Merge branch 'main' into feature/thresholding

.github/CODEOWNERS

@@ -0,0 +1 @@
+*   @hughes036 @yrkim98 @saeliddp

.github/ISSUE_TEMPLATE/bug_report.md

@@ -0,0 +1,36 @@
+---
+name: Bug report
+about: Create a report to help us improve
+title: ''
+labels: ''
+assignees: ''
+
+---
+
+**Describe the bug**
+A clear and concise description of what the bug is.
+
+**To Reproduce**
+Steps to reproduce the behavior:
+1. Go to '...'
+2. Click on '....'
+3. Scroll down to '....'
+4. See error
+
+**Expected behavior**
+A clear and concise description of what you expected to happen.
+
+**Screenshots**
+If applicable, add screenshots to help explain your problem.
+
+**Describe your data (image format, 2D /3D etc.)**
+
+**Environment (please complete the following information):**
+ - OS: [e.g. iOS8.1]
+ - Plugin Version [e.g. 0.16.1]
+ - PyTorch version [e.g. 2..4.0]
+ - GPU? [e.g. yes / no]
+ - CUDA version [e.g. 10.0]
+
+**Additional context**
+Add any other context about the problem here.

.github/ISSUE_TEMPLATE/config.yml

@@ -0,0 +1 @@
+blank_issues_enabled: false

.github/ISSUE_TEMPLATE/feature_request.md

@@ -0,0 +1,23 @@
+---
+name: Feature request
+about: Suggest an idea for this project
+title: ''
+labels: needs prioritization, Requests
+assignees: ''
+
+---
+
+**Please describe the problem that needs to be solved by this feature**
+A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
+
+**How important is this feature to you? (Software team will re-prioritize all tickets based on current workload)**
+Critical, high priority, medium priority, or low priority.
+
+**Describe the solution you'd like**
+A clear and concise description of what you want to happen.
+
+**Describe alternatives you've considered**
+A clear and concise description of any alternative solutions or features you've considered.
+
+**Additional context**
+Add any other context or screenshots about the feature request here.

.github/pull_request_template.md

@@ -0,0 +1,11 @@
+## Purpose
+<!-- What issue does the PR address? -->
+
+## Changes
+<!-- What is the effect of the PR? -->
+
+## Testing
+<!-- How were these changes tested? Any manual tests? -->
+
+## How to review
+<!-- Where should reviewers look? -->

.github/workflows/auto_add_bug_tickets_to_project.yaml

@@ -0,0 +1,17 @@
+name: Auto add bug tickets to project board
+
+on:
+  issues:
+    types: [opened]
+
+jobs:
+  add_to_project:
+    runs-on: ubuntu-latest
+    if: contains(github.event.issue.labels.*.name, 'Bug Reports')
+    steps:
+      - name: Add bug issue to project
+        uses: actions/add-to-project@v1
+        with:
+          project-url: https://github.com/orgs/AllenCell/projects/10
+          content-id: ${{ github.event.issue.node_id }}
+          column-name: Todo

.github/workflows/auto_add_dev_tickets_to_project.yaml

@@ -0,0 +1,19 @@
+name: Auto add dev tickets to project board
+
+on:
+  issues:
+    types: [opened]
+
+jobs:
+  add_to_project:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check labels and add to project
+        if: |
+          !contains(github.event.issue.labels.*.name, 'Requests') &&
+          !contains(github.event.issue.labels.*.name, 'Bug Reports')
+        uses: actions/add-to-project@v1
+        with:
+          project-url: https://github.com/orgs/AllenCell/projects/7
+          content-id: ${{ github.event.issue.node_id }}
+          column-name: Backlog

.github/workflows/auto_add_feature_request_to_project.yaml

@@ -0,0 +1,17 @@
+name: Auto-add feature requests and bug reports to project board
+
+on:
+  issues:
+    types: [opened]
+
+jobs:
+  add_to_project:
+    runs-on: ubuntu-latest
+    if: contains(github.event.issue.labels.*.name, 'Requests')
+    steps:
+      - name: Add issue to project
+        uses: actions/add-to-project@v1
+        with:
+          project-url: https://github.com/orgs/AllenCell/projects/9
+          content-id: ${{ github.event.issue.node_id }}
+          column-name: Scoping

.github/workflows/bump_version_pr.yaml

@@ -14,7 +14,7 @@ on:
           - major
           - minor
           - patch
-          - dev
+          - rc
 
 jobs:
   publish:

