- 15 Jan, 2021 1 commit
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DocGarbanzo authored
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- 11 Jan, 2021 1 commit
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Chris Anderson authored
Co-authored-by: Chris Anderson <gca2@earthlink.net>
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- 04 Jan, 2021 2 commits
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Chris Anderson authored
Co-authored-by: Chris Anderson <gca2@earthlink.net>
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Rahul Ravikumar authored
* - Update tensorflow version to 1.15.0 - Add doc for Jetpack 4.4 - Remove opencv installation * Add dataset and pre-trained model page * fix issue #634 (#646) - remove jquery dependency - add clearTimeout * Allow overriding WEB_CONTROL_PORT from env variable * pin h5py version * fix h5py version for mac * * Update doc with donkey train command. (#709) * Update doc with developer section for building own models in donkey 4.1 * Integrate changes from PR feedback Co-authored-by: Jonathan Tse <jonathan@tsez.net> Co-authored-by: Tawn Kramer <tawnkramer@gmail.com> Co-authored-by: DocGarbanzo <47540921+DocGarbanzo@users.noreply.github.com>
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- 29 Dec, 2020 3 commits
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wallarug authored
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Eric Wiener authored
* Added in PyTorch and PyTorch Lightning to train a DC model Successfully able to train a ResNet18-based model using PyTorch Lightning. * Removed hard-coded max number of epochs (used for debugging) * Added an inference transform to ResNet18 to convert PIL -> tensor * Unsqueezed input tensor during inference for batch dimension * Reshaped ResNet output from (1, 2) to (2,) * Added the ability to resume training from a checkpoint * Added helper print message when tensorboard logging is enabled * Updated docopt arguments for train.py. Made checkpoint optional * Changed TorchTubDataset from sub-classing Dataset to IterableDataset This was done in response to https://github.com/autorope/donkeycar/pull/706#discussion_r548137252 * Renamed load_image_arr to load_image. Updated load_pil_image load_pil_image will now handle converting the image to greyscale (vs. this being done in load_image). * Updated enviroments for Mac and Ubuntu. Set Python=3.7 * Updated installation documentation. Added script to setup Nano Updated the installation instructions for Ubuntu, Mac, and Windows. Clarified a common issue that occurs when running pip install -e .[pc] with ZSH. Also added a script to setup the Jetson Nano and updated the documentation for the Nano (it previously was installing tensorflow 1.x). * Added torch flag to setup.py to install pytorch * Moved pytorch training into base.py and removed from train.py * Moved Jetson Nano python package installation into requirements.txt * Formatted with PEP8 to clean up pytorch code * Updated docs to provide work-around for ZSH pip install -e .[pc] * Removed duplicate dependencies in conda env files * ResNet18 torch model now returns training loss history * Added test file for PyTorch training Still need to make sure this passes Travis CI. * Added lightning_logs to .gitignore * You can now specify the default AI framework to use in config.py This reduces the number of command line arguments you are required to provide. * get_model_by_type for PyTorch now lazy imports ResNet18 * Added help message to torch_train. Got rid of linear model type * Updated pytorch tests and fixed some syntax errors * ResNet18 example input shape updated to be (B, 3, 224, 224) Also now passing output_shape to load_resnet18 to modify how many output classes are used * No longer pinning requirement versions for Jetson Nano * Fixed formatting in setup.py
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Tim Gates authored
There is a small typo in docs/guide/host_pc/setup_windows.md. Should read `unfamiliar` rather than `unfarmilar`.
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- 23 Dec, 2020 1 commit
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DocGarbanzo authored
* Minor changes for 4.1 * Update conversion script to translate discontinuous data. * In developer guide add disclaimer for version and correct intra-page links. * * Update doc with donkey train command. * Update doc with developer section for building own models in donkey 4.1 * Integrate changes from PR feedback * Incorporate PR feedback * Add empty records concept to tub * Minor updates to conversion script * Incorporate PR feedback * Add empty record type into conversion script
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- 21 Dec, 2020 1 commit
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DocGarbanzo authored
* Add support for multi-dimensional model input and making the x, y interface symmetrical on the model / training interface: (#707) - x/y_transform extract x, y as numpy arrays or floats out of the record - x/y_translate convert the numpy arrays of floats into tf-readable dictionaries used in tf data. * Simplify model interface by implementing output_types() directly in the base class using output_shapes() dictionary. * Adding developer guide for own model development * Updated donkey command documentation * Improve asserts and type hints in keras.py * Added missing __init__.py in parts module. * Add cool ascii text for donkey init and update yml and setup files including mypy * Remove model training test from Travis and change the test to relative convergence. This avoids random fall overs in CI. * Added test of tf.data as used in the training pipeline through re-implementation of data transformation from tub records to tf expected dictionaries, for all currently supported models.
