Pipettes detection Object Detection Dataset and Pre-Trained Model by Pipette detection

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Explore Dataset

Here are a few use cases for this project:

Laboratory Equipment Inventory: This computer vision model could automate the process of taking inventory of pipettes in a laboratory setting, identifying the type and count of each pipette.
Quality Control in Manufacturing: The model could be used in manufacturing or assembly lines where pipettes are produced, enabling automated identification and sorting of different types of pipettes. It could also detect any irregularities or imperfections.
Medical and Pharmaceutical Research: This model could assist researchers in readily identifying the correct tool, speeding up processes and reducing errors in experiments or pharmaceutical compounding where pipettes are commonly used.
Precision Agriculture: It could be used in agricultural research labs where pipettes are utilized for product development, soil testing, etc. The model can provide timely and accurate pipette identification, streamlining lab procedures.
Education and Training: This model could be utilized for digital learning resources in educational institutes offering chemistry, biology, or medicine courses. Here it could help students to identify and use different classes of pipettes accurately, enhancing their learning experience.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

YOLOv8

This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            pipettes-detection_dataset,
                            title = { Pipettes detection Dataset },
                            type = { Open Source Dataset },
                            author = { Pipette detection },
                            howpublished = { \url{ https://universe.roboflow.com/pipette-detection/pipettes-detection } },
                            url = { https://universe.roboflow.com/pipette-detection/pipettes-detection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-05-06 },
                            }