SamsungInnovationCampus-Batch3-TeamVerlyn
https://github.com/arku-viel/SamsungInnovationCampus-Batch3-TeamVerlyn
Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (4.9%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: arku-viel
- License: agpl-3.0
- Language: Python
- Default Branch: master
- Size: 22.7 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
About The Project
Pada dasarnya project kami menggunakan salah satu model pembelajaran yang paling populer diranah deteksi objek, yaitu yoloV5.
Kemudian kami menggunakan tempelate yang telah disediakan oleh github yoloV5.
Untuk membuat dataset, kami menggunakan Roboflow sebagai dasar.
Kemudian kami membuat file best.pt dengan menggunakan dataset Roboflow dan Google Collab
Dan kami memodifikasi file detect.py dan membuat file main.py untuk interface dan file utama.
Kami juga membuat bot telegram dan mensinkronisasikannya untuk menjadi output sementara.
Link :
YoloV5 Github : https://github.com/ultralytics/yolov5.git
Roboflow Dataset : https://universe.roboflow.com/verlyn-project-object-detection/pendeteksi-perlengkapan-seragam/model/9
Google Colab : https://colab.research.google.com/github/roboflow-ai/yolov5-custom-training-tutorial/blob/main/yolov5-custom-training.ipynb#scrollTo=eaFNnxLJbq4J
Main.py : https://github.com/Arkcept/SIC-Verlyn/blob/main/main.py
Detect.py : https://github.com/Arkcept/SIC-Verlyn/blob/main/detect.py
Credit
SIC4 - Verlyn - 2023
Owner
- Name: Abdul Ghofur Almiqbadi
- Login: arku-viel
- Kind: user
- Location: Indonesia
- Repositories: 1
- Profile: https://github.com/arku-viel
Java | Flutter | Dart | Python | C++
Citation (CITATION.cff)
cff-version: 1.2.0
preferred-citation:
type: software
message: If you use YOLOv5, please cite it as below.
authors:
- family-names: Jocher
given-names: Glenn
orcid: "https://orcid.org/0000-0001-5950-6979"
title: "YOLOv5 by Ultralytics"
version: 7.0
doi: 10.5281/zenodo.3908559
date-released: 2020-5-29
license: AGPL-3.0
url: "https://github.com/ultralytics/yolov5"