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# 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: | |
```bash | |
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: | |
```bash | |
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`: | |
```bash | |
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: | |
```bash | |
python query_db.py print densepose_coco_2014_train image_id:int=36-156 -v | |
``` | |
## Visualization Mode | |
The general command form is: | |
```bash | |
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: | |
```bash | |
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: | |
```bash | |
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: | |
```bash | |
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: | |
```bash | |
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: | |
```bash | |
python query_db.py show densepose_coco_2014_train image_id:int=322 bbox,dp_v -v | |
``` | |
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