* store/send mic audio with toggle
* script to extract audio from logs
* change description and add translation placeholders
* microphone icon
* apply toggle in loggerd
* add legnth and counter
* startFrameIdx counter
* Revert "change description and add translation placeholders"
This reverts commit 7baa1f6de99c6ebe9f9906193da7e83dad79511a.
* send mic data first and then calc
* restore changed description/icon after revert
* adjust fft samples to keep old time window
* remove extract_audio.py since audio is now stored in qcam isntead of rlog
* qt microphone recording icon
* Revert "remove extract_audio.py since audio is now stored in qcam isntead of rlog"
This reverts commit 7a3a75bd8db5376d1e442a3ba931c67550b5f132.
* move extract_audio script and output file by default
* remove length field
* recording indicator swaps sides based on lhd/rhd
* use record icon from comma body
* Update toggle description
Co-authored-by: Adeeb Shihadeh <adeebshihadeh@gmail.com>
* update raylib toggle desc cause I did earlier
* microphone --> soundPressure, audioData --> rawAudioData
* cleanup unused var
* update README
* sidebar mic indicator instead of annotated camera
* improve logic readability
* remove startFrameIdx and sequenceNum
* use Q_PROPERTY/setProperty so that update() is actually called on value change
* specify old id for SoundPressure
* fix typo
---------
Co-authored-by: Adeeb Shihadeh <adeebshihadeh@gmail.com>
* Add calPerc field and torque progress
* Fix torqued test style and CarParams usage
* test: remove unused numpy import
* move here
* trying all combinations to see what's most linear
* clean up with best method
* no no
* epic
* clean up
* last min not needed
* doesn't hurt
* list comp
* init
* some fixes
* move
* more
* old navd helpers
* bring back cereal
* fix linting
* more
* add to cereal first
* sp events
* lint
* implement in long plan
* fixme-sp
* refactor state machine
* wrong state
* start refactor controller
* some type hints
* init these
* enable debug print
* ui? ui!
* print them out
* fix spinner import
* fix path
* let's use gps chips directly for now
* service missing
* publish events
* no nav for now
* need to sub
* no car state speed yet
* missed event
* Car: `CarStateSP`
* fix tests
* bring back car state speed limit
* fix
* use old controller for now
* fix
* fix source
* type hints
* none for now
* formatting
* more
* create directory if does not exist
* mypy my bt
* policy param catch exceptions
* handle all params with exceptions
* more
* single method
* define types in init
* rename
* simpler op enabled check
* more mypy stuff
* rename
* no need for brake pressed
* don't reset if gas pressed
* type hint all
* type hint all
* back to upstream
* in another pr
* no longer need data type
* qlog
* slc in another pr
* use horizontal accuracy
* set core affinity for all realtime processes
* unused
* sort
* unused
* type hint and slight cleanup
* from old implementation
* use directly
* combine pm
* slight more cleanup
* type hints
* even more type hint
* lint
* more cleanup
* even less
* license
* Refactor model runner methods for improved abstraction.
Moved slicing logic to a private `_slice_outputs` method and decoupled `_run_model` for clearer subclass implementation. Removed redundant `output` attribute in `ModelState` to streamline data handling.
* Add output parsing to model_runner and remove duplicate logic
Integrates an output parser directly into `model_runner` for streamlined inference and parsing. Removes redundant parser initialization from `modeld` to avoid duplication and enhance maintainability.
* Reordering
* linter
* linter
* Refactor model handling with `ModelData` abstraction
Introduce a `ModelData` class to encapsulate model and metadata logic, improving code clarity and modularity. Refactor `ModelRunner` to manage multiple models and add conditional handling for fallback scenarios. Adjust `TinygradRunner` to validate and use the new `ModelData` structure.
* Refactor model handling to use dictionary-based structure
Replaces the model list with a dictionary keyed by model type to improve clarity and maintainability. Updates related logic and ensures consistent handling of model metadata and inputs. Adds `slice_outputs` implementation to the `TinygradRunner` for proper output parsing.