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- 17 Dec, 2020 1 commit
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DocGarbanzo authored
* Improve pipeline use: move from building list of pipelines of single transforms to building a single pipeline with a list of transforms (actually just looping through function to go from TubRecord -> image -> augment -> normalise -> x and TubRecord -> y). Fixed TfmIterators and TfmIterables. * Iterables are the containers and are sized - these are the user objects * Iterators are protocol objects to allow iteration, they have no logic and are local to the Iterables * build/map_pipeline both return sized Iterables * removed all batch logic, this is not required * still commented but left code that uses generator based pipeline as this is simpler code Using new small temporary pipeline generator * this keeps the TubSequence lazy and avoids to roll out the pipeline into a list * added a test to check consistency of the pipeline * remove empty (after moved) augmentation file * removed augmentation from old tub (as it's not needed and we removed the old augmentation) New pipeline changes: * moved augmentation into own class that is used above and can be used a threaded or non-threaded part * moved train functionality out of template and added 'donkey train', train.py just a simple dummy script for backward compatibility * Address code reviews: * Re-base on current dev to use un-altered sequence.py * Add iterator consistency test to pipeline tests * Undo changes in fast_stretch.py * better tf shape manipulation * small code improvements in training.py * remove sleep in augment part * Address code reviews: * Add clearing of tubrecord list and minor renamings
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- 16 Dec, 2020 1 commit
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Rahul Ravikumar authored
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- 13 Dec, 2020 3 commits
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DocGarbanzo authored
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DocGarbanzo authored
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DocGarbanzo authored
change the public mqtt server name to one that's listening
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- 12 Dec, 2020 3 commits
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Tawn Kramer authored
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DocGarbanzo authored
The telemetry mqtt test is breaking w/ a timeout on the connection to the server
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DocGarbanzo authored
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- 09 Dec, 2020 2 commits
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Rahul Ravikumar authored
* Implement a Lazy transformable pipeline. * Implement basic batching. However, this will need to be improved further for models with multiple outputs. * Replace the old `Sequence` implementation used with a new `Pipeline`. Test: Ran end to end tests.
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Meir Tseitlin authored
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- 01 Dec, 2020 1 commit
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Rahul Ravikumar authored
* This makes reading a 100x faster.
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- 08 Nov, 2020 4 commits
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DGarbanzo authored
Fix template docopt, as it's called managed.py and not drive.py
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sctse999 authored
- Update cfg_basic.py with simulator parameters
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sctse999 authored
Allow overriding WEB_CONTROL_PORT from env variable
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Jonathan Tse authored
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- 07 Nov, 2020 1 commit
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DocGarbanzo authored
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- 01 Nov, 2020 1 commit
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DGarbanzo authored
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- 28 Oct, 2020 1 commit
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wallarug authored
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- 25 Oct, 2020 1 commit
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wallarug authored
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- 24 Oct, 2020 2 commits
- 22 Oct, 2020 1 commit
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sctse999 authored
MakeMovie Utility Update - option for turning off line drawing
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- 21 Oct, 2020 2 commits
- 20 Oct, 2020 1 commit
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wallarug authored
add in --user flag for MakeMovie so that you can select if you want to draw the line on the video or not. default: true
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- 19 Oct, 2020 2 commits
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DGarbanzo authored
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wallarug authored
Added more options for Installing Donkey Car on Windows. - Anaconda - Native - Windows Subsystem for Linux (WSL) - experiential These options give more flexibility and could make deployment easier for some individuals. I personally always install donkey car natively onto Python installed on the System. I will be looking more into WSL going forward as it has some interesting benefits.
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- 18 Oct, 2020 3 commits
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Rahul Ravikumar authored
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Rahul Ravikumar authored
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Rahul Ravikumar authored
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- 17 Oct, 2020 1 commit
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Rahul Ravikumar authored
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