diff --git a/Video-Image-Data-Tutorial/Ford_Video_Analysis.ipynb b/Video-Image-Data-Tutorial/Ford_Video_Analysis.ipynb
index b106c899cf2afe2a557fd6c4dd7f3faafb7a12f9..c65289a81d9fb1e5b632d9795fcad66fcf22e60c 100644
--- a/Video-Image-Data-Tutorial/Ford_Video_Analysis.ipynb
+++ b/Video-Image-Data-Tutorial/Ford_Video_Analysis.ipynb
@@ -1,235 +1,233 @@
{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "OqSmFS3lZj9Y"
- },
- "source": [
- "# <center> Video Image Data </center>\n",
- "#### CMSE 495 Ford Group\n",
- "\n",
- "This tutorial teaches the user how to input a video file, such a mp4 and convert each frame of the video into a jpeg image using python, primarily in a Jupyter notebook."
- ]
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "OqSmFS3lZj9Y"
+ },
+ "source": [
+ "# <center> Video Image Data </center>\n",
+ "#### CMSE 495 Ford Group\n",
+ "\n",
+ "This tutorial teaches the user how to input a video file, such a mp4 and convert each frame of the video into a jpeg image using python, primarily in a Jupyter notebook."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "uey1neRTkRwd"
+ },
+ "source": [
+ "[](https://colab.research.google.com/github/pathakis/DataTools_Tutorial_Demo/blob/main/Video-Image-Data-Tutorial/Ford_Video_Analysis.ipynb)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "GQIJxk_kdjT1"
+ },
+ "source": [
+ "<b> Environment Setup (Makefile):</b>\n",
+ "- Use the command 'make innit' automatically set up the environment for you.\n",
+ "\n",
+ "<b> Environment Setup (Manual):</b>\n",
+ "- Set up new environment using pip/conda (Conda Recommended). Use command \n",
+ "\n",
+ " <code> conda create -n envs python=3.10 </code>\n",
+ "\n",
+ "- Activate your new environment. Use command \n",
+ "\n",
+ " <code> conda activate envs</code>\n",
+ "\n",
+ "- Install the requisite packages.Use command \n",
+ "\n",
+ " <code> pip install opencv-python</code> or,\n",
+ "\n",
+ " <code> conda install -c conda-forge opencv</code>\n",
+ "\n",
+ "<b> Usage Instructions:</b>\n",
+ "\n",
+ "- The example call shows the format in which this func may be used.\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "f0aUW4PLdobE"
+ },
+ "source": [
+ "This process uses 2 packages called [os](https://docs.python.org/3/library/os.html) and [cv2](https://pypi.org/project/opencv-python/). Os provides miscellaneous operating system interfaces such as opening and reading the files."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "JGkN_k3BgXV8"
+ },
+ "outputs": [],
+ "source": [
+ "# !pip install opencv-python"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "PCbpVR-HZzmt"
+ },
+ "outputs": [],
+ "source": [
+ "import cv2\n",
+ "import os\n",
+ "import glob\n",
+ "import urllib.request\n",
+ "\n",
+ "\n",
+ "def video_to_frames(file_path, directory_path, greyscale = False):\n",
+ "\n",
+ " '''This function will change a video file to a frames'''\n",
+ " \n",
+ " #opening the video\n",
+ " vidcap = cv2.VideoCapture(file_path) \n",
+ " \n",
+ " dirname = directory_path\n",
+ " os.makedirs(dirname, exist_ok=True)\n",
+ " \n",
+ " #capturing a frame as well as a boolean value representing whether an image was properly opened\n",
+ " success,image = vidcap.read()\n",
+ " \n",
+ " count = 0\n",
+ " \n",
+ " while success:\n",
+ " \n",
+ " #this is specifically for foam_segmented.avi\n",
+ " if greyscale:\n",
+ " image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n",
+ " \n",
+ " #writing the image to a the directory path that was specified, \n",
+ " #if the path specified does not exist then it will be created\n",
+ " #this finctionality was added so that the images could be stored in a separate folder\n",
+ " #example of output file names: 1.jpg, 2.jpg, 3.jpg, and so on\n",
+ " cv2.imwrite(os.path.join(dirname, str(count)+\".jpg\"), image)\n",
+ " success,image = vidcap.read()\n",
+ " count += 1\n",
+ " #All the frames will be added in order\n",
+ " cv2.waitKey(1) \n",
+ " \n",
+ " #releasing the threads\n",
+ " vidcap.release()\n"
+ ]
+ },
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "hBfLcvMhh6v7"
+ },
+ "source": [
+ "DEMO FOR THE **avi_to_frames** \n",
+ "\n",
