{
    "info": {
        "author": "Adam Spannbauer",
        "author_email": "spannbaueradam@gmail.com",
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        "classifiers": [
            "License :: OSI Approved :: MIT License",
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            "Programming Language :: Python :: 3"
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        "description": "# Python Video Stabilization <img src='https://s3.amazonaws.com/python-vidstab/logo/vidstab_logo_hex.png' width=125 align='right'/>\n\n[![Build Status](https://travis-ci.org/AdamSpannbauer/python_video_stab.svg?branch=master)](https://travis-ci.org/AdamSpannbauer/python_video_stab)\n[![codecov](https://codecov.io/gh/AdamSpannbauer/python_video_stab/branch/master/graph/badge.svg)](https://codecov.io/gh/AdamSpannbauer/python_video_stab)\n[![Maintainability](https://api.codeclimate.com/v1/badges/f3a17d211a2a437d21b1/maintainability)](https://codeclimate.com/github/AdamSpannbauer/python_video_stab/maintainability)\n[![PyPi version](https://pypip.in/v/vidstab/badge.png)](https://pypi.org/project/vidstab/)\n[![Last Commit](https://img.shields.io/github/last-commit/AdamSpannbauer/python_video_stab.svg)](https://github.com/AdamSpannbauer/python_video_stab/commits/master)\n[![Downloads](https://pepy.tech/badge/vidstab)](https://pepy.tech/project/vidstab)\n\n Python video stabilization using OpenCV. Full [searchable documentation here](https://adamspannbauer.github.io/python_video_stab).\n\n This module contains a single class (`VidStab`) used for video stabilization. This class is based on the work presented by Nghia Ho in [SIMPLE VIDEO STABILIZATION USING OPENCV](http://nghiaho.com/?p=2093). The foundation code was found in a comment on Nghia Ho's post by the commenter with username koala.\n\n Input                           |  Output\n:-------------------------------:|:-------------------------:\n![](https://s3.amazonaws.com/python-vidstab/readme/input_ostrich.gif)    |  ![](https://s3.amazonaws.com/python-vidstab/readme/stable_ostrich.gif)\n\n*[Video](https://www.youtube.com/watch?v=9pypPqbV_GM) used with permission from [HappyLiving](https://www.facebook.com/happylivinginfl/)*\n\n## Contents:\n1. [Installation](#installation)\n   * [Install `vidstab` without installing OpenCV](#install-vidstab-without-installing-opencv)\n   * [Install vidstab & OpenCV](#install-vidstab-opencv)   \n2. [Basic Usage](#basic-usage)\n   * [Using from command line](#using-from-command-line)\n   * [Using VidStab class](#using-vidstab-class)\n3. [Advanced Usage](#advanced-usage)\n   * [Plotting frame to frame transformations](#plotting-frame-to-frame-transformations)\n   * [Using borders](#using-borders)\n   * [Using Frame Layering](#using-frame-layering)\n   * [Stabilizing a frame at a time](#stabilizing-a-frame-at-a-time)\n   * [Working with live video](#working-with-live-video)\n   * [Transform File Writing & Reading](#transform-file-writing--reading)\n\n## Installation\n\n> ```diff\n> + Please report issues if you install/try to install and run into problems!\n> ```\n\n### Install `vidstab` without installing OpenCV\n\nIf you've already built OpenCV with python bindings on your machine it is recommended to install `vidstab` without installing the pypi versions of OpenCV.  The `opencv-python` python module can cause issues if you've already built OpenCV from source in your environment.\n\nThe below commands will install `vidstab` without OpenCV included.\n\n#### From PyPi\n\n```bash\npip install vidstab\n```\n\n#### From GitHub\n\n```bash\npip install git+https://github.com/AdamSpannbauer/python_video_stab.git\n```\n\n### Install `vidstab` & OpenCV\n\nIf you don't have OpenCV installed already there are a couple options.  \n\n1. You can build OpenCV using one of the great online tutorials from [PyImageSearch](https://www.pyimagesearch.com/), [LearnOpenCV](https://www.learnopencv.com/), or [OpenCV](https://docs.opencv.org/3.0-beta/doc/py_tutorials/py_setup/py_table_of_contents_setup/py_table_of_contents_setup.html#py-table-of-content-setup) themselves.  