diff --git a/docs/cli.md b/docs/cli.md
deleted file mode 100644
index d9e7067..0000000
--- a/docs/cli.md
+++ /dev/null
@@ -1 +0,0 @@
-::: geococo.cli
diff --git a/docs/fiftyone.md b/docs/fiftyone.md
deleted file mode 100644
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--- a/docs/fiftyone.md
+++ /dev/null
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-## To be continued
\ No newline at end of file
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-# Welcome to geococo's documentation!
-
-
-Easily transform your GIS annotations into [Microsoft's Common Objects In Context (COCO)](https://cocodataset.org/#format-data) datasets with GeoCOCO. This tool allows users to leverage the advanced digitizing solutions of modern GIS software for the annotations of image objects in geographic imagery.
-
-Built with `Pydantic` and `pycocotools`, it features a complete implementation of the COCO standard for object detection with out-of-the-box support for JSON-encoding and RLE compression. The resulting datasets are versioned, easily extendable with new annotations and fully compatible with other data applications that accept the COCO format.
-
-## Key features
-- User-friendly: GeoCOCO is designed for ease of use, requiring minimal configuration and domain knowledge
-- Version Control: Datasets created with GeoCOCO are versioned and designed for expansion with future annotations
-- Command-line Tool: Use GeoCOCO from your terminal to create, append and copy COCO datasets
-- Python Module: Integrate GeoCOCO in your own data applications with the `geococo` package
-- Representation: GeoCOCO maximizes label representation through an adaptive moving window approach
-- COCO Standard: Output datasets are fully compatible with other COCO-accepting applications
-- Compact File Size: JSON-encoding and RLE compression are employed to ensure compact file sizes
-
-## Installation
-Installing from the Python Package Index (PyPI):
-````
-# Install from PYPI with Python's package installer (pip)
-pip install geococo
-````
-
-## Example of usage
-
-After installing `geococo`, there are a number of ways you can interact with its API.
-
-#### Command line interface
- The easiest way to use `geococo` is to simply call it from your preferred terminal with one of three commands: `new`, `add` and `copy`.
-
-````
-$ geococo --help
-Usage: geococo [OPTIONS] COMMAND [ARGS]...
-
- Transform your GIS annotations into COCO datasets.
-
-Options:
- --help Show this message and exit.
-
-Commands:
- add Transform and add GIS annotations to an existing CocoDataset
- copy Copy and (optionally) update the metadata of an existing CocoDataset
- new Initialize a new CocoDataset with user-prompted metadata
-````
-
-Starting a new CocoDataset (will prompt user for metadata like Description and Contributor)
-
-````
-$ geococo new dataset.json
-````
-
-Adding new annotations to existing CocoDataset (will increment version based on input data and update any new categories/images)
-````
-$ geococo add image.tif labels.shp dataset.json images/ 512 512 --id-attribute ids
-````
-
-For more information on the different commands, call `geococo COMMAND` with `--help`.
-````
-$ geococo add --help
-Usage: geococo add [OPTIONS] IMAGE_PATH LABELS_PATH JSON_PATH OUTPUT_DIR WIDTH
- HEIGHT
-
- Transform and add GIS annotations to an existing COCO dataset.
-
- This method generates a COCO dataset by moving across the given image
- (image_path) with a moving window (width, height), constantly checking for
- intersecting annotations (labels_path) that represent image objects in said
- image (e.g. buildings in satellite imagery; denoted by (super)category name
- and/or id). Each valid intersection will add n Annotations entries to the
- dataset (json_path) and save a subset of the input image that contained
- these entries (output_dir).
-
- The output data size depends on your input labels, as the moving window
- adjusts its step size to accommodate the average annotation size, optimizing
- dataset representation and minimizing tool configuration. Each addition will
- also increment the dataset version: patch if using the same image_path,
- minor if using a new image_path, and major if using a new output_dir.
-
-Arguments:
- IMAGE_PATH Path to geospatial image containing image objects [required]
- LABELS_PATH Path to vector file containing annotated image objects
- [required]
- JSON_PATH Path to json file containing the COCO dataset [required]
- OUTPUT_DIR Path to output directory for image subsets [required]
- WIDTH Width of image subsets [required]
- HEIGHT Height of image subsets [required]
-
-Options:
- --id-attribute TEXT Name of column containing category_id values
- (optional if --name_attribute is given)
- --name-attribute TEXT Name of column containing category_name values
- (optional if --id_attribute is given)
- --super-attribute TEXT Name of column containing supercategory values
- --help Show this message and exit.
-````
-
-
-#### Python module
-This is recommended for most developers as it gives you more granular control over the various steps. It does assume a basic familiarity with the `geopandas` and `rasterio` packages (i.e. GIS modules that help you manage vector and raster data respectively).
