text stringlengths 37 37 |
|---|
0 0.620272 0.865609 0.756430 0.265442 |
0 0.648671 0.654424 0.699336 0.687813 |
0 0.555992 0.684008 0.884086 0.628131 |
0 0.966316 0.711946 0.063158 0.572254 |
0 0.607004 0.652216 0.782101 0.691715 |
0 0.512127 0.851638 0.972015 0.292871 |
0 0.516176 0.605973 0.964706 0.784200 |
0 0.615596 0.917148 0.765138 0.161850 |
0 0.786133 0.807179 0.423828 0.382304 |
0 0.892971 0.729549 0.210863 0.537563 |
0 0.798860 0.770451 0.399023 0.455760 |
0 0.334734 0.563545 0.663866 0.869565 |
0 0.541586 0.620424 0.912959 0.755299 |
0 0.560757 0.804432 0.874502 0.387283 |
0 0.663717 0.774624 0.669027 0.447412 |
0 0.516814 0.340568 0.516814 0.574290 |
0 0.268945 0.402337 0.442793 0.804674 |
0 0.665676 0.530050 0.665676 0.936561 |
0 0.501316 0.501408 0.971053 0.991549 |
0 0.486034 0.498387 0.960894 0.958065 |
0 0.416816 0.732888 0.794275 0.517529 |
0 0.607874 0.721202 0.781102 0.554257 |
0 0.498879 0.747913 0.997758 0.500835 |
0 0.696589 0.768781 0.603232 0.459098 |
0 0.434959 0.701169 0.452575 0.347245 |
0 0.903017 0.900668 0.189655 0.195326 |
0 0.541750 0.552588 0.912525 0.891486 |
0 0.748980 0.956647 0.497959 0.082852 |
0 0.559928 0.782972 0.876565 0.430718 |
0 0.730841 0.904007 0.534579 0.188648 |
0 0.935282 0.673913 0.125261 0.391304 |
0 0.962376 0.777457 0.071287 0.441233 |
0 0.565341 0.672447 0.865530 0.651252 |
0 0.692529 0.788054 0.611111 0.420039 |
0 0.742837 0.631021 0.511461 0.734104 |
0 0.503745 0.565511 0.988764 0.865125 |
0 0.547359 0.674374 0.901639 0.647399 |
0 0.463930 0.694605 0.788557 0.606936 |
0 0.523128 0.546243 0.927313 0.903661 |
0 0.535714 0.699833 0.925926 0.596990 |
0 0.676596 0.530885 0.643972 0.934891 |
0 0.761386 0.792988 0.473267 0.410684 |
0 0.682590 0.606010 0.632696 0.784641 |
0 0.671825 0.578464 0.654216 0.839733 |
0 0.622614 0.720736 0.751836 0.555184 |
0 0.498908 0.520903 0.997817 0.954849 |
0 0.386935 0.639399 0.673367 0.717863 |
0 0.943220 0.763773 0.110169 0.469115 |
0 0.703917 0.592486 0.587558 0.811175 |
0 0.603563 0.613680 0.788419 0.768786 |
0 0.576324 0.668614 0.535826 0.659432 |
0 0.777487 0.501669 0.441536 0.993322 |
0 0.763341 0.878965 0.468677 0.238731 |
0 0.499314 0.502504 0.998628 0.991653 |
0 0.583162 0.557596 0.829569 0.881469 |
0 0.620567 0.500835 0.755319 0.994992 |
0 0.577907 0.786127 0.839535 0.423892 |
0 0.786828 0.577071 0.422877 0.842004 |
0 0.440230 0.696532 0.475862 0.603083 |
0 0.854023 0.577071 0.287356 0.842004 |
0 0.684411 0.710019 0.627376 0.576108 |
0 0.703593 0.837187 0.588822 0.321773 |
0 0.610437 0.608863 0.774272 0.778420 |
0 0.905077 0.866089 0.185430 0.263969 |
0 0.553097 0.610790 0.890265 0.774566 |
0 0.890323 0.982659 0.215054 0.030829 |
0 0.590832 0.520231 0.814941 0.955684 |
0 0.764957 0.710019 0.466667 0.576108 |
0 0.682018 0.638796 0.631579 0.719064 |
0 0.617550 0.587646 0.761589 0.821369 |
0 0.499106 0.539232 0.998211 0.918197 |
0 0.565138 0.499037 0.866055 0.998073 |
0 0.591116 0.635838 0.815490 0.724470 |
0 0.637540 0.489819 0.281553 0.468326 |
0 0.278436 0.452794 0.473934 0.890173 |
0 0.343609 0.610352 0.422556 0.482422 |
0 0.600186 0.546835 0.283859 0.425316 |
0 0.388626 0.651659 0.597156 0.535545 |
0 0.552050 0.515101 0.694006 0.714765 |
0 0.433764 0.598434 0.718901 0.418345 |
0 0.679558 0.682081 0.638674 0.631985 |
0 0.646930 0.863105 0.701754 0.270451 |
0 0.567922 0.502890 0.861872 0.990366 |
0 0.618254 0.587669 0.760317 0.820809 |
0 0.659176 0.707012 0.677903 0.582638 |
0 0.720217 0.476628 0.557160 0.666110 |
0 0.773465 0.535893 0.450753 0.507513 |
0 0.740828 0.762104 0.515976 0.472454 |
0 0.865096 0.876686 0.265525 0.242775 |
0 0.750996 0.508347 0.494024 0.979967 |
0 0.634094 0.505008 0.728959 0.986644 |
0 0.508050 0.550083 0.980322 0.896494 |
0 0.537149 0.702838 0.841365 0.590985 |
0 0.585007 0.897329 0.235609 0.202003 |
0 0.379518 0.347245 0.737617 0.594324 |
0 0.593042 0.504181 0.810680 0.988294 |
0 0.556780 0.504174 0.883051 0.988314 |
0 0.586176 0.505017 0.824057 0.715719 |
0 0.477558 0.860368 0.786355 0.275920 |
0 0.922801 0.773411 0.150808 0.449833 |
End of preview. Expand in Data Studio
Oral YOLO Lesion Detector
This model is a YOLO-based object detection model trained to detect oral lesion regions in smartphone-captured oral cavity images.
The model is intended for research, prototyping, and assistive screening workflows. It is not a medical device and must not be used as the sole basis for diagnosis, treatment decisions, or clinical triage.
Model Details
- Model type: YOLO object detector
- Task: Oral lesion detection / object detection
- Input: Oral cavity images
- Output: Bounding boxes around suspected lesion regions
- Framework: Ultralytics YOLO
- Dataset:
sach/oral-yolo-dataset
Intended Use
This model can be used for:
- Research on oral lesion detection
- Hackathon or prototype demonstrations
- Pre-screening assistance in oral health applications
- Cropping suspected lesion regions before passing them to a classifier or vision-language model
This model should not be used for:
- Final medical diagnosis
- Replacing dentists, oncologists, or trained medical professionals
- Emergency decision-making
- Deployment on real patients without clinical validation, regulatory review, and ethical approval
Training Data
The model was trained on a YOLO-format oral image dataset containing oral cavity images and bounding-box annotations for lesion-like regions.
Expected dataset structure:
oral_yolo_dataset/
├── images/
│ ├── train/
│ ├── val/
│ └── test/
├── labels/
│ ├── train/
│ ├── val/
│ └── test/
└── data.yaml
- Downloads last month
- 8,340