* Refactor model runners to support policy and vision separation
Introduced `TinygradPolicyRunner`, `TinygradVisionRunner`, and `TinygradSplitRunner` to enable separate handling of policy and vision models. Updated `TinygradRunner` initialization and input preparation to accommodate modular processing. Adjusted `modeld` to utilize the new runners, ensuring compatibility with separated model workflows.
* Refactor model runner initialization and simplify logic
Introduce `get_model_runner` to centralize model runner selection logic, replacing multiple conditional instantiations. Simplify the handling of model metadata by removing fallback logic and restructuring output slicing to enforce proper loading of model data. These changes improve code maintainability and clarity.
* Refactor model data access for TinygradRunner initialization
Update references to access nested artifact properties and align with structural changes to the model data schema. This simplifies input shapes handling and ensures compatibility with updated model attributes.
* Refactor imports and clean up redundant code.
Removed unused imports and improved formatting for clarity and maintainability. These changes simplify the codebase by eliminating unnecessary dependencies and ensuring consistency.
* Refactor model output parsing with specialized parsers.
Introduce abstract `_parse_outputs` method to standardize parsing logic. Add `SplitParser` for specialized parsing in `TinygradVisionRunner` and `TinygradPolicyRunner`. This improves modularity and paves the way for easier parser customization.
* Add parser for model output processing in modeld_v2
Introduce a new `Parser` class to handle parsing and processing of model outputs, including MDN, binary cross-entropy, and categorical cross-entropy outputs. This modularizes the logic, improves clarity, and prepares for handling various types of model data.
* Add `input_shapes` property to model runners
Introduce a new `input_shapes` property in the abstract base class and its implementation in derived classes. This provides a standardized way to access the input shapes of models, improving clarity and consistency in the model runners.
* Refactor model runner to use private `_model_data` attribute
Replaced public `model_data` with private `_model_data` for improved encapsulation. Updated all references and property accessors accordingly. Simplified model type handling by using raw types where applicable.
* Remove debug print statement from model_runner.py
The unnecessary `print(model_type)` statement was removed as it served no functional purpose in the code. This improves code cleanliness and avoids unintended console output during execution.
* Refactor `_parse_outputs` call in `run_model`.
Replaced the use of `self.parser.parse_outputs` with `self._parse_outputs` for clarity and consistency. Updated method signature to align with the revised usage.
* Refactor model output parsing for clarity and scope separation
Moved specific parsing logic (e.g., lane_lines, lead) from `parse_model_outputs` to `parse_policy_outputs` to better align with functional responsibilities. This improves modularity and readability while maintaining existing functionality.
* Refactor model_runner to simplify result handling
Renamed variable `result` to `parsed_result` for clarity and removed unnecessary slicing during model output parsing. These changes improve code readability and maintain consistency within the `run_model` method.
* Adjust _parse_outputs method signature in model_runner
Updated the method signature of _parse_outputs to accept a single np.ndarray instead of a dictionary. This aligns with the intended data structure and ensures consistency across subclasses implementing this abstract method.
* Refactor ModelRunner to enforce abstract base class compliance
Updated `ModelRunner` and its subclasses to properly inherit from `ABC` while refactoring methods to ensure compliance with Python's abstract base class standards. Streamlined the handling of `_parse_outputs` and added a new `input_shapes` property for improved functionality.
* Fix buffer length issue in 20Hz model initialization
Adjusted `FULL_HISTORY_BUFFER_LEN` by adding +1 for `full_features_20Hz` to address compatibility issues with the current FoF model. Added a comment noting potential failure for other models with this adjustment.
* Refactor TinygradRunner to remove abstract methods.
Simplified the TinygradRunner class by removing unnecessary @abstractmethod decorators and redundant method definitions. This streamlines the code and aligns it more effectively with its current usage and implementation.
