vendor/detectron2/projects/DensePose/doc/TOOL_QUERY_DB.md

Query Dataset

query_db is a tool to print or visualize DensePose data from a dataset. It has two modes: print and show to output dataset entries to standard output or to visualize them on images.

Print Mode

The general command form is:

python query_db.py print [-h] [-v] [--max-entries N] <dataset> <selector>

There are two mandatory arguments:

• <dataset>, DensePose dataset specification, from which to select the entries (e.g. densepose_coco_2014_train).
• <selector>, dataset entry selector which can be a single specification, or a comma-separated list of specifications of the form field[:type]=value for exact match with the value or field[:type]=min-max for a range of values

One can additionally limit the maximum number of entries to output by providing --max-entries argument.

Examples:

1. Output at most 10 first entries from the densepose_coco_2014_train dataset:

python query_db.py print densepose_coco_2014_train \* --max-entries 10 -v

2. Output all entries with file_name equal to COCO_train2014_000000000036.jpg:

python query_db.py print densepose_coco_2014_train file_name=COCO_train2014_000000000036.jpg -v

3. Output all entries with image_id between 36 and 156:

python query_db.py print densepose_coco_2014_train image_id:int=36-156 -v

Visualization Mode

The general command form is:

python query_db.py show [-h] [-v] [--max-entries N] [--output <image_file>] <dataset> <selector> <visualizations>

There are three mandatory arguments:

• <dataset>, DensePose dataset specification, from which to select the entries (e.g. densepose_coco_2014_train).
• <selector>, dataset entry selector which can be a single specification, or a comma-separated list of specifications of the form field[:type]=value for exact match with the value or field[:type]=min-max for a range of values
• <visualizations>, visualizations specifier; currently available visualizations are:
  • bbox - bounding boxes of annotated persons;
  • dp_i - annotated points colored according to the containing part;
  • dp_pts - annotated points in green color;
  • dp_segm - segmentation masks for annotated persons;
  • dp_u - annotated points colored according to their U coordinate in part parameterization;
  • dp_v - annotated points colored according to their V coordinate in part parameterization;

One can additionally provide one of the two optional arguments:

• --max_entries to limit the maximum number of entries to visualize
• --output to provide visualization file name template, which defaults to output.png. To distinguish file names for different dataset entries, the tool appends 1-based entry index to the output file name, e.g. output.0001.png, output.0002.png, etc.

The following examples show how to output different visualizations for image with id = 322 from densepose_coco_2014_train dataset:

1. Show bounding box and segmentation:

python query_db.py show densepose_coco_2014_train image_id:int=322 bbox,dp_segm -v

2. Show bounding box and points colored according to the containing part:

python query_db.py show densepose_coco_2014_train image_id:int=322 bbox,dp_i -v

3. Show bounding box and annotated points in green color:

python query_db.py show densepose_coco_2014_train image_id:int=322 bbox,dp_segm -v

4. Show bounding box and annotated points colored according to their U coordinate in part parameterization:

python query_db.py show densepose_coco_2014_train image_id:int=322 bbox,dp_u -v

5. Show bounding box and annotated points colored according to their V coordinate in part parameterization:

python query_db.py show densepose_coco_2014_train image_id:int=322 bbox,dp_v -v