Medical waste deytection by deep learning

Object Detection

Dataset Analytics

Generated on June 20, 2023 at 10:26 pm.

Number of Annotations

666

Average Image Size

8.29 mp

Median Image Ratio

2160x2160
square

Class Balance

Overview of the number of annotations for each class in your dataset.

Classes

all
train
valid
test
122
119
82
82
72
40
Under Represented
22
Under Represented
Under Represented
7
Under Represented
6
Under Represented
86
54
62
52
28
Under Represented
15
Under Represented
Under Represented
7
Under Represented
5
Under Represented
24
11
18
18
8
Under Represented
5
Under Represented
Under Represented
0
Missing
1
Under Represented
12
17
Under Represented
Under Represented
4
Under Represented
2
Under Represented
Under Represented
0
Missing
0
Missing

Dimension Insights

Overview of the sizes and aspect ratios of the images in your dataset.

Size Distribution

Sizes are based on the number of pixels in your images.

The purple box indicates the median width by median height image (2160x2160).

56
294
> 1024x1024
2160px
2160px

Aspect Ratio Distribution

The aspect ratio of your images compares the width vs. the height of your images.

tall
221
wide
129

Annotation Heatmap

Overview of where your annotations are located in the images in your dataset.

all
medicine (119)
waste (122)
dresser (82)
needle box (105)
cotton (40)
syringe (82)
cork (22)
dustbin (72)
Strip (7)
bed sheet (9)
tissue (6)

Histogram of Object Count by Image

Overview of how many classes are annotated in each image in your dataset.

all
medicine
waste
dresser
needle box
cotton
syringe
cork
dustbin
Strip
bed sheet
tissue
    184 imgs
    92
  • 0
  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
Count of all objects

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