.github/workflows/test_lint_pr.yaml

@@ -16,4 +16,4 @@ jobs:
     strategy:
       matrix:
         os: [macos-latest, windows-latest]
-        python-version: ["3.10"]
+        python-version: ["3.9", "3.10"]

.github/workflows/test_lint_push.yml

@@ -14,4 +14,4 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest]
-        python-version: ["3.10"]
+        python-version: ["3.9", "3.10"]

README.md

@@ -15,7 +15,7 @@ A deep learning-based segmentation Napari plugin to curate datasets, train your
 
 
 
-## :hammer_and_wrench: Installation
+## 🛠️ Installation
 
 ### System Requirements
 
@@ -33,7 +33,7 @@ We currently support `Windows`, `MacOS`, and `Linux` operating systems. The mini
 
 Before installing the plugin, please make sure you have the following installed:
 
-- Python 3.10 or later
+- `Python >=3.9,<3.11` 
 
 __New to `Python`?__ We recommend installing `Python 3.10` through the official [`Python` website](https://www.python.org/downloads/). This will include the `pip` package manager, which is required to install the plugin.
 
@@ -62,7 +62,10 @@ Navigate to where you want to create a new environment (_Example._ `Documents`),
 # Create a new environment
 python3.10 -m venv venv-allen-segmenter-ml
 
