Visualize

.gitignore

@@ -10,4 +10,7 @@ docs/_build
 *.egg-info
 
 # MacOS files
-.DS_Store
+.DS_Store
+
+# data
+web_app/test_example/

UV_MIGRATION.md

@@ -0,0 +1,45 @@
+# UV Migration Guide
+
+This project has been migrated from pixi to uv for dependency management.
+
+## Installation
+
+1. Install uv if not already installed:
+   ```bash
+   curl -LsSf https://astral.sh/uv/install.sh | sh
+   ```
+
+2. Sync dependencies:
+   ```bash
+   uv sync
+   ```
+
+3. Install the project in editable mode:
+   ```bash
+   uv pip install -e .
+   ```
+
+## Common Commands
+
+### Development
+- Install dependencies: `uv sync`
+- Add a dependency: `uv add package-name`
+- Add a dev dependency: `uv add --dev package-name`
+- Remove a dependency: `uv remove package-name`
+
+### Running the project
+- Activate virtual environment: `source .venv/bin/activate` (or use `uv run`)
+- Run scripts with uv: `uv run python script.py`
+- Run the visualizer: `uv run quac-visualizer` (replaces `pixi run visualizer`)
+
+### Environments
+The project supports different environments through optional dependencies:
+- Development: `uv sync --extra dev` (installs pytest, black, mypy, etc.)
+- Web: `uv sync --extra web` (installs flask, werkzeug)
+- Docs: `uv sync --extra docs` (installs sphinx and related packages)
+
+### Migration Notes
+- Pixi's conda channels (nvidia, pytorch) are replaced by PyPI packages
+- The `funlib.learn.torch` git dependency is handled via `[tool.uv.sources]`
+- The pixi task `visualizer` is replaced by the `quac-visualizer` script
+- Python version is constrained to `>=3.10,<3.13` for PyTorch compatibility

pyproject.toml

@@ -6,7 +6,7 @@ requires = ["setuptools", "wheel"]
 name = "quac"
 description = "Quantitative Attribution with Counterfactuals"
 readme = "README.md"
-requires-python = ">=3.10"
+requires-python = ">=3.10,<3.13"
 classifiers = ["Programming Language :: Python :: 3"]
 keywords = []
 license = { text = "BSD 3-Clause License" }
@@ -18,9 +18,8 @@ dynamic = ["version"]
 dependencies = [
   "captum",
   "numpy>=2.0",
-  "torch==2.4.0",
-  "torchvision",
-  "funlib.learn.torch@git+https://github.com/funkelab/funlib.learn.torch",
+  "torch>=2.4.0,<2.5",
+  "torchvision>=0.19.0",
   "opencv-python",
   "pydantic",
   "scipy",
@@ -33,6 +32,7 @@ dependencies = [
 
 [project.optional-dependencies]
 dev = ['pytest', 'black', 'mypy', 'pdoc', 'pre-commit']
+web = ['flask>=2.0.0', 'werkzeug>=2.0.0']
 docs = [
   "ipykernel",
   "jupyter_sphinx",
@@ -53,16 +53,21 @@ docs = [
 homepage = "https://funkelab.github.io/quac/"
 repository = "https://github.com/funkelab/quac"
 
-[tool.pixi.project]
-channels = ["nvidia/label/cuda-11.8.0", "nvidia", "conda-forge", "pytorch"]
-platforms = ["linux-64"]
+[tool.setuptools.dynamic]
+version = { attr = "quac.__version__" }
 
-[tool.pixi.pypi-dependencies]
-quac = { path = ".", editable = true }
+[tool.uv]
+dev-dependencies = [
+    "pytest",
+    "black", 
+    "mypy",
+    "pdoc",
+    "pre-commit"
+]
 
-[tool.pixi.environments]
-default = { solve-group = "default" }
-dev = { features = ["dev"], solve-group = "default" }
-docs = { features = ["docs"], solve-group = "default" }
+[tool.uv.sources]
+# Handle the git dependency for funlib.learn.torch
+funlib-learn-torch = { git = "https://github.com/funkelab/funlib.learn.torch" }
 
-[tool.pixi.tasks]
+[tool.mypy]
+python_version = "3.10"

src/quac/explanation.py

@@ -42,6 +42,7 @@ def __init__(
         score_changes: Optional[Union[list, np.ndarray]] = None,
         optimal_threshold: Optional[float] = None,
         method: Optional[str] = None,
+        annotation: str = "",
     ):
         self._query_path = query_path
         self._counterfactual_path = counterfactual_path
@@ -59,6 +60,7 @@ def __init__(
         self._score_changes = score_changes
         self._optimal_threshold = optimal_threshold
         self._method = method
+        self.annotation = annotation
 
         # Computed
         self._query: Optional[torch.Tensor] = None
@@ -78,6 +80,7 @@ def __eq__(self, value):
                 and self.source_class == value.source_class
                 and self.target_class == value.target_class
                 and self.score == value.score
+                and self.annotation == value.annotation
             )
             # The other, optional, attributes are not checked for equality
         return False
@@ -179,4 +182,5 @@ def explanation_encoder(explanation: Explanation):
             "generated_prediction": serialize(explanation.generated_prediction),
             "optimal_threshold": explanation._optimal_threshold,
             "method": explanation._method,
+            "annotation": explanation.annotation,
         }

tests/test_evaluation.py

@@ -1,11 +1,11 @@
 import pytest
 from quac.evaluation import Evaluator
-from funlib.learn.torch.models import Vgg2D
+from torchvision.models.resnet import resnet18
 import numpy as np
 
 
 @pytest.mark.skip("Skip test until we have usable data in CI/CD")
-@pytest.mark.parametrize("input_shape", [(1, 128, 128)])
+@pytest.mark.parametrize("input_shape", [(3, 224, 224)])
 @pytest.mark.parametrize("num_thresholds", [50, 100])
 def test_evaluator(input_shape, num_thresholds):
     """Checks that evaluator runs without errors"""
@@ -16,9 +16,7 @@ def test_evaluator(input_shape, num_thresholds):
     attribution = np.random.rand(*input_shape)
     vmin = -1
     vmax = 1
-    classifier = Vgg2D(
-        (input_shape[1], input_shape[2]), output_classes=2, input_fmaps=input_shape[0]
-    )
+    classifier = resnet18(num_classes=2)
 
     predictions = {
         "original": np.random.rand(2),