* Refactor model runner classes and enhance type annotations
Simplified model runner implementations, added type annotations, and improved code readability and maintainability. Introduced new type definitions, updated metadata handling, and standardized input/output parsing across all runner classes. Minor comment update in `modeld.py` for clarity.
* Refactor model runner classes with detailed docstrings.
Enhanced class and function docstrings across model_runner.py for better clarity and maintainability. Descriptions now include detailed explanations of attributes, purposes, and workflows to aid understanding and future development.
* Refactor model runner classes and add TICI hardware optimization
Simplified and clarified class definitions, comments, and functionality for ModelRunner subclasses. Introduced the use of QCOM environment variable on TICI for potential hardware acceleration. Enhanced input/output handling and error reporting across Tinygrad and ONNX implementations.
* Update parser import and usage to use CombinedParser
Replaced the Parser class with CombinedParser in model_runner.py. This change ensures consistency with the updated parsing logic, aligning with the latest requirements for combined model output handling.
* Refactor TinygradRunner hierarchy for modular parsers
Reorganized the TinygradRunner and its specialized runners (Vision, Policy, and Supercombo) into a cleaner, modular structure using composable classes. This consolidates parser logic, removes redundancy, and simplifies initialization by leveraging a shared base class with a dictionary-based parser method.
* Refactor model runners to use ModularRunner as abstract base.
Introduce a new `ModularRunner` class to enforce a consistent interface across model runners. Updated existing runners, including `ModelRunner`, `SupercomboTinygrad`, `PolicyTinygrad`, and `VisionTinygrad`, to extend `ModularRunner`. Added abstract methods and properties to enhance modularity and code maintainability.
* Refactor model runners into modular components.
This commit separates the logic for Tinygrad, ONNX, and split runners into clearly defined modules and components. It introduces `PolicyTinygrad`, `VisionTinygrad`, `SupercomboTinygrad`, and centralized helpers for cleaner architecture. The changes improve modularity and maintainability of the model running and parsing workflows.
* Simplify imports and clean up unused code in ONNXRunner.
Removed unused imports and redundant environmental variables to streamline the codebase. Consolidated necessary imports and organized type definitions for improved readability and maintenance.
* Standardize imports and add model data validation.
Updated import paths to ensure consistency across modules by using `openpilot` as the base. Introduced validation in `_parse_outputs` methods to handle cases where `_model_data` is not initialized, preventing potential runtime errors.
* Remove unused import and fix whitespace in runners
The unused import `ModelData` was removed from `tinygrad_runner.py` to clean up the code. Additionally, extraneous whitespace was corrected in `onnx_runner.py` for improved readability and consistency.
* Remove unnecessary blank line in import statements
Cleaned up import section by removing an extra blank line. This helps maintain consistency and adheres to code style conventions.
* BROKEN!! Staging code but its not gonna work. Also I realized we need to run the split models in 2 stages because the output of one is immediately needed for the input of the other. We might handle it inside of the model_runner instead
* update smooth
* Revert "update smooth"
This reverts commit c335712e6e1ee189459ce34dfc9d4028feb9470f.
* match case made this very hard to read.
* shouldnt be there
* Refactor to allow TR (soon TM)
* TR 7 is .1
* metadata
* .2=3
* Remove redundant comments and clean up conditional blocks in modeld.py.
* Undoing wrong buffer
* Refactor model initialization and adjust ONNX runner import
Reorganized numpy input buffer initialization and updated `temporal_idxs` logic for better clarity and efficiency. Conditional import for ONNXRunner added for non-TICI platforms to optimize imports. These changes improve maintainability and compatibility across platforms.
* Update CURRENT_SELECTOR_VERSION to 4
Bump the CURRENT_SELECTOR_VERSION constant from 3 to 4 to reflect changes in the selector logic or requirements. This ensures compatibility with the updated selector version while maintaining the minimum required version as 2.
* Add output_slices property to model runners
Introduce output_slices property to provide access to the output slices for individual and combined models. This ensures consistent handling of output slices across vision and policy models, improving modularity and usability.
