"""
These are answers to the questions: How do I?
"""
[docs]def get_images_with_videoid():
"""
Q: How would you recommend querying a kwcoco file to get all of the images
associated with a video id?
"""
import kwcoco
import ubelt as ub
dset = kwcoco.CocoDataset.demo('vidshapes8-msi')
video_id = 1
# With Object1d API
images = dset.images(vidid=video_id)
print('images = {!r}'.format(images))
print('images.objs = {}'.format(ub.repr2(images.objs, nl=1)))
# With the index
image_ids = dset.index.vidid_to_gids[video_id]
imgs = [dset.index.imgs[gid] for gid in image_ids]
print('image_ids = {!r}'.format(image_ids))
print('imgs = {}'.format(ub.repr2(imgs, nl=1)))
[docs]def get_all_channels_in_dataset():
"""
Q. After I load a kwcoco.json into a kwcoco_dset, is there a nice way to
query what channels are available for the input imagery? It looks like I
can iterate over .imgs and build my own set, but maybe theres a built in
way
A. The better way is to use the CocoImage API.
"""
import kwcoco
dset = kwcoco.CocoDataset.demo('vidshapes8-msi-multisensor')
all_channels = []
for gid in dset.images():
# Build the CocoImage (a lightweight wrapper around the image
# dictionary) and then access the "channels" attribute.
coco_img = dset.coco_image(gid)
channels = coco_img.channels
print(f'channels={channels}')
all_channels.append(channels)
# You can build a histogram if you want:
import ubelt as ub
hist = ub.ddict(lambda: 0)
for channels in all_channels:
hist[channels.spec] += 1
print('hist = {}'.format(ub.repr2(hist, nl=1)))
[docs]def whats_the_difference_between_Images_and_CocoImage():
"""
Q. What is the difference between `kwcoco.Images` and `kwcoco.CocoImage`.
It's a little weird because it grew organically, but the "vectorized API"
calls like `.images`, `.annots`, `.videos` are methods for handling
multiple dictionaries at once. E.g. `dset.images().lookup('width')` returns
a list of the width attribute for each dictionary that particular `Images`
object is indexing (which by default is all of them, although you can
filter).
In contrast the `kwcoco.CocoImage` object is for working with exactly one
image. The important thing to note is if you have a CocoImage `coco_img =
dset.coco_image(1)` The `coco_img.img` attribute is exactly the underlying
dictionary. So you are never too far away from it.
Similarly for the `Images` objects: `dset.images().objs` returns a list of
all of the image dictionaries in that set.
"""
...