+ "1. To download a sample avi file that you want to work with, use the following code `urllib.request.urlretrieve('https://file-examples.com/wp-content/uploads/2018/04/file_example_AVI_480_750kB.avi', 'testing.mp4')` \n",
+ "\n",
+ "2. After the video has been downloaded `avi_frames(./testing.mp4, path_to_where_you_want_the_frames, False)` this will create a folder with frames from the video."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "-N-hJD11jJjo"
+ },
+ "outputs": [],
+ "source": [
+ "# Making a Video From Frames\n",
+ "def frames_to_video(directory_path, fps, width, height):\n",
+ " fourcc = cv2.VideoWriter_fourcc(*'mp4v')\n",
+ " video = cv2.VideoWriter('video.avi', fourcc, fps, (width, height))\n",
+ " num_frames = len([name for name in os.listdir(directory_path) if os.path.isfile(name)])\n",
+ "\n",
+ " for j in range(num_frames):\n",
+ " img = cv2.imread(str(j) + '.jpg')\n",
+ " video.write(img)\n",
+ "\n",
+ " cv2.destroyAllWindows()\n",
+ " video.release()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "sIhvc4DplLkE"
+ },
+ "source": [
+ "DEMO FOR THE **frames_to_video** \n",
+ "\n",
+ "1. We will be working with the frames that we created using `avi_to_frames`. If you have not created those frames feel free to look at the steps above.\n",
+ "\n",
+ "2. Run the following command (**make the necessary changes in the function call**)`frames_to_video(where_the_frames_are, fps, width, height)`\n",
+ "\n",
+ "3. The video will show up in the current directory."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "bnfzxPNJeZVS"
+ },
+ "source": [
+ "**The code below will put the image arrays into a list.** This snippet of code utilizes glob but packages like os can also be used."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "mLbqPW7SeJd-"
+ },
+ "outputs": [],
+ "source": [
+ "path = glob.glob(\"./*.jpg\")\n",
+ "images = []\n",
+ "for img in path:\n",
+ " n = cv2.imread(img)\n",
+ " images.append(n)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "GIq-_h4wdxWM"
+ },
+ "source": [
+ "<b> References:</b>\n",
+ "- [Managing Environments](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html)\n",
+ "- [Open CV in python](https://pypi.org/project/opencv-python/)\n",
+ "- [Colab Button](https://www.youtube.com/watch?v=RoGZIbwzG5w)"
+ ]
+ }
+ ],
+ "metadata": {
+ "colab": {
+ "collapsed_sections": [],
+ "name": "Ford_Video_Analysis.ipynb",
+ "provenance": []
+ },
+ "kernelspec": {
+ "display_name": "base",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "name": "python",
+ "version": "3.9.15"
+ },
+ "vscode": {
+ "interpreter": {
+ "hash": "4f3567101b31d35f97cf2856951ebbba1e09a3f852422478e736adda2bb3beee"
+ }
+ }
},
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "uey1neRTkRwd"
- },
- "source": [
- "[](https://colab.research.google.com/github/pathakis/DataTools_Tutorial_Demo/blob/main/Video-Image-Data-Tutorial/Ford_Video_Analysis.ipynb)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "GQIJxk_kdjT1"
- },
- "source": [
- "<b> Environment Setup (Makefile):</b>\n",
- "- Use the command 'make innit' automatically set up the environment for you.\n",
- "\n",
- "<b> Environment Setup (Manual):</b>\n",
- "- Set up new environment using pip/conda (Conda Recommended). Use command \n",
- "\n",
- " <code> conda create -n envs python=3.10 </code>\n",
- "\n",
- "- Activate your new environment. Use command \n",
- "\n",
- " <code> conda activate envs</code>\n",
- "\n",
- "- Install the requisite packages.Use command \n",
- "\n",
- " <code> pip install opencv-python</code> or,\n",
- "\n",
- " <code> conda install -c conda-forge opencv</code>\n",
- "\n",
- "<b> Usage Instructions:</b>\n",
- "\n",
- "- The example call shows the format in which this func may be used.\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "f0aUW4PLdobE"
- },
- "source": [
- "This process uses 2 packages called [os](https://docs.python.org/3/library/os.html) and [cv2](https://pypi.org/project/opencv-python/). Os provides miscellaneous operating system interfaces such as opening and reading the files."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "JGkN_k3BgXV8"
- },
- "outputs": [],
- "source": [
- "# !pip install opencv-python"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "PCbpVR-HZzmt"
