Datasets
Standard Dataset
Micronutrient Deficiency Data

- Citation Author(s):
- Submitted by:
- Amey Agarwal
- Last updated:
- Wed, 04/16/2025 - 07:04
- DOI:
- 10.21227/e5pe-qe60
- Data Format:
- License:
- Categories:
- Keywords:
Abstract
Paper : Assessment of Inference Improvements for Facial Micronutrient Deficiency Detection using Attention-Enhanced YOLOv5
Authors : Amey Agarwal, Shreya Rathod, Riva Rodrigues, Nirmitee Sarode, Dhananjay R. Kalbande
Desciption
This is a dataset of 7 classes : 6 facial skin problems and 1 null class.
A facial skin problem may be identified in an image and marked using Bounding Box Annotation.
Acne Class indicates deficiency of Vitamin D
Blackhead and Nodules are types of acne
Darkspot indicates deficiency of Vitamin B12
Freckle class does not have a reported potential micronutrient deficiency
Skin Redness, treated as hyperpigmentation, indicates deficiency of Vitamin B12
Null class indicates healthy face image
Size
MicronutrientDeficiencyData-1 Folder size : 169 MB
Platform
No specific platform required.
Environmnent
No specific environment required.
Directory
MicronutrientDeficiencyData-1
|--->data.yaml
|--->README.dataset.txt
|--->README.roboflow.txt
|--->test
|--->images/*.jpg
|--->labels/*.txt
|--->train
|--->images/*.jpg
|--->labels/*.txt
|--->valid
|--->images/*.jpg
|--->labels/*.txt
Class Names
class_id : class_name
0 : acne
1 : blackhead
2 : darkspot
3 : freckle
4 : nodules
5 : skinredness
6 : null
TXT file format
Format : YOLOv5 PyTorch TXT
class_id center_x center_y width height
Reference Support : https://roboflow.com/formats/yolov5-pytorch-txt
Training Instructions
1) !git clone https://github.com/ultralytics/yolov5
2) !pip install -r yolov5/requirements.txt
3) !python yolov5/train.py --img 640 --batch 16 --epochs 300 --data yolov5/MicronutrientDeficiencyData-1/data.yaml --cfg yolov5/models/yolov5s.yaml --weights '' --save-period 10
References (Open-Source Datasets)
1) https://universe.roboflow.com/testing-rfihx/facial-health/dataset/1
2) https://github.com/xpwu95/LDL
3) https://universe.roboflow.com/kritsakorn/acne-kbm0q
4) https://universe.roboflow.com/bdle-9kwmc/skin-problems-2eamt
5) https://universe.roboflow.com/dermafie/dermafie
6) https://universe.roboflow.com/sanjanar-yktgw/normal-bwevz
Author Contact
Amey Agarwal : amey.agarwal@spit.ac.in
Dhananjay R. Kalbande : drkalbande@spit.ac.in
Shreya Rathod : shreya.rathod22@spit.ac.in
Nirmitee Sarode : nirmitee.sarode22@spit.ac.in
Riva Rodrigues : riva.rodrigues22@spit.ac.in
1) !git clone https://github.com/ultralytics/yolov5
2) !pip install -r yolov5/requirements.txt
3) !python yolov5/train.py --img 640 --batch 16 --epochs 300 --data yolov5/MicronutrientDeficiencyData-1/data.yaml --cfg yolov5/models/yolov5s.yaml --weights '' --save-period 10
Comments
This is the cleaned preprocesed dataset for detecting facial skin issues(bounding box) to identify potential micronutrient deficiencies
Thank you for providing such a useful dataset.