FreeClimber
is a Python-based, background-subtracting particle detection algorithm that performs a local linear regression to quantify the vertical velocity of points moving in a common direction.
In lay terms:
-
Background-subtracting: Removes a video's background pixels to improve particle detection.
-
Particle detection: Identifies the x,y,time-coordinates of each spot/marker.
-
Local linear regression: Finds the most linear segment of a position vs. time (velocity) curve, via linear regression over each subset of n-consecutive frames.
-
Vertical velocity: Slope of the most linear segment of the velocity curve, which corresponds with the most consistent increase in mean vertical position across n-frames.
This program was designed initially for assessing climbing performance in a Drosophila (fruit fly) rapid iterative negative geotaxis (RING) assay. However, this program employs several functions that may be of use beyond the initial design and can be accessed from the source code or loaded as a module. This program includes a Graphical User Interface (GUI) for optimizing parameter configurations, and a command line interface for batch processing. This platform has several advantages over over methods and circumvents systemic biases associated with manual methods that are traditionally used to quantify climbing performance in flies.
General programs:
- FFmpeg [4.3.1 ]
FFmpeg will also need to be installed using the following Windows Guide.
Python modules:
- argparse [1.1 ]
- ffmpeg-python [0.2.0 ]
- matplotlib [3.1.3 ]
- numpy [1.18.1]
- pandas [1.0.0 ]
- pip [20.0.2]
- scipy [1.4.1 ]
- trackpy [0.4.2 ]
- wxPython [4.0.4 ]
NOTE: We recommend using with a Python3.6 virtual environment, though it was built with a Python3.7 environment.
We recommend running this package in an Anaconda-based virtual environment. Anaconda can be downloaded here.
Make sure conda
is installed (should return something like conda 4.7.11
):
conda -V
Update conda if needed (press y
when prompted):
conda update conda
Create a Python 3 virtual environment (replace python36
with your name of choice):
conda create -n python36 python=3.6 anaconda
NOTE: See note above about Python 3.6 vs. 3.7
Activate your virtual environment:
conda activate python36
OR (if that doesn't work):
source activate python36
For more details about creating a conda virtual environment, see here. Once the environment is set up and activated, we can install the dependencies listed in the Requirements
section above.
Installation using PyPi
pip install FreeClimber
Download the script files (can be done with git clone
if user is familiar with git
or by directly downloading the .py
files into a single folder)
Cloning the git repository:
cd <folder of interest>
git clone https://github.com/adamspierer/FreeClimber.git
NOTE: As of now, the platform itself is not callable as a module and these steps merely download the dependencies. The script files must be directly referenced when running the program. See our tutorial for usage instructions.
The example
folder contains the video file used in the Tutorial. These files contain the video and resulting data and plot files are also included.
Inputs (by file suffix):
In ./example folder (main test file):
- .h264 - Video file (default Raspberry Pi output, see note below).
- .mov - Video file (more standard video file type).
- .cfg - Configuration file (generated from GUI but can be modified like a text document).
In ./example_other folder (additional test files):
- /ex_1/climbing_1.h264 - Clean background, rig from example folder, with different numbers of flies per vial.
- /ex_2/climbing_2.h264 - Clean background, rig from example folder, with similar numbers of flies per vial, plus wagon-wheel banding effect.
- /ex_3/climbing_3.h264 - Clean background, homemade rig 1, with similar numbers of flies per vial. Same video as gif in overview.
- /ex_4/climbing_4.h264 - Heterogeneous background, homemade rig 2/test tube holder, with similar numbers of flies.
- /ex_5/climbing_5.h264 - Heterogeneous background, homemade rig 3, borderline unusable quality.
Outputs (by file suffix):
- .raw.csv - Data - All spots before filtering. Can be used as input with trackpy for tracking spots.
- .filtered.csv - Data - Spots after filtering, binning, and labeling.
- .slopes.csv - Data - Each vial's slope and best local linear regression score.
- .ROI.png - Plot - First frame of video with a box drawn around the ROI, white dividers corresponding with vial bins, and a cyan box drawn around the ROI post-edge filtering.
