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DeepTrack2

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DeepTrack2 is a modular Python library for generating, manipulating, and analyzing image data pipelines for machine learning and experimental imaging.

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<img width="350" src=https://github.com/DeepTrackAI/DeepTrack2/blob/develop/assets/DeepTrack2-logo.png?raw=true>

<h3 align="center">DeepTrack2 - A comprehensive deep learning framework for digital microscopy.</h3>

 <a href="/LICENSE" alt="licence">
 <img src="https://img.shields.io/github/license/DeepTrackAI/DeepTrack2">
 </a>
 <a href="https://badge.fury.io/py/deeptrack">
 <img src="https://badge.fury.io/py/deeptrack.svg" alt="PyPI version">
 </a>
 <a href="https://deeptrackai.github.io/DeepTrack2">
 <img src="https://img.shields.io/badge/docs-available-blue?logo=readthedocs">
 </a>
 <a href="https://badge.fury.io/py/deeptrack">
 <img src="https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12%20%7C%203.13%20%7C%203.14-blue" alt="Python version">
 </a>
 <a href="https://doi.org/10.1063/5.0034891">
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 </a>


 <a href="#installation">Installation</a> •
 <a href="#getting-started">Getting Started</a> •
 <a href="#examples">Examples</a> •
 <a href="#advanced-tutorials">Advanced Tutorials</a> •
 <a href="#developer-tutorials">Developer Tutorials</a> •
 <a href="#cite-us">Cite us</a> •
 <a href="/LICENSE">License</a>

DeepTrack2 is a modular Python library for generating, manipulating, and analyzing image data pipelines for machine learning and digital microscopy.

> TensorFlow Compatibility Notice: 
> DeepTrack2 version 2.0 and subsequent do not support TensorFlow. If you need TensorFlow support, please install the legacy version 1.7.

The following quick-start guide is intended for complete beginners to understand how to use DeepTrack2, from installation to training your first model. Let's get started!

# Installation

DeepTrack2 requires at least python 3.10.

To install DeepTrack2, open a terminal or command prompt and run:
```bash
pip install deeptrack
```
or
```bash
python -m pip install deeptrack
```
This will automatically install the required dependencies.

# Getting Started

Here you find a series of notebooks providing an overview of the core features of DeepTrack2 and how to use them:

- DTGS101 **[Introduction to DeepTrack2](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS101_intro.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS101_intro.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

Overview of how to use DeepTrack2. Creating images combining DeepTrack2 features, extracting properties, and using them to train a neural network.

- DTGS106 **[Simulating Different Image Modalities](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS106_particle_image_modalities.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS106_particle_image_modalities.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

Simulating a spherical particle with different image modalities and generating a movie where this particle diffuses with passive Brownian motion.

- DTGS111 **[Loading Image Files Using Sources](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS111_datafiles.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS111_datafiles.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

Using sources to load image files and to train a neural network.

- DTGS121 **[Tracking a Point Particle with a CNN](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS121_tracking_particle_cnn.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS121_tracking_particle_cnn.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

Tracking a point particle with a convolutional neural network (CNN) using simulated particles resolved through a microscope with aberrations.
 
- DTGS126 **[Characterizing Aberrations with a CNN](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS126_characterizing_aberrations_cnn.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS126_characterizing_aberrations_cnn.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

Characterizing spherical aberrations of an optical device with a convolutional neural network (CNN) using simulated images in the training process.

- DTGS127 **[Characterizing Aberrations with Optuna](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

Characterizing aberrations of an optical device with the optimization framework [`Optuna`](https://optuna.org/).

- DTGS131 **[Tracking Multiple Particles with a U-Net](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS131_tracking_multiple_particles_unet.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS131_tracking_multiple_particles_unet.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

Tracking multiple particles using a U-net trained on simulated images.

- DTGS141 **[Distinguishing Particles with a U-Net](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS141_distinguishing_particles_in_brightfield.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS141_distinguishing_particles_in_brightfield.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

Tracking and distinguishing particles of different sizes in brightfield microscopy using a U-net trained on simulated images.

- DTGS151 **[Unsupervised Object Detection](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS151_unsupervised_object_detection_with_lodestar.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS151_unsupervised_object_detection_with_lodestar.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

Single-shot unsupervised object detection using LodeSTAR.