* Refactor imports to use SplitModelConstants consistently
Updated import references to use the renamed `SplitModelConstants` class for consistency across files. This change ensures clarity and better alignment with the updated class naming convention.
* Refactor buffer initialization and desired curvature handling
Refactored model input buffer initialization for improved clarity and consistency, leveraging dynamic shape calculations. Extracted `process_desired_curvature` method to encapsulate logic for handling 3D and non-3D cases. Simplified temporal index generation and related calculations for better maintainability.
* Refactor desire reshape dims logic in modeld.py
Adjust logic for setting desire reshape dimensions to handle `is_20hz_3d` separately. This improves clarity and ensures proper handling of different model runner configurations.
* Fix off-by-one error in full_desire buffer initialization
The full_desire buffer length was mistakenly set to full_history_buffer_len + 1. This change corrects it to match the intended full_history_buffer_len, ensuring proper alignment with other buffers.
* Simplify desire reshape logic by removing unused condition.
Removed the `is_20hz_3d` condition and associated reshape logic since it is no longer needed. This streamlines the code and avoids unnecessary checks for unused configurations.
* Refactor buffer initialization for 20Hz model variants
Reorganized buffer initialization logic to prioritize the 20Hz_3D condition. This improves clarity and ensures specific handling of different 20Hz configurations. Adjusted the order of conditions to streamline execution flow.
* Refactor: Move `get_action_from_model` and constants to `Model` class to improve encapsulation and readability.
* 12 line reshaping red diff
* .2 to match old models delay
* mypy fixes
* Revert "12 line reshaping red diff"
This reverts commit 8c7280f629043f0485749e2536a20af74c9209b2.
* mypy
* remove this
* Fix desired curvature for models which do not output desired_curvature
* fix FoF
* flip policy and vision outs to allow FoF and tomb raider to live in harmony using conditional `if 'this' in outs:'`
* noqa
* single
* sunnypilot modeld.py
* action
* overrides methodology
* combine split outputs to its own method
* comments
* Fix static checker line length
* static will fail on line length
lines:
286,
206,
70 - 77,
159,
168
* Address E501 line length violations
* This will make TR better while not effecting FoF/VFF at all
* Reduce this to one conditional and just call normally in vision/policy
* Align with upstream in our own way.
* check for desired curvature in outputs first
* outputs
* Use a cleaner import method
* Fix output
* Clean up some values
* Only call on init
* slight cleanup
* names!!!!!!!!!
* Refactor overrides structure to support key-value pairs.
The overrides structure now uses a list of key-value pairs instead of fixed lat/long fields. This change improves flexibility, allowing dynamic addition of override parameters. Code adjustments ensure backward compatibility and consistent behavior throughout the application.
* Refactor: Use local variable for SplitModelConstants
Introduce a local `constants` variable to replace repeated access to `SplitModelConstants`. This simplifies code readability and adheres to linter recommendations for line length.
* Refactor model constant handling to improve modularity
Replaced direct usage of model constants with dynamic access through model runners for better scalability and maintainability. This change centralizes constant definitions, reduces redundancy, and ensures clearer integration with different model types.
---------
Co-authored-by: discountchubbs <alexgrant990@gmail.com>
Co-authored-by: Discountchubbs <159560811+Discountchubbs@users.noreply.github.com>
Co-authored-by: Jason Wen <haibin.wen3@gmail.com>
* car: initialize sunnypilot interface immediately
* init
* Revert "car: initialize sunnypilot interface immediately"
This reverts commit 2e0fc4d87eb312a3a74a61bb8cbc780e33efbfc7.
* show int
* show int
* work properly with cereal
* unused
* in its own module
* bump
* not yet
* not yet
* list comp and use structs directly
* allow default key if needed
* lint
* send it with None
* bump
* MADS: Refactor Unified Engagement Mode
* init
* bring back pedal pressed event while trying to engage long
* MADS: prep for refactor
* no longer
* this is cleaner?