- .processed.csv - Plot - Three subplots corresponding with the cropped and grayscaled frame (variable
frame_0
), null background image, and background subtracted image. - .spot_check.png - Plot - Three sets of two subplots. Sets correspond with three filtering parameters: eccentricity (ecc, circularity (0 circular <--> 1 not circular), spot mass, and spot signal. The two subplots for each correspond with a histogram colored according to the spot metric value on the corresponding scatterplot for the x,y location of each spot in the video (all overlayed on the first frame of the video).
- .diagnostic.png - Plot - Overlay scatterplots for the spots identified in the first and last frame of the local linear regression for all spots in the video, the mean-vertical position vs. time plot for each vial (darker section corresponds with most linear), and an overlay scatterplot for all points identified throughout the video.
Other outputs:
- results.csv - Merging of all video .slopes.csv files into a single file.
- log/completed.log - File paths for videos fully processed.
- log/skipped.log - File paths for videos skipped during processing.
Video files were recorded in .h264 format (Raspberry Pi default) and can be incompatibile with certain media players. We recommend using VLC media player, though provide the .mp4 format as well. Nearly all common video file types should be compatible with FreeClimber, though ones that are not can be converted using FFmpeg.
The following is a general overview of the platform usage. For detailed instructions, please see our tutorial page.
Make sure the FreeClimber scripts are downloaded and in a folder on your computer. Navigate to the FreeClimber
directory and type:
cd <path_to_FreeClimber>
To run from the GUI:
Specify a file path to a video after the --video_file
flag.
pythonw ./scripts/FreeClimber_gui.py --video_file ./example/<video_file.suffix>
- Example video_file.suffix:
w1118_m_2_1.h264
To run from the command line:
Specify a file path to a configuration file after the --config_file
flag.
python FreeClimber_main.py --config_file ./example/example.cfg
-
A required
<file>.cfg
is needed to run the command line tool. This file is generated by the GUI, or can be modified from the providedexample.cfg
file. The program will find all specified video files of a common type (file_suffix
) that are nested within the specified parent folder (project_path
), rather than where the configuration file is held. -
There are other options for running the command line version that can be accessed using the
-h
flag. Notably, there are options for processing--process_all
,--process_undone
, and--process_custom
. As the names imply, you can process all, those unprocessed, or a custom list of flies. See the Tutorial page for more information.
FreeClimber_gui.py
- GUI wrapper for the detector.py script.
FreeClimber_main.py
- Command line interface wrapper for the detector.py script.
detector.py
- Contains the detector object, which is important for parsing the video file into a multi-dimensional numpy array (ndarray) and all the functions needed to get the data out.
example.cfg
- A configuration file generated by the GUI or modified by the user from the provided example. It contains the detection parameters needed to run the program.
gather_files.py
- Outputs a list of all files with a given suffix that can be used for customizing the files a user wants to process.
custom.prc
- Output from gather_files.py
, contains file paths that can be used to customize the files FreeClimber processes. File paths from the log/skipped.log
file can also be copied and pasted into a similar file.
We encourage you to to visit our Tutorial page for a more thorough walk-through, description, and various caveats.
0.4.0 - Fixed error with frame cropping and added additional variable compatibility checks.0.3.2 - Release version for Journal of Experimental Biology
This software has only been tested on a Mac OS X (Sierra 10.12.6) but is likely not limited to this OS.
Contributors can fork from the repository and submit a pull request when modifications are ready. Please document the changes you made and any pertinent information that will help in our review of the changes.
We plan to release maintenance updates as needed, though we are unlikely to modify the platform's main functionality.
If you use FreeClimber in your work, please cite: > A.N. Spierer, D. Yoon, CT. Zhu, and DM. Rand. (2020) FreeClimber: Automated quantification of climbing performance in Drosophila. Journal of Experimental Biology. DOI: 10.1242/jeb.229377This work is licensed under the MIT license.
Written by Adam Spierer and Lei Zhuo with special thanks to Brown University's Computational Biology Core for assistance with code review.