- DTGS161 **[Fitting Using PyTorch Gradients](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS161_torch_fitting.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS161_torch_fitting.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

Using PyTorch gradients to fit a Gaussian generated by a DeepTrack2 pipeline.

- DTGS171 **[Creating Custom Scatterers](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS171_custom_scatterers.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS171_custom_scatterers.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

Creating custom scatterers of arbitrary shapes.

- DTGS172 **[Simulating Bacteria](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS172_custom_scatterers_bacteria.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS172_custom_scatterers_bacteria.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

Creating custom scatterers in the shape of bacteria.

# Examples

These are examples of how DeepTrack2 can be used on real datasets:

- DTEx211 **[MNIST](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx211_MNIST.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx211_MNIST.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

Training a fully connected neural network to identify handwritten digits using MNIST dataset.

- DTEx212 **Single Particle Tracking**

Tracks experimental videos of a single particle.

<img width="300" src=/assets/SPT-ideal.gif?raw=true>
 <img width="300" src=/assets/SPT-noisy.gif?raw=true>
 
 <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx212_single_particle_tracking.ipynb">
 <img src="https://colab.research.google.com/assets/colab-badge.svg">
 </a>
 <a href="https://doi.org/10.1364/OPTICA.6.000506" alt="DeepTrack article">
 <img src="https://img.shields.io/badge/article-10.1364/OPTICA.6.000506-blue">
 </a> 
 <a href="https://doi.org/10.1063/5.0034891" alt="LodeSTAR article">
 <img src="https://img.shields.io/badge/article-10.1063/5.0034891-blue">
 </a>

- DTEx213 **Multi-Particle Tracking** 
 
 Detecting quantum dots in a low SNR image.

<img width="300" src=/assets/MPT-qdots_1.png?raw=true>

- DTEx214 **Particle Feature Extraction**
 
  Extracting the radius and refractive index of particles.

- DTEx215 **Cell Counting**

Counting the number of cells in fluorescence images.

- DTEx216 **3D Multi-Particle tracking**

Tracking multiple particles in 3D for holography.

- DTEx217 **GAN image generation**

Using a GAN to create cell image from masks.

Specific examples for label-free particle tracking using **LodeSTAR**:

- DTEx231A **LodeSTAR to Detect Particles**

<img width="600" src=/assets/MPT-packed.gif?raw=true>
 
 <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx231A_LodeSTAR_template.ipynb">
 <img src="https://colab.research.google.com/assets/colab-badge.svg">
 </a>
 <a href="https://doi.org/10.1038/s41467-022-35004-y" alt="Article LodeSTAR">
 <img src="https://img.shields.io/badge/article-10.1038%2Fs41467--022--35004--y-blue">
 </a>

- DTEx231B **LodeSTAR to Detect Particles of Various Shapes**

- DTEx231C **LodeSTAR to Measure the Mass of Particles in Holography**

- DTEx231D **LodeSTAR to Detect the Cells in the BF-C2DT-HSC Dataset**

- DTEx231E **LodeSTAR to Detect the Cells in the Fluo-C2DT-Huh7 Dataset** 
 
- DTEx231F **LodeSTAR to Detect the Cells in the PhC-C2DT-PSC Dataset** 
 
- DTEx231G **LodeSTAR to Detect Plankton** 
 
- DTEx231H **LodeSTAR to Detect Particles in 3D Holography**

- DTEx231I **LodeSTAR Measure the Mass of Simulated Particles**
  
- DTEx231J **LodeSTAR to Measure the Mass of Cells**

Specific examples for graph-neural-network-based particle linking and trace characterization using **MAGIK**:

- DTEx241A **MAGIK to Trace Migrating Cells**

<img width="600" src=/assets/Tracing.gif?raw=true>
 
 <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx241A_MAGIK_cell_migration_analysis.ipynb">
 <img src="https://colab.research.google.com/assets/colab-badge.svg">
 </a>
 <a href="https://doi.org/10.1038/s42256-022-00595-0" alt="Article MAGIK">
 <img src="https://img.shields.io/badge/article-10.1038/s42256--022--00595--0-blue">
 </a>

- DTEx241B **MAGIK to Track HeLa Cells**

# Advanced Tutorials

This section provides a list of advanced tutorials. The primary focus of these tutorials is to demonstrate the functionalities of individual modules and how they work in relative isolation, helping to provide a better understanding of them and their roles in DeepTrack2.