* in another pr
Used to ship python UI in agnos without an openpilot clone
* add a main method to target
* pack script
* validate inputs
* refactors
* copy into temp, dont keep this
* cleanup
* help messages
* rename to pack.py
* pack.py
* updates for device
* moar
* don't use cereal
* just log normally
* use importlib.resources
* revert
* Revert "don't use cereal"
This reverts commit 7208524d422d88a1b07e209359aeb25e8b3bf4e7.
* fix cereal?
* cleanup
* Revert "cleanup"
This reverts commit 921edfe5020f244dbdf4f26767af7c98ca837d1c.
* cython hotfix
* Reapply "cleanup"
This reverts commit 9b54552f784dea1b1eb4ffc03937571e4fc851ba.
* more cleanup
* any script?
* slightly clearer
* rm print
* nothing python should use SVGs
---------
Co-authored-by: Trey Moen <trey@moen.ai>
* Add enhanced HyundaiCAN extension
Introduced HyundaiCanEXT for improved object parsing and control integration, leveraging new fields like lead distance and relative speed in CarControlSP.
Refactored controlsd to utilize a modular design with ControlsdExt for additional sunnypilot specific functionality.
* self.cc_sp
* Refactor CarControlSP handling for improved state updates
* refactor
* bool
* Refactor controlsd SP communication logic
Update `publish_sp` method to include `CC_SP` parameter and refine SP SubMaster to exclude `radarState`. Remove custom lead vehicle state processing as it is no longer needed.
* remove in this pr
* bump
* start cleanup
* inherit instead
* even more!
* lint
* type hint
* use the same objects for submaster and pubmaster
* more
---------
Co-authored-by: Jason Wen <haibin.wen3@gmail.com>
* feat: Show alert on user flag event
* feat: Temporarily update border status on user flag to match connect timeline
* Revert "feat: Temporarily update border status on user flag to match connect timeline"
This reverts commit f1da6a4f5f555d4db50b47fb68ce74ae7737b8af.
* feat: Increase alert duration to 1.5 seconds
* remove audible alert for bookmark event
* refactor: Use NormalPermamentAlert for user flag alert
* fix: Update userFlag enum value in OnroadEvent struct
* fix: Handle userFlag event even in dashcam mode
* don't need to ignore that anymore
* remove 'userFlag' from ignore list
---------
Co-authored-by: Jason Young <jyoung8607@gmail.com>
* messaging: fix bug with relaxed checks under simulation
* refactor
* cleanup
* fix bug
* Revert "fix bug"
This reverts commit ea31f3ee83676c5b8ffe57500881557f7586998c.
* that did need to be different
* fix bug, add test coverage
* retry CI
* Refactor model and artifact structures with version compatibility filtering
- Introduced `Artifact` struct and nested it within the `Model` struct for improved clarity and organization.
- Updated enums, logic, and parsing to align with the new struct definitions.
- Implemented version compatibility filtering for model bundles using the `is_bundle_version_compatible` helper.
- Enhanced artifact download handling by adding checks for missing URIs, better error management, and improved logging.
- Adjusted model fetching to point to the latest endpoint (`v3`).
* Make linter happy
* Make linter happy
* Refactor model data parsing to improve readability.
Replaced kwargs-based data extraction with explicit parameter passing for clarity. This enhances code readability and reduces ambiguities in method calls, making the parsing logic more maintainable and straightforward.
* Refactor error handling in active model bundle retrieval.
Wrapped the logic to fetch the active model bundle in a try-except block to prevent unhandled exceptions. This ensures more robust error handling and avoids potential crashes when retrieving or processing model data.
* Refactor exception handling in get_active_model_bundle
Replace bare except with Exception to improve specificity and clarity. This ensures better debugging practices and aligns with recommended coding standards. Other minor whitespace adjustments were made for improved readability.
