This guide provides instructions on structuring annotation files correctly before importing them into Visual Layer. Visual Layer supports two annotation formats : COCO (JSON format) and CSV format. Ensuring proper structuring will prevent errors during dataset creation and allow seamless integration.
image_annotations.csv
orimage_annotations.parquet
. Each row in the file represents an image and its corresponding label.
filename | label |
---|---|
IDX_DF_SIG21341_PlasmasNeg.png | IDX_DF |
IDX_DF_ALM00324_PlasmasPos.png | IDX_DF |
folder/IDX_RC_ALM04559_PlasmasNeg.png | IDX_RC |
filename
column must contain relative paths.label
column assigns a class to entire image.['t-shirt', 'SKU12345']
.caption
column for textual metadata.filename | label |
---|---|
cool-tshirt.png | [“t-shirt”, “SKU12345”] |
cool-pants.jpg | [“pants”, “SKU231312”] |
object_annotations.csv
or object_annotations.parquet
. Each row represents a detected object, including its bounding box coordinates and class label.
filename | col_x | row_y | width | height | label |
---|---|---|---|---|---|
Kitti/raw/training/image_2/006149.png | 0 | 240 | 135 | 133 | Car |
Kitti/raw/training/image_2/006149.png | 608 | 169 | 59 | 43 | Car |
col_x
and row_y
define the top-left corner of the bounding box.width
and height
must be greater than zero.annotations.json
.
bbox
) follow the format [col_x, row_y, width, height]
.
col_x
and row_y
define the top-left corner of the bounding box.width
and height
must be greater than zero.Format | Representation | File Type |
---|---|---|
JSON (COCO) | [x_min, y_min, width, height] | .json |
CSV(Image Labels) | [filename, label] | .csv |
CSV(Object Labels) | filename, col_x, row_y, width, height, label | .csv |