-# Activate the environment
+# (Windows) Activate the environment 
+.\venv-allen-segmenter-ml\Scripts\activate
+
+# (Mac/Linux) Activate the environment 
 source venv-allen-segmenter-ml/bin/activate
 ```
 #### Confirm Virtual Environment is Activated
@@ -89,19 +92,19 @@ To confirm that the virtual environment has been successfully activated, you can
 
 
 
-
-
-
 ## Install the Plugin
 
-To install the latest version of the plugin:
+To install the latest version of the plugin, along with napari:
 ```bash
-pip install allencell-segmenter-ml
+pip install allencell-segmenter-ml[napari]
 ```
 
-### :rotating_light: Post-Installation :rotating_light:
+You do not need to install `napari` separately as it is included in the plugin.
+
+### 🚨 Post-Installation 🚨
 
-> :memo: __NOTE:__ This section is specifically for users with at least one NVIDIA GPU installed on their machine. Not sure if you have an NVIDIA GPU? You can check by running `nvidia-smi` as shown [below](#step-1-checking-cuda-version). If you __do not__ have an NVIDIA GPU system, you can skip this section.
+>[!IMPORTANT] 
+⚠️ __NOTE:__ This section is specifically for users with at least one NVIDIA GPU installed on their machine. Not sure if you have an NVIDIA GPU? You can check by running `nvidia-smi` as shown [below](#step-1-checking-cuda-version). If you __do not__ have an NVIDIA GPU system, you can skip this section.
 
 Required Package
 

docs/models.md

@@ -0,0 +1,22 @@
+### Pre-Trained Models
+
+| Category           | Name              | MegaSeg_v1                                                                                  | MegaSeg_light                                                          |
+|--------------------|-------------------|---------------------------------------------------------------------------------------------|------------------------------------------------------------------------|
+| **Model Properties**   | Description       | CNN-based segmentation model trained on 2600 open 3D fluorescent microscopy images of cellular structures in human hiPSCs | Lighter version of MegaSeg which compromises accuracy for speed       |
+|                    | Architecture       | nnUNet                                                                                      | small nnUNet with fewer kernels                                       |
+|                    | Loss Function      | Generalized dice focal loss                                                                 | Generalized dice focal loss                                           |
+|                    | Optimization       | Adam                                                                                        | Adam                                                                  |
+|                    | # of Epochs        | 1000                                                                                        | 1000                                                                  |
+|                    | Stopping Criteria  | Validation loss not improving for 100 epochs                                               | Validation loss not improving for 100 epochs                          |
+|                    | System Trained On  | Nvidia A100                                                                                | Nvidia A100                                                           |
+|                    | Validation Step    | -                                                                                          | -                                                                     |
+| **Dependencies**   | CytoDL Version     | 1.7.1                                                                                       | 1.7.1                                                                 |
+|                    | PyTorch Version    | 2.4.0+cu118                                                                                | 2.4.0+cu118                                                           |
+| **Training Data**  | Image Resolution   | 55x624x924; 60x624x924; 65x600x900; 65x624x924; 70x624x924; 75x624x924; 75x600x900         | 55x624x924; 60x624x924; 65x600x900; 65x624x924; 70x624x924; 75x624x924; 75x600x900 |
+|                    | Minimum Image Size | -                                                                                          | -                                                                     |
+|                    | Microscope Objective | 100x                                                                                    | 100x                                                                  |
+|                    | Microscopy Technique | Spinning disk confocal                                                                    | Spinning disk confocal                                                |
+|                    | Public Data Link   | [Dataset Link](https://open.quiltdata.com/b/allencell/tree/aics/hipsc_single_cell_image_dataset/) | [Dataset Link](https://open.quiltdata.com/b/allencell/tree/aics/hipsc_single_cell_image_dataset/) |
+|                    | Expected Performance | On NVIDIA-A100, 80GB, Inference @ 6.01 Secs for an Input image of size 924x624x65        | On NVIDIA-A100, 80GB, Inference @ 2.32 Secs for an Input image of size 924x624x65 |
+|                    | Structures Trained On | Actin bundles, ER(SERCA2), Adherens junctions, Desmosomes, Gap junctions, Myosin, Nuclear pores, Endosomes, ER (SEC61 Beta), Nuclear speckles, Golgi, Tight junctions, Mitochondria | Actin bundles, ER(SERCA2), Adherens junctions, Desmosomes, Gap junctions, Myosin, Nuclear pores, Endosomes, ER (SEC61 Beta), Nuclear speckles, Golgi, Tight junctions, Mitochondria |
+| **Inference Data** | Minimum Image Dimension | 16x16x16                                                                            | 16x16x16                                                              |

pyproject.toml

@@ -8,16 +8,11 @@ build-backend = "setuptools.build_meta"
 # https://peps.python.org/pep-0621/
 [project]
 name = "allencell-segmenter-ml"
-version = "0.1.16"
+version = "1.0.0rc0"
 description = "A plugin to leverage ML segmentation in napari"
 readme = "README.md"
-requires-python = "<3.11,>=3.10"
+requires-python = ">=3.9,<3.11"
 license = { file = "LICENSE" }
-authors = [
-    { email = "[email protected]", name = "Brian Kim" },
-    { email = "[email protected]", name = "Chris Hughes" },
-    { email = "[email protected]", name = "Daniel Saelid" },
-]
 
 classifiers = [
     "Development Status :: 2 - Pre-Alpha",
@@ -29,12 +24,12 @@ classifiers = [
     "Programming Language :: Python",
     "Programming Language :: Python :: 3",
     "Programming Language :: Python :: 3 :: Only",
+    "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Topic :: Scientific/Engineering :: Image Processing",
 ]
 
 dependencies = [
-    "napari>=0.4.18",
     "npe2>=0.6.2",
     "numpy",
     "hydra-core==1.3.2",
@@ -54,6 +49,11 @@ Documentation = "https://github.com/AllenCell/allencell-ml-segmenter#README.md"
 # extra dependencies
 # https://peps.python.org/pep-0621/#dependencies-optional-dependencies
 [project.optional-dependencies]
+napari = [
+    "napari>=0.4.18",
+    "pyqt5",
+]
+
 test_lint = [
     "pytest<8.0.0", # https://docs.pytest.org/en/latest/contents.html
     "pytest-cov",  # https://pytest-cov.readthedocs.io/en/latest/
@@ -66,6 +66,8 @@ test_lint = [
     "mypy",
     "toml",
     "bumpver",
+    "napari>=0.4.18",
+    "magicgui"
 ]
 
 dev = [
@@ -103,8 +105,8 @@ where = ["src"]
 
 # https://pypi.org/project/bumpver
 [tool.bumpver]
-current_version = "0.1.16"
-version_pattern = "MAJOR.MINOR.PATCH[.PYTAGNUM]"
+current_version = "1.0.0rc0"
+version_pattern = "MAJOR.MINOR.PATCH[PYTAGNUM]"
 commit_message  = "Bump version {old_version} -> {new_version}"
 commit          = true
 tag             = false # no longer useful to tag here, must happen in create_publish_pr.yaml

src/allencell_ml_segmenter/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "0.1.16"
+__version__ = "1.0.0rc0"
 
 from allencell_ml_segmenter.napari.napari_reader import napari_get_reader
 from allencell_ml_segmenter.napari.sample_data import make_sample_data

src/allencell_ml_segmenter/_tests/scripts/pyproject.toml

@@ -5,7 +5,7 @@ version = "0.0.1"
 # https://pypi.org/project/bumpver
 [tool.bumpver]
 current_version = "0.0.1"
-version_pattern = "MAJOR.MINOR.PATCH[.PYTAGNUM]"
+version_pattern = "MAJOR.MINOR.PATCH[PYTAGNUM]"
 commit          = false
 tag             = false # no longer useful to tag here, must happen in create_publish_pr.yaml
 push            = false