* Update model path to use artifact fileName property
Replaced `fileName` with `artifact.fileName` in the custom model path construction. This ensures compatibility with updated drive model structures and avoids potential file resolution issues.
* Online lateral lag learning (#34974)
This reverts commit b4cc9e68d1.
* pad to the best size for fft
* Fix static analysis
* Add typing
* Fix typing
* MAX_LAG
* Calculate cross correlation regardless if the points are valid
* Back to lagd
* Add lagd to process_config
* Lagd in test onroad
* Move lag estimator for lagd
* Remove duplicate entry from test_onroad
* Update process replay
* pre-fill the data
* Update cpu usage
* 25sec window
* Change the meaning of lateralDelayEstimate
* No newline
* Fix typing
* Prefill
* Update ref commit
* Add a unit test
* Fix static issues
* Time limit
* Or timeout
* Use mocker
* Update estimate every time
* empty test
* DT const
* enable RIVIAN again
* Update ref commit
* Update that again
* Improve the tests
* Fix static
* Add masking test
* Increase timeout
* Add liveDelay to selfdrived
* Add liveDelay to selfdrived in process_replay
* Fix block_avg restore after num_blocks
* regen most
* Update bolt
* Update ref commit
* Change the key name
* Add assert
* True weighted average
* MADS: prevent `wrongCarMode` from disabling MADS enabled state
Add wrongCarModeNoEntry as a NO_ENTRY event to replace wrongCarMode (USER_DISABLE)
that would incorrectly disable MADS when in the wrong car mode. Provides
contextual guidance to users based on car brand, showing appropriate
instructions for re-engagement without requiring MADS to be re-enabled.
* move down
* warning only?
* cereal SIKE
* remove duplicate
* try this out
* final
* Add struct and services
* Proof of concept
* Use vego
* Process replay support
* Fix issues
* Max not min
* Remove print
* Make lag positive
* Points and updates
* Sliding cross corr
* Stuff
* Remove redundant param
* Move to lagd
* Update alert
* Something that works
* Report isEstimated
* Corr field
* Use skimage masked corr
* Fixes
* Move to lat_accel_loc
* Use the delay it in the model
* Mark as executable
* Add 0.2 to initial
* add install line
* Back to 5m window
* Move the import up
* corr window 120
* Show is estimated
* Sort messages
* New impl
* Fix
* Params
* Set initial_lag elsewhere
* Add param
* Rename Param
* Fix type isues
* More blocks
* Masked fft NCC implementation
* Remove package installation
* Use 20hz data and interp the correlation peak
* Move ncc code to separate function
* steering_saturated support
* Constants
* Add recovery buffer
* Fix static
* min_valid_block_count nad liveDelay
* lateralDelayEstimate
* Fix comm issues. Do estimations at 4hz
* Fix
* Display the estimate
* Increase the block size
* Cache every minute
* DEBUG flag
* Add progress to the alert
* Fix crash
* points only in debug
* Fix BlockAverage restoration
* Comment
* Move estimators into estimator directory
* Remove lagd
* Feed only relevant messages
* Rewrite as a set literal
* np.diag with P_initial
* Fix static
* Struct renames
* Update ref commit
* Make it nicer
* Some renames
* Refactor OnroadEventSP structure to contain list of events
A restructuring of the OnroadEventSP structure has been undertaken to accommodate a list of 'Event' substructures. The change is reflected in different files where OnroadEventSP is used. This update allows for more efficient management of multiple events by grouping them together under the revised OnroadEventSP structure.
* Rename `OnroadEventSP` to `OnroadEventsSP` across codebase.
Updated all references to `OnroadEventSP` to ensure consistency with the renamed struct `OnroadEventsSP`. This change improves code clarity and aligns naming conventions across modules.
* Add optional debug logging to schema validation script
Introduced a `DEBUG` flag and a `print_debug` function to streamline debug output management. This replaces direct `print` calls with conditional logging to control verbosity during execution.