-
-````
-import pathlib
-import geopandas as gpd
-import rasterio
-from geococo import create_dataset, load_dataset, save_dataset, append_dataset
-
-# Replace this with your preferred output paths
-data_path = pathlib.Path("path/to/your/coco/output/images")
-json_path = pathlib.Path("path/to/your/coco/json/file")
-
-# Dimensions of the moving window and output images
-width, height = 512, 512
-
-# Starting a new CocoDataset
-description = "My First Dataset"
-contributor = "User"
-
-# version and date_created are automatically set
-dataset = create_dataset(description=description, contributor=contributor)
-# You can also load existing COCO datasets
-# dataset = load_dataset(json_path=json_path)
-
-# Loading GIS data with rasterio and geopandas
-labels = gpd.read_file(some_labels_path)
-raster_source = rasterio.open(some_image_path)
-
-# (Optional) Apply any spatial or attribute queries here
-# labels = labels.loc[labels["ids"].isin([1, 2, 3])]
-# labels = labels.loc[labels.within(some_polygon)]
-
-# Find and save all Annotation instances
-dataset = append_dataset(
- dataset=dataset,
- images_dir=data_path,
- src=raster_source,
- labels=labels,
- window_bounds=[(width, height)],
- id_attribute=None, # column with category_id values
- name_attribute="ids", # column with category_name values
- super_attribute=None, # optional column with super_category values
-)
-
-# Encode CocoDataset instance as JSON and save to json_path
-save_dataset(dataset=dataset, json_path=json_path)
-````
-
-## Visualization with FiftyOne
-Like the official COCO project, the open source tool [FiftyOne](https://docs.voxel51.com/) can be used to visualize and evaluate your datasets. To do this, you'll need the `fiftyone` and `pycocotools` packages. Note that `geococo` does not install `fiftyone` by default, so you'll need to install it separately (instructions for installation can be found [here](https://docs.voxel51.com/getting_started/install.html)). Once you have `fiftyone` installed, you can use the following command to inspect your COCO dataset in your web browser.
-
-````
-# requires pycocotools and fiftyone
-import fiftyone as fo
-import fiftyone.zoo as foz
-import pathlib
-
-data_path = pathlib.Path("path/to/your/coco/output/images")
-json_path = pathlib.Path("path/to/your/coco/json/file")
-
-# Load COCO formatted dataset
-coco_dataset = fo.Dataset.from_dir(
- dataset_type=fo.types.COCODetectionDataset,
- data_path=data_path,
- labels_path=json_path,
- include_id=True,
-)
-
-# Launch the app
-session = fo.launch_app(coco_dataset, port=5151)
-````
-
-
- 
- 
-
-
diff --git a/docs/leafmap.md b/docs/leafmap.md
deleted file mode 100644
index 10899ec..0000000
--- a/docs/leafmap.md
+++ /dev/null
@@ -1 +0,0 @@
-## To be continued
\ No newline at end of file
diff --git a/docs/models.md b/docs/models.md
deleted file mode 100644
index ba0ca82..0000000
--- a/docs/models.md
+++ /dev/null
@@ -1,13 +0,0 @@
-::: geococo.coco_models
- options:
- members:
- - Info
- - Image
- - Annotation
- - Category
- - RleDict
- - Source
- - CocoDataset
- show_root_heading: false
- merge_init_into_class: false
- show_if_no_docstring: false
\ No newline at end of file
diff --git a/docs/processing.md b/docs/processing.md
deleted file mode 100644
index 17a40c4..0000000
--- a/docs/processing.md
+++ /dev/null
@@ -1,16 +0,0 @@
-::: geococo.coco_manager
- options:
- members:
- - create_dataset
- - load_dataset
- - save_dataset
- show_root_heading: false
-
-
-::: geococo.coco_processing
- options:
- members:
- - append_dataset
- show_root_heading: false
-
-
diff --git a/docs/utils.md b/docs/utils.md
deleted file mode 100644
index 3454d2d..0000000
--- a/docs/utils.md
+++ /dev/null
@@ -1 +0,0 @@
-::: geococo.utils
diff --git a/mkdocs.yml b/mkdocs.yml
deleted file mode 100644
index 96f9eca..0000000
--- a/mkdocs.yml
+++ /dev/null
@@ -1,61 +0,0 @@
-site_name: "GeoCOCO: Transform your GIS annotations into COCO datasets"
-site_description: Transform your GIS annotations into COCO datasets
-site_url: https://jaspersiebring.github.io/geococo/
-repo_url: https://github.com/jaspersiebring/geococo
-repo_name: jaspersiebring/geococo
-
-nav:
-- Quickstart: index.md
-- API Documentation:
- - COCO Models: models.md
- - COCO Processing: processing.md
- - Typer CLI: cli.md
- - Utilities: utils.md
-- References:
- - License: https://github.com/jaspersiebring/GeoCOCO/blob/main/LICENSE
-
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- toggle:
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- - media: "(prefers-color-scheme: dark)"
- scheme: slate
- primary: light green
- accent: light green
- toggle:
- icon: material/lightbulb
- name: "Switch to light mode"
- highlightjs: true
- locale: en
- features:
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-
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- domains: [std, py]
- options:
- docstring_style: sphinx
- docstring_section_style: table
- summary: true
- separate_signature: true
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index 0d94561..c3ff826 100644
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-
[[package]]
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@@ -2109,17 +1576,16 @@ testing-integration = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "jar
[[package]]
name = "setuptools-scm"
-version = "8.0.1"
+version = "8.0.3"
description = "the blessed package to manage your versions by scm tags"
optional = false
python-versions = ">=3.8"
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tomli = {version = ">=1", markers = "python_version < \"3.11\""}
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python-versions = "^3.8"
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diff --git a/pyproject.toml b/pyproject.toml
index d986e9c..4685870 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
[tool.poetry]
name = "geococo"
-version = "0.5.1"
+version = "0.5.2"
description = "Converts GIS annotations to Microsoft's Common Objects In Context (COCO) dataset format"
authors = ["Jasper Siebring "]
readme = "README.md"
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pandas-stubs = "^2.0.3.230814"
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