWkJCNgP3zXA"
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},
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"outputs": [],
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"source": [
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"!python3 inference_img.py --img demo/I0_0.png demo/I0_1.png\n",
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"ffmpeg -r 10 -f image2 -i output/img%d.png -s 448x256 -vf \"split[s0][s1];[s0]palettegen=stats_mode=single[p];[s1][p]paletteuse=new=1\" output/slomo.gif\n",
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"# Image interpolation"
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]
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}
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],
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"metadata": {
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"accelerator": "GPU",
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"colab": {
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"include_colab_link": true,
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"name": "Untitled0.ipynb",
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"provenance": []
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},
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"kernelspec": {
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"display_name": "Python 3",
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"name": "python3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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