diff --git a/Video-Image-Data-Tutorial/Ford_Video_Analysis.ipynb b/Video-Image-Data-Tutorial/Ford_Video_Analysis.ipynb
index c65289a81d9fb1e5b632d9795fcad66fcf22e60c..acbd75012ff4bdb5f7b487246af4482fcac89cc7 100644
--- a/Video-Image-Data-Tutorial/Ford_Video_Analysis.ipynb
+++ b/Video-Image-Data-Tutorial/Ford_Video_Analysis.ipynb
@@ -1,4 +1,5 @@
{
+<<<<<<< HEAD
"cells": [
{
"cell_type": "markdown",
@@ -230,4 +231,248 @@
},
"nbformat": 4,
"nbformat_minor": 0
+=======
+ "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": 1,
+ "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 `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": 2,
+ "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": 3,
+ "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)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "**Comments:**\n",
+ "\n",
+ "The videos is not working "
+ ]
+ }
+ ],
+ "metadata": {
+ "colab": {
+ "collapsed_sections": [],
+ "name": "Ford_Video_Analysis.ipynb",
+ "provenance": []
+ },
+ "kernelspec": {
+ "display_name": "Python 3",
+ "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": "3.8.8"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+>>>>>>> 5c328fa (this is a testing comment)
}