Holo1

Images and Python code for holographic microscope. This repository is dedicated to our work on an inexpensive digital in-line holographic microscope made from a laser, image sensor and Raspberry Pi. Construction instructions can be found here in the youtube video, youtu.be/zqBVLydhUBg "Microscope Kit V3" (2020). This project is supported by the Center for Cellular Construction (ccc.ucsf.edu) and the National Science Foundation under Grant No. DBI-1548297. Disclaimer: Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

goldHolo.zip

64 cropped raw images of plankton and microfiber from dryer lint

holoVideoReco

Interactive Holographic Reconstruction with Tkinter Interface Mouse and button driven GUI to opens a video, view frame-by-frame, selecting area to crop and reconstruct

reco.py

Supporting functions for holoVideoReco program, including reconstruction

Detect.py

Main program to detect, track and extract morphological features of plankton. Requires Feature_12.py, Track_3.py, and Common_4.py.

To detect, track and extract features of plankton:

1. Edit Common_4.py for the video file you want to process, the file name to store detection, tracking and features, and operating parameters you desire.
2. Run Dect_10.py.

Feature.py

Calculates shape, texture, grayscale histogram, local binary patterns, and several moment features of an object.

darkPixReco.py

Detects plankton in video, optimized for detecting tiny plankton that produces fringes with low or no contrast center, making detection very difficult Create composite image by selecting darkets pixel of several Z reconstructions.

3D_Cluster_Plot.py

Displays scatter plot of area, texture and aspect ratio. Uses clusterConstants for program constants.

ViewFeatures.py

Displays scatter plot of area, texture and aspect ratio of all objects for all frames, while viewing video. Uses blep1.mp4 video and featureFile.csv

Cluster.py

Clusters objects in video blep1.mp4 into 5 clusters using features (featureFile_2.csv) and cluster file names (clusterFile_2.csv)

ConfusionMatrix.py

Displays normalized confusion matrix and accuracy calculation for feature dataset FeaturesForConfusionMatrix.csv

piClassifier.pdf

A paper that evaluates the performance of 13 classifiers and 9 feature sets on 9 classes of plankton running on a Raspberry Pi 3 using images from a lensless microscope.

ACKNOWLEDGMENTS

Code written by Thomas G. Zimmerman, IBM Research-Almaden and Center for Cellular Construction, except Holgraphic Reconstruction Algorithms by Nick Antipac, UC Berkeley and Daniel Elnatan, UCSF, and Features.py written by Vito Pastore and Thomas G. Zimmerman. This work is funded by the National Science Foundation (NSF) grant No. DBI-1548297, Center for Cellular Construction. Disclaimer: Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.