Comments (2)
I just merged #51 that fixes the issue you reported and some other things. I was able to get python -m rastervision.run experiments/semseg/4_20_17/fcn_0.json
to run without errors using the following updated experiment file. Remember that experiment files aren't backward compatible, so to get it to run with the develop
branch, I made some necessary changes which were
"problem_type": "semseg",
"dataset_name": "isprs/potsdam",
I also made various changes so it would run quickly for testing purposes.
{
"batch_size": 1,
"problem_type": "semseg",
"dataset_name": "isprs/potsdam",
"generator_name": "numpy",
"active_input_inds": [3, 0, 1],
"use_pretraining": false,
"freeze_base": false,
"train_stages": [
{
"epochs": 1,
"init_lr": 1e-5
},
{
"epochs": 2,
"init_lr": 1e-6
}
],
"kernel_size": [5, 5],
"train_ratio": 0.8,
"optimizer": "adam",
"target_size": [256, 256],
"eval_target_size": [2000, 2000],
"nb_eval_samples": 1,
"nb_eval_plot_samples": 1,
"model_type": "conv_logistic",
"run_name": "semseg/4_20_17/fcn_0",
"validation_steps": 1,
"steps_per_epoch": 1
}
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Thanks for the bug report and sorry for any inconvenience. When we get the time, we'd like to come up with a better testing strategy.
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Related Issues (20)
- Support reading temporal data (i.e. time-series of multiple images of the same scene)
- Can't use a geojson as AOI in a SemanticSegmentationRandomWindowGeoDataset HOT 3
- ARM64 build currently broken HOT 1
- Unable to install RasterVision HOT 3
- Issues with using model bundle for prediction HOT 15
- Cannot import ClassConfig on Kaggle HOT 16
- Cannot save prediction using colors from ClassConfig HOT 4
- Improve unit test coverage of CLI and `Runner`s
- Cannot plot batch with ObjectDetectionVisualizer HOT 4
- Multi-temporal raster source visualizer fails when batch size is 1 HOT 2
- Make it possible to exclude "null" class labels from the computation of metrics HOT 3
- RuntimeError: expected scalar type Long but found Int HOT 10
- Allow user to specify AOI box filtering behavior in sliding window datasets HOT 1
- self._hds cannot be converted to a Python object for pickling HOT 2
- Semantic Segmentation Labels not initializing properly from predictions when extent provided HOT 2
- use my trained modle to prediction ,has wrong happened HOT 2
- RuntimeError: The size of tensor a (82) must match the size of tensor b (64) at non-singleton dimension 3 HOT 4
- Migrate to `pydantic` v2
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