- DTAT301 **[deeptrack.features](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT301_features.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT301_features.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

- DTAT311 **[deeptrack.properties](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT311_properties.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT311_properties.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

- DTAT321 **[deeptrack.properties](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT321_wrappers.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT321_wrappers.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

- DTAT331 **[deeptrack.sequences](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT331_sequences.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT331_sequences.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

- DTAT351 **[deeptrack.utils](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT351_utils.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT351_utils.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

- DTAT353 **[deeptrack.statistics](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT353_statistics.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT353_statistics.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>

- DTAT355 **[deeptrack.types](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT_387_types.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT_387_types.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>

- DTAT357 **[deeptrack.elementwise](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT357_elementwise.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT357_elementwise.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>

- DTAT361 **[deeptrack.sources.base](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT361_sources.base.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT361_sources.base.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>

- DTAT362 **[deeptrack.sources.folder](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT362_sources.folder.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT362_sources.folder.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>

- DTAT366 **[deeptrack.pytorch.data](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT366_pytorch.features.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT366_pytorch.features.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>

- DTAT367 **[deeptrack.pytorch.features](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT367_pytorch.data.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT367_pytorch.data.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>

- DTAT369 **[deeptrack.extras.radialcenter](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT369_extras.radialcenter.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT369_extras.radialcenter.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>

- DTAT391 **[deeptrack.backend.core](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT391_backend.core.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT391_backend.core.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
 
- DTAT392 **[deeptrack.backend.pint_definition](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT392_backend.pint_definition.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT392_backend.pint_definition.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
 
- DTAT393 **[deeptrack.backend.units](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT393_backend.units.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT393_backend.units.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
 
- DTAT394 **[deeptrack.backend.polynomials](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT394_backend.polynomials.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT394_backend.polynomials.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
 
- DTAT395 **[deeptrack.backend.mie](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT395_backend.mie.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT395_backend.mie.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
 
- DTAT396 **[deeptrack.backend._config](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT396_backend._config.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT396_backend._config.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>

## Advanced Tutorials for Optical Microscopy

- DTATo10 **[deeptrack.optical.scatterers](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo10_scatterers.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo10_scatterers.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

- DTATo20 **[deeptrack.optical.optics](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo20_optics.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo20_optics.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

- DTATo30 **[deeptrack.optical.holography](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo30_holography.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo30_holography.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>

- DTATo40 **[deeptrack.optical.aberrations](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo40_aberrations.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo40_aberrations.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

- DTATo50 **[deeptrack.optical.noises](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo50_noises.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo50_noises.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

- DTATo60 **[deeptrack.optical.augmentations](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo60_augmentations.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo60_augmentations.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

- DTATo90 **[deeptrack.optical.math](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo90_math.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo90_math.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

# Developer Tutorials

Here you will find a series of notebooks tailored for DeepTrack2's developers:

- DTDV401 **[Overview of Code Base](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/4-developers/DTDV401_overview.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/4-developers/DTDV401_overview.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

- DTDV411 **[Style Guide](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/4-developers/DTDV411_style.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/4-developers/DTDV411_style.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

- DTDV421 **[Using Different Computational Backends](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/4-developers/DTDV421_backends.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/4-developers/DTDV421_backends.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>

# Documentation

The detailed documentation of DeepTrack2 is available at the following link: [https://deeptrackai.github.io/DeepTrack2](https://deeptrackai.github.io/DeepTrack2)

# Cite us!
If you use DeepTrack2 in your project, please cite us:

<https://pubs.aip.org/aip/apr/article/8/1/011310/238663>
```
"Quantitative Digital Microscopy with Deep Learning."
Benjamin Midtvedt, Saga Helgadottir, Aykut Argun, Jesús Pineda, Daniel Midtvedt & Giovanni Volpe.
Applied Physics Reviews, volume 8, article number 011310 (2021).
```

DeepTrack2

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