Detection of apple based on YOLOv4 model

License BSD-3 PyPI Python Version tests codecov napari hub

Detection of apple based on YOLOv4-tiny model

This napari plugin was generated with Cookiecutter using @napari's cookiecutter-napari-plugin template.


Before you can operate the module, you must install the napari-apple module.

Instruction for napari-module

You can install napari-apple via pip:

pip install napari-apple

To install latest development version :

pip install git+

How does it works

Here, user drop its images in the napari windows. The plugin shows two widgets :

  • Image detection
  • Export data

In Image detection, user select the interesting layer to detect apple. The "Run" button run the inference detection based on Yolov4-tiny model. At the end, the result is displayed on screen. User can correct freely the detection by removing or adding box in image.

In Export data, user export select the interesting shape layer and RGB image. A button "Save to csv" save bounding box coordinate in Yolo way into a text file.

Capture d'écran 2024-04-24 114340


Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.


Distributed under the terms of the BSD-3 license, "napari-apple" is free and open source software


If you encounter any problems, please file an issue along with a detailed description.


  • 0.0.8

Last updated:

  • 24 April 2024

First released:

  • 23 June 2022


Supported data:

  • Information not submitted

Plugin type:

  • Information not submitted

GitHub activity:

  • Stars: 2
  • Forks: 4
  • Issues + PRs: 1

Python versions supported:

Operating system:


  • numpy
  • magicgui
  • qtpy
  • opencv-python-headless
  • scikit-image
  • napari