. Computer Vision Project

Deneme

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Classes (694)
* Auto-contrast via contrast stretching
* Auto-orientation of pixel data (with EXIF-orientation stripping)
* Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise, upside-down
* Random shear of between -14° to +14° horizontally and -15° to +15° vertically
* Resize to 800x800 (Stretch)
* Salt and pepper noise was applied to 1.13 percent of pixels
* annotate, and create datasets
* collaborate with your team on computer vision projects
* collect & organize images
* export, train, and deploy computer vision models
* understand and search unstructured image data
* use active learning to improve your dataset over time
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==============================
For state of the art Computer Vision training notebooks you can use with this dataset,
Keman
Keman Yay
Keman yay
Roboflow is an end-to-end computer vision platform that helps you
The dataset includes 4470 images.
The following augmentation was applied to create 3 versions of each source image:
The following pre-processing was applied to each image:
This dataset was exported via roboflow.com on April 17, 2024 at 4:42 PM GMT
To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
Violin are annotated in Tensorflow Object Detection format.
violin_detection - v4 yoloV8_pre_trained_coco
visit https://github.com/roboflow/notebooks

A description for this project has not been published yet.

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Cite This Project

LICENSE
CC BY 4.0

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

                        @misc{
                            .-avbgp_dataset,
                            title = { . Dataset },
                            type = { Open Source Dataset },
                            author = { Deneme },
                            howpublished = { \url{ https://universe.roboflow.com/deneme-ohu32/.-avbgp } },
                            url = { https://universe.roboflow.com/deneme-ohu32/.-avbgp },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { apr },
                            note = { visited on 2024-09-23 },
                            }