Refactor structural validation logic in cereal test
Simplify the iteration over read_instances to streamline structural validation. Removed redundant comparisons and improved error handling to detect unreadable fields more effectively. Updated error messages for better clarity during debugging.
Update build command to include 'cereal' target in CI
Modified the scons build command in selfdrive_tests workflow to explicitly build the 'cereal' target. This ensures necessary components are included during the CI process, improving reliability and consistency.
Added workflow for cereal validation artifacts generation and validation against upstream
This commit encompasses significant changes to .github/workflows/selfdrive_tests.yaml, including the addition of two new jobs. One is responsible for 'Generating cereal validation artifacts' and the other for 'Validating cereal with Upstream'. This includes generating cereal schemas, building openpilot, and running validation schema instances against master. Furthermore, a new Python script (validate_sp_cereal_upstream.py) was also added to perform cereal schema instance generation and validation. These changes aim to enhance the testing process, ensuring schema compatibility and integration quality.
* Relocate cereal validation to a dedicated GitHub workflow
This commit introduces a distinct GitHub workflow for cereal validation named 'cereal_validation.yaml'. This workflow includes two jobs: one for generating cereal validation artifacts and another for validating cereal with the upstream project. Previously, these operations were included as separate jobs in 'selfdrive_tests.yaml'. However, the decoupling in this commit allows for a better organization of GitHub workflows within the project. Additionally, this separation allows these workflows to be individually configured and run, providing a greater degree of flexibility in managing our continuous integration activities.
* Rename workflow to "cereal validation" for clarity.
Updated the workflow name in the GitHub Actions configuration to better reflect its purpose. This change improves maintainability and ensures clearer identification of the workflow's function.
* Add LFS configuration and GitLab SSH setup to workflow
Integrate GitLab LFS handling by configuring LFS URLs and enabling SSH setup. This includes adding public GitLab keys and updating the workflow to support secure connections for LFS operations. Ensures proper handling of large files and seamless integration with GitLab.
* rename
* format
---------
Co-authored-by: Jason Wen <haibin.wen3@gmail.com>
* Add AES encryption and utility methods
This commit introduces a new AESCipher class that can be used for AES encryption with support for both AES-128 and AES-256. It also adds a set of utility functions, including methods for RSA to AES key derivation, file decryption and compression, and encryption and decompression. These changes provide fundamental cryptographic functionalities for data security within the system.
* Revised backup management system with new structures
This update introduces important revisions to the backup management system. A new struct named 'BackupManagerSP' has been integrated into the 'custom.capnp' file, replacing 'CustomReserved6'. This new struct includes several variables that help keep track of backup and restore status, progress and related messages.
Additional code modifications were made in 'base.py' and 'api.py' to include a 'json' parameter in the 'api_get' method. Lastly, 'manager.py' has been updated with functions to manage device configuration backups to and from sunnylink.
The changes promote better handling and management of data backup and restoration processes. The update is specifically designed to ensure that the backup information is well integrated into the system, with properly tracked status and progress.
* Refactor `allKeys` to filter by parameter key type
Updated the `allKeys` method to support filtering by `ParamKeyType`, allowing more specific key retrieval. Added a default value for backward compatibility and updated related bindings and keys to reflect this change.
* Improve Backup and Restore mechanisms
The commit refactors and improves several aspects of the backup and restore mechanisms in the `BackupManagerSP` class.
These improvements include removing redundant status tracking variables and replacing them with unified ones, updating the messaging system to handle all changes correctly, and including an enumeration `OperationType` to keep track of the type of operation currently being processed.
This commit also applies stricter conditions for restore operations, such that it only restores parameters that are currently marked as backupable, and skips those that are not. This is a preventive measure against potential issues when restoring parameters that are no longer relevant or could conflict with current versions.
Also, the encryption and decryption methods were updated to use AES-256 for more security. These changes have increased the robustness and reliability of the backup and restoration processes.
* copyright
* Add backup_manager process to offroad sunnypilot tasks
The backup_manager process is introduced to handle backups during offroad mode when SunnyLink is ready. This ensures proper backup management functionality integrated into the system.
