poker Computer Vision Project
HuDz
Updated 4 months ago
Tags
Classes (81)
* Auto-orientation of pixel data (with EXIF-orientation stripping)
* 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
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
==============================
Cards are annotated in YOLOv9 format.
For state of the art Computer Vision training notebooks you can use with this dataset,
No image augmentation techniques were applied.
PokerStars - v2 2023-12-30 7:58pm
Roboflow is an end-to-end computer vision platform that helps you
The dataset includes 2629 images.
The following pre-processing was applied to each image:
This dataset was exported via roboflow.com on August 12, 2024 at 6:06 PM GMT
To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
visit https://github.com/roboflow/notebooks
Metrics
Try This Model
Drop an image or
A description for this project has not been published yet.
Use This Trained Model
Try it in your browser, or deploy via our Hosted Inference API and other deployment methods.
Build Computer Vision Applications Faster with Supervision
Visualize and process your model results with our reusable computer vision tools.
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{
poker-2mlt9_dataset,
title = { poker Dataset },
type = { Open Source Dataset },
author = { HuDz },
howpublished = { \url{ https://universe.roboflow.com/hudz/poker-2mlt9 } },
url = { https://universe.roboflow.com/hudz/poker-2mlt9 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { aug },
note = { visited on 2024-11-30 },
}