When building from source you have more options (e.g. [platform optimization](https://www.pyimagesearch.com/2017/10/09/optimizing-opencv-on-the-raspberry-pi/)), but more responsibility.  Once installed you can use the pip install command shown above.\n2. You can install a pre-built distribution of OpenCV from pypi as a dependency for `vidstab` (see command below)\n\nThe below commands will install `vidstab` with `opencv-contrib-python` as dependencies.\n\n#### From PyPi\n\n```bash\npip install vidstab[cv2]\n```\n\n#### From Github\n\n```bash\n pip install -e git+https://github.com/AdamSpannbauer/python_video_stab.git#egg=vidstab[cv2]\n```\n\n## Basic usage\n\nThe `VidStab` class can be used as a command line script or in your own custom python code.\n\n### Using from command line\n\n```bash\n# Using defaults\npython3 -m vidstab --input input_video.mov --output stable_video.avi\n```\n\n```bash\n# Using a specific keypoint detector\npython3 -m vidstab -i input_video.mov -o stable_video.avi -k GFTT\n```\n\n### Using `VidStab` class\n\n```python\nfrom vidstab import VidStab\n\n# Using defaults\nstabilizer = VidStab()\nstabilizer.stabilize(input_path='input_video.mov', output_path='stable_video.avi')\n\n# Using a specific keypoint detector\nstabilizer = VidStab(kp_method='ORB')\nstabilizer.stabilize(input_path='input_video.mp4', output_path='stable_video.avi')\n\n# Using a specific keypoint detector and customizing keypoint parameters\nstabilizer = VidStab(kp_method='FAST', threshold=42, nonmaxSuppression=False)\nstabilizer.stabilize(input_path='input_video.mov', output_path='stable_video.avi')\n```\n\n## Advanced usage\n\n### Plotting frame to frame transformations\n\n```python\nfrom vidstab import VidStab\nimport matplotlib.pyplot as plt\n\nstabilizer = VidStab()\nstabilizer.stabilize(input_path='input_video.mov', output_path='stable_video.avi')\n\nstabilizer.plot_trajectory()\nplt.show()\n\nstabilizer.plot_transforms()\nplt.show()\n```\n\nTrajectories                     |  Transforms\n:-------------------------------:|:-------------------------:\n![](https://s3.amazonaws.com/python-vidstab/readme/trajectory_plot.png)  |  ![](https://s3.amazonaws.com/python-vidstab/readme/transforms_plot.png)\n\n### Using borders\n\n```python\nfrom vidstab import VidStab\n\nstabilizer = VidStab()\n\n# black borders\nstabilizer.stabilize(input_path='input_video.mov', \n                     output_path='stable_video.avi', \n                     border_type='black')\nstabilizer.stabilize(input_path='input_video.mov', \n                     output_path='wide_stable_video.avi', \n                     border_type='black', \n                     border_size=100)\n\n# filled in borders\nstabilizer.stabilize(input_path='input_video.mov', \n                     output_path='ref_stable_video.avi', \n                     border_type='reflect')\nstabilizer.stabilize(input_path='input_video.mov', \n                     output_path='rep_stable_video.avi', \n                     border_type='replicate')\n```\n\n<table>\n  <tr>\n    <td><p align='center'><code>border_size=0</code></p></td>\n    <td><p align='center'><code>border_size=100</code></p></td>\n  </tr>\n  <tr>\n    <td><p align='center'><img src='https://s3.amazonaws.com/python-vidstab/readme/stable_ostrich.gif'></p></td>\n    <td><p align='center'><img src='https://s3.amazonaws.com/python-vidstab/readme/wide_stable_ostrich.gif'></p></td>\n  </tr>\n</table>\n\n`border_type='reflect'`                 |  `border_type='replicate'`\n:--------------------------------------:|:-------------------------:\n![](https://s3.amazonaws.com/python-vidstab/readme/reflect_stable_ostrich.gif)  |  ![](https://s3.amazonaws.com/python-vidstab/readme/replicate_stable_ostrich.gif)\n\n*[Video](https://www.youtube.com/watch?v=9pypPqbV_GM) used with permission from [HappyLiving](https://www.facebook.com/happylivinginfl/)*\n\n### Using Frame Layering\n\n```python\nfrom vidstab import VidStab, layer_overlay, layer_blend\n\n# init vid stabilizer\nstabilizer = VidStab()\n\n# use