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updated COLAB notebooks to install a CUDA version compatible with DLC… · DeepLabCut/DeepLabCut@258b19b · GitHub
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n-poulsenn-poulsen
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updated COLAB notebooks to install a CUDA version compatible with DLC (#2506)
1 parent 8ce2377 commit 258b19b

7 files changed

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‎examples/COLAB/COLAB_3miceDemo.ipynb‎

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},
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"outputs": [],
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"source": [
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"# Installs a CUDA version compatible with tensorflow on COLAB\n",
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"!apt update && apt install cuda-11-8\n",
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"\n",
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"# Install the latest DeepLabCut version:\n",
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"!pip install \"deeplabcut[tf]\""
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]

‎examples/COLAB/COLAB_DEMO_SuperAnimal.ipynb‎

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},
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"outputs": [],
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"source": [
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"!apt update && apt install cuda-11-8\n",
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"!pip install deeplabcut[tf,modelzoo]"
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]
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},
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},
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{
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"cell_type": "markdown",
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"source": [
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"## Please select a video you want to run SuperAnimal-X on:"
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],
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"metadata": {
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"id": "GXf8N4v28Xqo"
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}
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},
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"source": [
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"## Please select a video you want to run SuperAnimal-X on:"
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]
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},
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{
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"cell_type": "code",
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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": "A8sDYMa08f62"
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},
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"source": [
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"## Next select the model you want to use, Quadruped or TopViewMouse\n",
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"- See http://modelzoo.deeplabcut.org/ for more details on these models\n",
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"- The pcutoff is for visualization only, namely only keypoints with a value over what you set are shown. 0 is low confidience, 1 is perfect confidience of the model."
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],
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"metadata": {
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"id": "A8sDYMa08f62"
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}
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]
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},
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{
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"cell_type": "code",
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},
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{
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"cell_type": "markdown",
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"source": [
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"## Okay, let's go! 🐭🦓🐻"
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],
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"metadata": {
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"id": "zsB0pGtj9Luq"
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}
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},
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"source": [
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"## Okay, let's go! 🐭🦓🐻"
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]
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},
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{
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"cell_type": "code",
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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": "gPLZSBpD34Mj"
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},
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"source": [
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"## Let's view the video in Colab:\n",
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"- otherwise, you can download and look at the video from the left side of your screen! It will end with _labeled.mp4\n",
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"- If your data doesn't work as well as you'd like, consider fine-tuning our model on your data, changing the pcutoff, changing the scale-range\n",
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"(pick values smaller and larger than your video image input size). See our repo for more details."
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],
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"metadata": {
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"id": "gPLZSBpD34Mj"
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}
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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": "ejFJ1Pbg33i6"
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},
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"outputs": [],
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"source": [
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"from base64 import b64encode\n",
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"from IPython.display import HTML\n",
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" <source src=\"%s\" type=\"video/mp4\">\n",
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"</video>\n",
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"\"\"\" % data_url)"
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],
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"metadata": {
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"id": "ejFJ1Pbg33i6"
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},
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"execution_count": null,
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"outputs": []
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]
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}
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],
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"metadata": {
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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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}

‎examples/COLAB/COLAB_DEMO_mouse_openfield.ipynb‎

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{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"accelerator": "GPU",
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"colab": {
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"name": "Colab_DEMO_mouse_openfield.ipynb",
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"provenance": [],
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"collapsed_sections": []
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},
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"kernelspec": {
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"display_name": "Python [default]",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.9"
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}
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},
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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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"id": "view-in-github",
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"colab_type": "text"
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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/DeepLabCut/DeepLabCut/blob/master/examples/COLAB/COLAB_DEMO_mouse_openfield.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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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Installs a CUDA version compatible with tensorflow on COLAB\n",
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"!apt update && apt install cuda-11-8"
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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": "Ew6r4hotoQjt"
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},
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"outputs": [],
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"source": [
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"# Clone the entire deeplabcut repo so we can use the demo data:\n",
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"!git clone -l -s https://github.com/DeepLabCut/DeepLabCut.git cloned-DLC-repo\n",
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"%cd cloned-DLC-repo\n",
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"!ls"
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],
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"execution_count": null,
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"outputs": []
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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": "yDaY78dFoxyD"
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},
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"outputs": [],
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"source": [
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"%cd /content/cloned-DLC-repo/examples/openfield-Pranav-2018-10-30\n",
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"!ls"
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],
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"execution_count": null,
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"outputs": []
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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": "q23BzhA6CXxu"
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},
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"outputs": [],
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"source": [
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"# Install the latest DeepLabCut version (this will take a few minutes to install all the dependencies!)\n",
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"%cd /content/cloned-DLC-repo/\n",
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"!pip install \".[tf]\""
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],
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"execution_count": null,
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"outputs": []
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]
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"cell_type": "markdown",
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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": "sXufoX6INe6w"
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"outputs": [],
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"source": [
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"import deeplabcut"
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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": "Z7ZlDr3wV4D1"
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},
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"outputs": [],
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"source": [
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"#create a path variable that links to the config file:\n",
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"path_config_file = '/content/cloned-DLC-repo/examples/openfield-Pranav-2018-10-30/config.yaml'\n",
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"\n",
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"# Loading example data set:\n",
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"deeplabcut.load_demo_data(path_config_file)"
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],
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]
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},
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"cell_type": "markdown",
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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": "_pOvDq_2oEJW"
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},
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"outputs": [],
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"source": [
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"#let's also change the display and save_iters just in case Colab takes away the GPU... \n",
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"#if that happens, you can reload from a saved point. Typically, you want to train to 200,000 + iterations.\n",
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"\n",
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"#this will run until you stop it (CTRL+C), or hit \"STOP\" icon, or when it hits the end (default, 1.03M iterations). \n",
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"#Whichever you chose, you will see what looks like an error message, but it's not an error - don't worry...."
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "nv4zlbrnoEJg"
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},
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"outputs": [],
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"source": [
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"%matplotlib notebook\n",
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"deeplabcut.evaluate_network(path_config_file,plotting=True)\n",
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"\n",
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"# Here you want to see a low pixel error! Of course, it can only be as good as the labeler, so be sure your labels are good!"
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],
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"execution_count": null,
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"execution_count": null,
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"metadata": {
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"id": "Y_LZiS_0oEJl"
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"outputs": [],
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"videofile_path = ['/content/cloned-DLC-repo/examples/openfield-Pranav-2018-10-30/videos/m3v1mp4.mp4'] #Enter the list of videos to analyze.\n",
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"deeplabcut.analyze_videos(path_config_file,videofile_path, videotype='.mp4')"
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]
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},
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"cell_type": "code",
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"metadata": {
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"id": "6aDF7Q7KoEKE"
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"outputs": [],
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"deeplabcut.create_labeled_video(path_config_file,videofile_path)"
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"metadata": {
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"outputs": [],
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"source": [
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"deeplabcut.plot_trajectories(path_config_file,videofile_path)"
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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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"collapsed_sections": [],
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"name": "Colab_DEMO_mouse_openfield.ipynb",
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"provenance": []
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},
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"kernelspec": {
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"display_name": "Python [default]",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.9"
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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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