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varroa-mites-detection--test-set/README.dataset.txt

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+# varroa-mites-detection--test-set-1irzb-gsig > 2025-03-13 10:48pm
+https://universe.roboflow.com/rf-100-vl/varroa-mites-detection-test-set-1irzb-gsig-8ecee
+
+Provided by a Roboflow user
+License: MIT
+
+# Overview
+- [Introduction](#introduction)
+- [Object Classes](#object-classes)
+  - [Varroa Mite](#varroa-mite)
+
+# Introduction
+The dataset aims to detect Varroa mites on bees. Varroa mites are parasitic mites known for their impact on honey bee colonies. The dataset will help in identifying and annotating these mites accurately for monitoring and managing bee health.
+
+# Object Classes
+
+## Varroa Mite
+
+### Description
+Varroa mites are small, oval-shaped parasites that attach themselves to bees. They are typically seen on the bee's abdomen. The mites have a hard shell and their bodies are usually flattened, making them appear as small, round spots on the bee’s body.
+
+### Instructions
+- Annotate each visible Varroa mite on the bee.
+- Mites should be enclosed within a bounding box capturing the entire body of the mite.
+- Ensure the bounding box includes the whole visible surface of the mite.
+- Do not annotate mites that are indistinguishable from natural blemishes on the bee.
+- Ignore any reflections or shadows of the mites on the bee’s body.
+- If a mite is obstructed by wings or legs, use your best estimate to enclose its visible parts within the bounding box.
+- Do not annotate areas that can be mistaken for mite-like patterns on the wings or body, only focus on clear, oval-shaped parasites.

varroa-mites-detection--test-set/README.roboflow.txt

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+
+varroa-mites-detection--test-set-1irzb-gsig - v2 2025-03-13 10:48pm
+==============================
+
+This dataset was exported via roboflow.com on March 16, 2025 at 10:11 AM GMT
+
+Roboflow is an end-to-end computer vision platform that helps you
+* collaborate with your team on computer vision projects
+* collect & organize images
+* understand and search unstructured image data
+* annotate, and create datasets
+* export, train, and deploy computer vision models
+* use active learning to improve your dataset over time
+
+For state of the art Computer Vision training notebooks you can use with this dataset,
+visit https://github.com/roboflow/notebooks
+
+To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
+
+The dataset includes 942 images.
+Varroa-mites-detection--test-set-1irzb-gsig are annotated in COCO format.
+
+The following pre-processing was applied to each image:
+* Auto-orientation of pixel data (with EXIF-orientation stripping)
+
+No image augmentation techniques were applied.
+
+