- },
- "outputs": [],
- "source": [
- "import cv2\n",
- "import os\n",
- "import glob\n",
- "import urllib.request\n",
- "\n",
- "\n",
- "def video_to_frames(file_path, directory_path, greyscale = False):\n",
- "\n",
- " '''This function will change a video file to a frames'''\n",
- " \n",
- " #opening the video\n",
- " vidcap = cv2.VideoCapture(file_path) \n",
- " \n",
- " dirname = directory_path\n",
- " os.makedirs(dirname, exist_ok=True)\n",
- " \n",
- " #capturing a frame as well as a boolean value representing whether an image was properly opened\n",
- " success,image = vidcap.read()\n",
- " \n",
- " count = 0\n",
- " \n",
- " while success:\n",
- " \n",
- " #this is specifically for foam_segmented.avi\n",
- " if greyscale:\n",
- " image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n",
- " \n",
- " #writing the image to a the directory path that was specified, \n",
- " #if the path specified does not exist then it will be created\n",
- " #this finctionality was added so that the images could be stored in a separate folder\n",
- " #example of output file names: 1.jpg, 2.jpg, 3.jpg, and so on\n",
- " cv2.imwrite(os.path.join(dirname, str(count)+\".jpg\"), image)\n",
- " success,image = vidcap.read()\n",
- " count += 1\n",
- " #All the frames will be added in order\n",
- " cv2.waitKey(1) \n",
- " \n",
- " #releasing the threads\n",
- " vidcap.release()\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "hBfLcvMhh6v7"
- },
- "source": [
- "DEMO FOR THE **avi_to_frames** \n",
- "\n",
- "1. To download a sample avi file that you want to work with, use the following code `urllib.request.urlretrieve('https://www.engr.colostate.edu/me/facil/dynamics/files/drop.avi', 'testing.mp4')` \n",
- "\n",
- "2. After the video has been downloaded `video_to_frames(./testing.mp4, path_to_where_you_want_the_frames, False)` this will create a folder with frames from the video."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "-N-hJD11jJjo"
- },
- "outputs": [],
- "source": [
- "# Making a Video From Frames\n",
- "def frames_to_video(directory_path, fps, width, height):\n",
- " fourcc = cv2.VideoWriter_fourcc(*'mp4v')\n",
- " video = cv2.VideoWriter('video.avi', fourcc, fps, (width, height))\n",
- " num_frames = len([name for name in os.listdir(directory_path) if os.path.isfile(name)])\n",
- "\n",
- " for j in range(num_frames):\n",
- " img = cv2.imread(str(j) + '.jpg')\n",
- " video.write(img)\n",
- "\n",
- " cv2.destroyAllWindows()\n",
- " video.release()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "sIhvc4DplLkE"
- },
- "source": [
- "DEMO FOR THE **frames_to_video** \n",
- "\n",
- "1. We will be working with the frames that we created using `avi_to_frames`. If you have not created those frames feel free to look at the steps above.\n",
- "\n",
- "2. Run the following command (**make the necessary changes in the function call**)`frames_to_video(where_the_frames_are, fps, width, height)`\n",
- "\n",
- "3. The video will show up in the current directory."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "bnfzxPNJeZVS"
- },
- "source": [
- "**The code below will put the image arrays into a list.** This snippet of code utilizes glob but packages like os can also be used."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "mLbqPW7SeJd-"
- },
- "outputs": [],
- "source": [
- "path = glob.glob(\"./*.jpg\")\n",
- "images = []\n",
- "for img in path:\n",
- " n = cv2.imread(img)\n",
- " images.append(n)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "GIq-_h4wdxWM"
- },
- "source": [
- "<b> References:</b>\n",
- "- [Managing Environments](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html)\n",
- "- [Open CV in python](https://pypi.org/project/opencv-python/)\n",
- "- [Colab Button](https://www.youtube.com/watch?v=RoGZIbwzG5w)"
- ]
- }
- ],
- "metadata": {
- "colab": {
- "collapsed_sections": [],
- "name": "Ford_Video_Analysis.ipynb",
- "provenance": []
- },
- "kernelspec": {
- "display_name": "Python 3 (ipykernel)",
- "language": "python",
- "name": "python3"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.9.15"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 4
+ "nbformat": 4,
+ "nbformat_minor": 0
}