Datasets:
text string |
|---|
11 0.557766 0.609125 0.228219 0.207125 |
14 0.888961 0.583844 0.221703 0.514687 |
14 0.883258 0.647385 0.233484 0.642104 |
11 0.402211 0.713167 0.804422 0.573667 |
11 0.351859 0.659167 0.701594 0.681667 |
14 0.855234 0.638979 0.288844 0.691792 |
11 0.422828 0.596406 0.845656 0.807187 |
14 0.925039 0.720333 0.149922 0.542875 |
11 0.416969 0.710229 0.809094 0.579542 |
14 0.944086 0.708000 0.111828 0.578833 |
14 0.901047 0.719719 0.197906 0.546896 |
11 0.407359 0.650729 0.809969 0.695708 |
11 0.481781 0.695615 0.952281 0.596146 |
11 0.477070 0.701135 0.945641 0.597729 |
11 0.482047 0.639385 0.925906 0.721229 |
14 0.911742 0.775937 0.176516 0.448125 |
11 0.486039 0.669937 0.972078 0.633875 |
11 0.500000 0.696844 1.000000 0.602604 |
14 0.881937 0.835760 0.233937 0.325271 |
11 0.511305 0.641698 0.963922 0.716604 |
11 0.500000 0.685708 1.000000 0.586000 |
2 0.097016 0.427052 0.129875 0.077562 |
11 0.500000 0.651781 1.000000 0.691854 |
2 0.070859 0.376781 0.141719 0.155604 |
11 0.558445 0.587708 0.856297 0.824583 |
2 0.447719 0.484375 0.146125 0.157083 |
11 0.596297 0.722240 0.794406 0.555521 |
12 0.134141 0.535917 0.152344 0.159375 |
2 0.424656 0.374552 0.207250 0.195479 |
12 0.190266 0.360042 0.313000 0.181167 |
11 0.591539 0.641979 0.816922 0.716042 |
11 0.500000 0.707500 1.000000 0.585000 |
11 0.492023 0.711083 0.977828 0.577583 |
2 0.961820 0.684167 0.076359 0.490833 |
14 0.225344 0.497510 0.197156 0.274021 |
7 0.602305 0.517583 0.078078 0.075875 |
14 0.848672 0.639531 0.291906 0.528021 |
11 0.348859 0.713854 0.697719 0.561208 |
15 0.862883 0.491677 0.271359 0.914312 |
14 0.832922 0.623479 0.311844 0.500500 |
15 0.890359 0.560896 0.218625 0.608625 |
11 0.333508 0.683198 0.667016 0.626812 |
14 0.851555 0.562635 0.296891 0.815563 |
11 0.379789 0.674000 0.758141 0.631875 |
15 0.827703 0.493479 0.344594 0.986958 |
11 0.373500 0.706583 0.736750 0.584417 |
15 0.820453 0.500177 0.347844 0.999646 |
14 0.844711 0.605833 0.310578 0.500500 |
11 0.369203 0.678885 0.730500 0.642229 |
15 0.803719 0.600594 0.392063 0.755729 |
11 0.388156 0.614208 0.774000 0.763417 |
15 0.538148 0.500000 0.535016 1.000000 |
14 0.875125 0.572104 0.249375 0.834625 |
11 0.404008 0.702531 0.770609 0.593229 |
14 0.881203 0.649073 0.237594 0.674104 |
15 0.582141 0.440625 0.456344 0.881250 |
2 0.035258 0.741729 0.070453 0.516542 |
14 0.867687 0.697240 0.264625 0.605521 |
11 0.323047 0.697698 0.646094 0.604604 |
15 0.538195 0.555542 0.464016 0.863042 |
15 0.202898 0.415625 0.405797 0.831250 |
11 0.388914 0.664854 0.701109 0.640083 |
14 0.828391 0.500000 0.343219 1.000000 |
14 0.848906 0.620052 0.302187 0.758021 |
15 0.151086 0.446760 0.302172 0.888229 |
11 0.418813 0.712229 0.837625 0.561958 |
11 0.487156 0.667781 0.774844 0.607479 |
14 0.823219 0.697521 0.350750 0.600542 |
15 0.210102 0.598802 0.420203 0.802396 |
2 0.123523 0.714177 0.247016 0.383729 |
11 0.450000 0.543021 0.900000 0.410708 |
14 0.780531 0.512604 0.438938 0.966458 |
15 0.145266 0.492063 0.290531 0.978792 |
11 0.475031 0.701948 0.950062 0.552437 |
14 0.784820 0.505833 0.430359 0.988333 |
15 0.124852 0.518375 0.249703 0.963250 |
14 0.783867 0.724896 0.432266 0.542708 |
2 0.109891 0.549229 0.214312 0.387083 |
11 0.460484 0.652010 0.920969 0.570854 |
15 0.134617 0.612229 0.269016 0.763958 |
11 0.628516 0.419063 0.742969 0.838125 |
2 0.361187 0.741417 0.154219 0.136458 |
14 0.170805 0.500490 0.341609 0.999021 |
14 0.174523 0.591615 0.345047 0.805979 |
11 0.556016 0.696292 0.665656 0.607417 |
2 0.446094 0.507760 0.089687 0.128021 |
14 0.196328 0.604448 0.392656 0.791104 |
11 0.610008 0.665500 0.779984 0.666958 |
2 0.442453 0.421885 0.120406 0.116771 |
11 0.447008 0.732833 0.894016 0.528875 |
2 0.904711 0.692854 0.190047 0.511042 |
14 0.842477 0.614177 0.315047 0.415313 |
11 0.485906 0.733333 0.312562 0.529583 |
14 0.849141 0.615323 0.301719 0.542521 |
11 0.515164 0.715385 0.958766 0.560521 |
14 0.851953 0.314542 0.296094 0.026792 |
14 0.827117 0.554271 0.345766 0.517667 |
11 0.396352 0.653750 0.792703 0.683000 |
14 0.887094 0.647073 0.225812 0.671479 |
11 0.571945 0.758229 0.287391 0.483542 |
End of preview. Expand in Data Studio
🏥 Hospital Robot Perception Dataset (17 Classes - 5,254 Frames)
Tập dữ liệu chuẩn vàng phục vụ bài toán nhận diện đồ vật, phương tiện và con người trong môi trường bệnh viện dành cho robot tự hành và camera giám sát thông minh.
📊 Phân bố dữ liệu
| Tập (Split) | Số lượng ảnh | Bounding Boxes | Mục đích |
|---|---|---|---|
| Train | 3,715 | 10,642 | Huấn luyện mô hình YOLO |
| Validation | 655 | 1,957 | Tinh chỉnh siêu tham số và đánh giá epoch |
| Test (Benchmark) | 884 | 3,082 | Benchmark độc lập (robot patrol & clinical inspection) |
| Tổng cộng | 5,254 | 15,681 |
🏷️ 17 Lớp đối tượng (Classes)
0: patient, 1: doctor, 2: wheelchair, 3: queue_kiosk, 4: reception_counter, 5: sanitizer_stand, 6: pccc_station, 7: medical_waste_bin, 8: water_dispenser, 9: wc_station, 10: elevator_doors, 11: hospital_bed, 12: stretcher_cart, 13: iv_stand, 14: medical_trolley, 15: vital_monitor, 16: hospital_chair
📁 Cấu trúc thư mục YOLO
dataset/
├── data.yaml
├── train/
│ ├── images/
│ └── labels/
├── val/
│ ├── images/
│ └── labels/
└── test/
├── images/
└── labels/
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