PTLFlow

Getting started:

  • Installation
  • Predict optical flow with a pretrained model
  • Run validation on a model
  • Train an existing model
  • Predicting optical flow on test datasets
  • Using config files
  • Model Benchmarking
  • Changes from PTLFlow v0.3 to v0.4

Models:

  • List of available models
  • Checkpoint List

Datasets:

  • List of supported datasets

Results:

  • Accuracy - EPE
  • Accuracy - EPE and Fl-All
  • Model benchmark
  • Paper/PTLFlow metrics
  • Result plots

Customizing:

  • Adding a new model
  • Adding a new dataset

API:

  • train_dataset and val_dataset
  • scripts
  • ptlflow.models
  • ptflow.data
  • ptlflow.utils
PTLFlow
  • Overview: module code

All modules for which code is available

  • infer
  • model_benchmark
  • ptlflow.data.datasets
  • ptlflow.data.flow_transforms
  • ptlflow.models.base_model.base_model
  • ptlflow.utils.callbacks.logger
  • ptlflow.utils.correlation
  • ptlflow.utils.dummy_datasets
  • ptlflow.utils.flow_metrics
  • ptlflow.utils.flow_utils
  • ptlflow.utils.flowpy_torch
  • ptlflow.utils.io_adapter
  • ptlflow.utils.timer
  • ptlflow.utils.utils
  • summary_metrics
  • validate

© Copyright 2024, Henrique Morimitsu.

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