bwprice/butterfly-wings

Automated butterfly wing length measurement

Butterfly Wings

Analyzing images of butterflies and measuring their wing lengths. Using binarization techniques and calculating the resolution of ruler ticks, we read in images of butterflies and output the millimeter lengths of their wings.

Usage

$ python pipeline.py -p -i [input directory or image path] -o [output directory] -csv [csv output file path]

The pipeline script combines four modules to analyze an image: ruler detection, binarization, tracing, and final measurement. These modules are located in /butterfly. Python module requirements are listed in requirements.txt.

Run the pipeline.py file with the arguments to read in raw images and output result images and .csv file with the measurements.

The results are cached in cachedir so that if the same methods are re-run with the same inputs, the computation will simply be retrieved from memory instead of being recomputed. Delete cachedir to remove the cache and to recompute all results. If the source files for any part of the pipeline are tweaked, then results will be recomputed automatically.

Options

• -p, --plot : This flag is used to generate output images. This can be ommitted to not plot any images (Image outputs can be ommitted to improve runtime or save space.)
• -pp, --detailed_plot : Outputs detailed plots to help debugging. Included in the detailed plot are the various points of interest of the image marked in seperate plots, as well as the method we are using to measure the pixels per millimeter on the ruler (Again, can be ommitted to improve runtime and save space). Example detailed result:

• -i, --input : A single image input or a directory of images to be analyzed. (Default is raw_images).
• -o, --output_folder : The output directory in which the result images will be outputted. (Default is outputs).
• -s, --stage : The stage which to run the pipeline until. Must be one of ['ruler_detection', 'binarization', 'measurements']. Pipeline runs to measurement stage by default (running to completion). Running the pipeline and stopping at an earlier stage can be useful for debugging.
• -csv, --path_csv : Path of .csv file for the measurement results. (Default is results.csv).
• -dpi : Optional argument to specify resolution of the output image. (Default is 300.)
• -g, --grabcut : Use OpenCV's grabcut method in order to improve binarization on blue butterflies.

Example

Example data can be found at github.com/machine-shop/butterfly-wings-data. For this example, clone the repository alongside butterfly-wings.

git clone https://github.com/machine-shop/butterfly-wings.git
git clone https://github.com/machine-shop/butterfly-wings-data.git

Resulting files:

/butterfly-wings
    ...
    pipeline.py
    ...
/butterfly-wings-data
    image1.jpg
    image2.jpg
    ...

Running this command

$ python pipeline.py -p -i ../butterfly-wings-data -o ../test_output -csv ../test_output/results.csv

in /butterfly-wings will run the pipeline on the example data in /butterfly-wings-data. The file locations should look like this:

/butterfly-wings
    ...
    pipeline.py
    ...
/butterfly-wings-data
    image1.jpg
    image2.jpg
    ...
/test_output
    image1.jpg (result image for image1.jpg)
    image2.jpg
    ...
    results.csv

Miscellaneous

The testing suite can be run with PYTHONPATH=. pytest from /butterfly-wings.

Result Plotting

result_plotting.py is a script that generates a histogram of differences between actual measurements and predicted measurements. This is useful for debugging and evaluating accuracy. This can be used in isolation from the main pipeline, and simply takes in the predicted results.csv from the pipeline and either an .xlsx file or .csv file with actual measurements.

Usage

python result_plotting.py -a "h_comma_wing_lengths.xlsx" -n "full name" -l "Left" -r "Right"

Apart from outputting a plot of the differences, it can also output a comparison.csv with all differences between predicted and actual measurements, and/or a outliers.csv with only measurement differences from outliers. It can also copy outlier images to a outliers/ folder, for easier debugging by rerunning the pipeline on these outlier images.

Options

• -a, --actual : File path of either Excel .xlsx file or .csv file containing the actual measurements.
• -n, --name : Name of column in actual file that contains the image names for each measurement.
• -l, --left : Name of column in actual file that contains the name of left wing measurements.
• -r, --right : Name of column in actual file that contains the name of right wing measurements.
• -p, --predicted : File path of .csv predictions outputted by out pipeline. results.csv by default.
• -c, --comparison : If specified, will output a comparison.csv file containing all measurements and the differences.
• -o, --outliers : If specified, will output a outliers.csv file containing only measurements that are deemed outliers.
• -sd, --sd : By default, the SD to determine an outlier is +/- 2 SD's away from the average measurement. If specified, you can use something else.
• -co, --copy_outliers : Specify a folder where the outlier images are from, and copy any outlier images to a outliers/ folder in the current directory.

Example

Example files:

/"Measured_images_Data_H.comma"
    BMNHE_1354218.JPG
    ...
    ...
/butterfly-wings
    result_plotting.py
    h_comma_wing_lengths.xlsx
    results.csv

h_comma_wing_lengths.xlsx has these columns:

full name	...	Right	Left
BMNHE_1354218.JPG	...	15.11	15.288
...	...	...	...

Thus, we will specify -n "full name", -l "Left", -r "Right".

We know what results.csv looks like (since it is output by the pipeline).

We also want to output both the comparison.csv and outliers.csv table, so we will specify -c and -o, and we also want to copy outliers from the images folder Measured_images_Data_H.comma, so we will do -co "../Measured_images_Data_H.comma". We also want to define an outlier as a measurement +-1.75 SD's from the actual measurement, so we well specify -sd 1.75. Thus the usage is:

python result_plotting.py -a "h_comma_wing_lengths.xlsx" -n "full name" -l "Left" -r "Right" -c -o -co "../Measured_images_Data_H.comma" -sd 1.75 

File results:

/butterfly-wings
    result_plotting.py
    h_comma_wing_lengths.xlsx
    results.csv
    ...
    result_plot.png
    comparison.csv
    outliers.csv
    /outliers
        BMNHE_1354218.JPG (an outlier image)
        ...