geowatch.tasks.dino_detector.predict module

SeeAlso:

• ~/data/dvc-repos/smart_expt_dvc/models/kitware/xview_dino/package_trained_model.py

Notes

# To test if mmcv is working on your machine:

python -c “from mmcv.ops import multi_scale_deform_attn”

class geowatch.tasks.dino_detector.predict.BuildingDetectorConfig(*args, **kwargs)

Bases: DataConfig

Valid options: []

Parameters:

• *args – positional arguments for this data config

• **kwargs – keyword arguments for this data config

default = {'batch_size': 1, 'coco_fpath': <Value(None)>, 'data_workers': 2, 'device': <Value(0)>, 'fixed_resolution': '1GSD', 'out_coco_fpath': <Value(None)>, 'package_fpath': <Value(None)>, 'select_images': None, 'track_emissions': True, 'window_dims': (1024, 1024), 'window_overlap': 0.5}

class geowatch.tasks.dino_detector.predict.WrapperDataset(subdset)

Bases: Dataset

geowatch.tasks.dino_detector.predict.main(cmdline=1, **kwargs)

Example

>>> # xdoctest: +SKIP
>>> from geowatch.tasks.dino_detector.predict import *  # NOQA
>>> import ubelt as ub
>>> import geowatch
>>> import kwcoco
>>> dvc_data_dpath = geowatch.find_dvc_dpath(tags='phase2_data', hardware='auto')
>>> dvc_expt_dpath = geowatch.find_dvc_dpath(tags='phase2_expt', hardware='auto')
>>> coco_fpath = dvc_data_dpath / 'Drop6-MeanYear10GSD-V2/imgonly-KR_R001.kwcoco.zip'
>>> package_fpath = dvc_expt_dpath / 'models/kitware/xview_dino.pt'
>>> out_coco_fpath = ub.Path.appdir('geowatch/tests/dino/doctest0').ensuredir() / 'pred_boxes.kwcoco.zip'
>>> kwargs = {
>>>     'coco_fpath': coco_fpath,
>>>     'package_fpath': package_fpath,
>>>     'out_coco_fpath': out_coco_fpath,
>>>     'fixed_resolution': '10GSD',
>>>     'window_dims': (256, 256),
>>> }
>>> cmdline = 0
>>> _ = main(cmdline=cmdline, **kwargs)
>>> out_dset = kwcoco.CocoDataset(out_coco_fpath)
>>> # xdoctest: +REQUIRES(--show)
>>> import kwplot
>>> import kwimage
>>> kwplot.plt.ion()
>>> gid = out_dset.images()[0]
>>> annots = out_dset.annots(gid=gid)
>>> dets = annots.detections
>>> list(map(len, out_dset.images().annots))
>>> config = out_dset.dataset['info'][-1]['properties']['config']
>>> delayed = out_dset.coco_image(gid).imdelay(channels='red|green|blue', resolution=config['fixed_resolution'])
>>> rgb = kwimage.normalize_intensity(delayed.finalize())
>>> import kwplot
>>> kwplot.plt.ion()
>>> kwplot.imshow(rgb, doclf=1)
>>> top_dets = dets.compress(dets.scores > 0.2)
>>> top_dets.draw()

geowatch.tasks.dino_detector.predict.dino_preproc_item(item)

geowatch.tasks.dino_detector.predict.dino_predict(model, batch)