vidstab.layer_overlay for generating a trail effect\nstabilizer.stabilize(input_path=INPUT_VIDEO_PATH,\n                     output_path='trail_stable_video.avi',\n                     border_type='black',\n                     border_size=100,\n                     layer_func=layer_overlay)\n\n\n# create custom overlay function\n# here we use vidstab.layer_blend with custom alpha\n#   layer_blend will generate a fading trail effect with some motion blur\ndef layer_custom(foreground, background):\n    return layer_blend(foreground, background, foreground_alpha=.8)\n\n# use custom overlay function\nstabilizer.stabilize(input_path=INPUT_VIDEO_PATH,\n                     output_path='blend_stable_video.avi',\n                     border_type='black',\n                     border_size=100,\n                     layer_func=layer_custom)\n```\n\n`layer_func=vidstab.layer_overlay`     |  `layer_func=vidstab.layer_blend`\n:--------------------------------------:|:-------------------------:\n![](https://s3.amazonaws.com/python-vidstab/readme/trail_stable_ostrich.gif)  |  ![](https://s3.amazonaws.com/python-vidstab/readme/blend_stable_ostrich.gif)\n\n*[Video](https://www.youtube.com/watch?v=9pypPqbV_GM) used with permission from [HappyLiving](https://www.facebook.com/happylivinginfl/)*\n\n\n### Automatic border sizing\n\n```python\nfrom vidstab import VidStab, layer_overlay\n\nstabilizer = VidStab()\n\nstabilizer.stabilize(input_path=INPUT_VIDEO_PATH,\n                     output_path='auto_border_stable_video.avi', \n                     border_size='auto',\n                     # frame layering to show performance of auto sizing\n                     layer_func=layer_overlay)\n```\n\n<p align='center'>\n  <img width='45%' src='https://s3.amazonaws.com/python-vidstab/readme/auto_border_stable_ostrich.gif'>\n</p>\n\n\n### Stabilizing a frame at a time\n\nThe method `VidStab.stabilize_frame()` can accept `numpy` arrays to allow stabilization processing a frame at a time.\nThis can allow pre/post processing for each frame to be stabilized; see examples below.\n\n#### Simplest form\n\n```python\nfrom vidstab.VidStab import VidStab\n\nstabilizer = VidStab()\nvidcap = cv2.VideoCapture('input_video.mov')\n\nwhile True:\n     grabbed_frame, frame = vidcap.read()\n\n     if frame is not None:\n        # Perform any pre-processing of frame before stabilization here\n        pass\n\n     # Pass frame to stabilizer even if frame is None\n     # stabilized_frame will be an all black frame until iteration 30\n     stabilized_frame = stabilizer.stabilize_frame(input_frame=frame,\n                                                   smoothing_window=30)\n     if stabilized_frame is None:\n         # There are no more frames available to stabilize\n         break\n\n     # Perform any post-processing of stabilized frame here\n     pass\n```\n\n#### Example with object tracking\n\n```python\nimport os\nimport cv2\nfrom vidstab import VidStab, layer_overlay, download_ostrich_video\n\n# Download test video to stabilize\nif not os.path.isfile(\"ostrich.mp4\"):\n    download_ostrich_video(\"ostrich.mp4\")\n\n# Initialize object tracker, stabilizer, and video reader\nobject_tracker = cv2.TrackerCSRT_create()\nstabilizer = VidStab()\nvidcap = cv2.VideoCapture(\"ostrich.mp4\")\n\n# Initialize bounding box for drawing rectangle around tracked object\nobject_bounding_box = None\n\nwhile True:\n    grabbed_frame, frame = vidcap.read()\n\n    # Pass frame to stabilizer even if frame is None\n    stabilized_frame = stabilizer.stabilize_frame(input_frame=frame, border_size=50)\n\n    # If stabilized_frame is None then there are no frames left to process\n    if stabilized_frame is None:\n        break\n\n    # Draw rectangle around tracked object if tracking has started\n    if object_bounding_box is not None:\n        success, object_bounding_box = object_tracker.update(stabilized_frame)\n\n        if success:\n            (x, y, w, h) = [int(v) for v in object_bounding_box]\n            cv2.rectangle(stabilized_frame, (x, y), (x + w, y + h),\n                          (0, 255, 0), 2)\n\n    # Display stabilized output\n    cv2.imshow('Frame', stabilized_frame)\n\n    key = cv2.waitKey(5)\n\n    # Select ROI for tracking and begin object tracking\n    # Non-zero frame indicates stabilization process is warmed up\n    if stabilized_frame.sum() > 0 and object_bounding_box is None:\n        object_bounding_box = cv2.selectROI(\"Frame\",\n                                            stabilized_frame,\n                                            fromCenter=False,\n                                            showCrosshair=True)\n        object_tracker.init(stabilized_frame, object_bounding_box)\n    elif key == 27:\n        break\n\nvidcap.release()\ncv2.destroyAllWindows()\n```\n\n<p align='center'>\n  <img width='50%' src='https://s3.amazonaws.com/python-vidstab/readme/obj_tracking_vidstab_1.gif'>\n</p>\n\n\n### Working with live video\n\nThe `VidStab` class can also process live video streams.  The underlying video reader is `cv2.VideoCapture`([documentation](https://docs.opencv.org/3.0-beta/doc/py_tutorials/py_gui/py_video_display/py_video_display.html)).\nThe relevant snippet from the documentation for stabilizing live video is:\n\n> *Its argument can be either the device index or the name of a video file. Device index is just the number to specify which camera. Normally one camera will be connected (as in my case). So I simply pass 0 (or -1). You can select the second camera by passing 1 and so on.*\n\nThe `input_path` argument of the `VidStab.stabilize` method can accept integers that will be passed directly to `cv2.VideoCapture` as a device index.  You can also pass a device index to the `--input` argument for command line usage.\n\nOne notable difference between live feeds and video files is that webcam footage does not have a definite end point.\nThe options for ending a live video stabilization are to set the max length using the `max_frames` argument or to manually stop the process by pressing the <kbd>Esc</kbd> key or the <kbd>Q</kbd> key.\nIf `max_frames` is not provided then no progress bar can be displayed for live video stabilization processes.\n\n#### Example\n\n```python\nfrom vidstab import VidStab\n\nstabilizer = VidStab()\nstabilizer.stabilize(input_path=0,\n                     output_path='stable_webcam.avi',\n                     max_frames=1000,\n                     playback=True)\n```\n\n<p align='center'>\n  <img width='50%' src='https://s3.amazonaws.com/python-vidstab/readme/webcam_stable.gif'>\n</p>\n\n### Transform file writing & reading \n\n#### Generating and saving transforms to file\n\n```python\nimport numpy as np\nfrom vidstab import VidStab, download_ostrich_video\n\n# Download video if needed\ndownload_ostrich_video(INPUT_VIDEO_PATH)\n\n# Generate transforms and save to TRANSFORMATIONS_PATH as csv (no headers)\nstabilizer = VidStab()\nstabilizer.gen_transforms(INPUT_VIDEO_PATH)\nnp.savetxt(TRANSFORMATIONS_PATH, stabilizer.transforms, delimiter=',')\n```\n\nFile at `TRANSFORMATIONS_PATH` is of the form shown below.  The 3 columns represent delta x, delta y, and delta angle respectively.\n\n```\n-9.249733913760086068e+01,2.953221378387767970e+01,-2.875918912994855636e-02\n-8.801434576214279559e+01,2.741942225927152776e+01,-2.715232319470826938e-02\n```\n\n#### Reading and using transforms from file\n\nBelow example reads a file of transforms and applies to an arbitrary video.  The transform file is of the form shown in [above section](#generating-and-saving-transforms-to-file).\n\n```python\nimport numpy as np\nfrom vidstab import VidStab\n\n# Read in csv transform data, of form (delta x, delta y, delta angle):\ntransforms = np.loadtxt(TRANSFORMATIONS_PATH, delimiter=',')\n\n# Create stabilizer and supply numpy array of transforms\nstabilizer = VidStab()\nstabilizer.transforms = transforms\n\n# Apply stabilizing transforms to INPUT_VIDEO_PATH and save to OUTPUT_VIDEO_PATH\nstabilizer.apply_transforms(INPUT_VIDEO_PATH, OUTPUT_VIDEO_PATH)\n```\n\n\n",
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