* Simplify backup endpoint construction in restore method
Replaced conditional expression with a more concise and readable `or` operation for constructing the backup endpoint. This makes the code cleaner and easier to maintain while preserving functionality.
* Added support for backing up and restoring sunnypilot settings
An update to the sunnypilot functionality now provides two new features that allow users to backup and restore their sunnypilot settings. The changes include the addition of UI controls for initiating backup and restore operations, and the creation of a system-wide state management function for tracking these operations. This enhancement significantly improves the user experience by providing a safety net for user settings in case of software failures, bugs, or unintended changes.
* Refactor type hints to use PEP 604 syntax for clarity
Replaced `Optional` and `Dict` type hints with `|` and `dict` syntax for improved readability and compliance with Python 3.10+. Updated related imports and adjusted list comprehension for cleaner code.
* Update import path for hardware module in utils.py
Replaced the import path for the `Paths` module to align with the new directory structure under `openpilot`. This ensures compatibility with recent project reorganization and avoids import errors.
* Improve RSA key handling and fix backup status comparison
Added explicit RSA key type checks to handle invalid key formats. Enhanced type safety in `manager.py` by ensuring the backup status comparison returns a boolean. These changes improve robustness and error handling in backups.
* format
* more
* Improve backup and restore flow with progress tracking and fixes
Added proper progress tracking and cleanup logic during restore operations. Enhanced restore experience by resetting progress after completion and introducing confirmation dialogs for errors and completion. Updated API compatibility with a version query parameter for backups.
* Enable backup button only when restore process is complete
Previously, the backup button could be enabled during a restore operation, which might cause unintended behavior. This update introduces a check to ensure the backup button remains disabled while a restore process is active. This improves user experience and prevents potential conflicts.
* Fix restore button state handling during restore process
Ensure the restore button is disabled consistently when a restore is in progress. This prevents user interaction issues and aligns the button state with the restore operation status.
* "Refactor restore logic and improve button state handling"
Replaced `is_restoring` with `restore_request_pending` for clarity and better state management. Adjusted button behavior to immediately disable upon user action, ensuring improved UX and preventing repeat inputs. Refined restore completion flow for better consistency and reliability.
* Refine restore process logic for SunnyLink settings.
Introduced `restore_request_started` to improve handling of restore states and ensure accurate UI updates during the process. Adjusted case handling to enhance clarity and maintain proper behavior when restoring settings, especially during ongoing or completed requests.
* revert
* move around
* fix enabled states for different statuses
* add prompt to notify backup is complete
* same states as restore
* disable buttons if sunnylink is off
* can use the same texts
---------
Co-authored-by: Jason Wen <haibin.wen3@gmail.com>
* init
* more init
* keep it alive
* fixes
* more fixes
* more fix
* new submodule for nn data
* bump submodule
* update path to submodule
* spacing???
* update submodule path
* update submodule path
* bump
* dump
* bump
* introduce params
* Add Neural Network Lateral Control toggle to developer panel
This introduces a new toggle for enabling Neural Network Lateral Control (NNLC), providing detailed descriptions of its functionality and compatibility. It includes UI integration, car compatibility checks, and feedback links for unsupported vehicles.
* decouple even more
* static
* codespell
* remove debug
* in structs
* fix import
* convert to capnp
* fixes
* debug
* only initialize if NNLC is enabled or allow to enable
* oops
* fix initialization
* only allow engage if nnlc is off
* fix toggle param
* fix tests
* lint
* fix more test
* capnp test
* try this out
* validate if it's not None
* make it 33 to match
* align
* share the same friction input calculation
* return stock values if not enabled
* unused
* split base and child
* space
* rename
* NeuralNetworkFeedForwardModel
* less
* just use file name
* try this
* more explicit
* rename
* move it
* child class for additional controllers
* rename
* time to split out custom lateral acceleration
* move around
* space
* fix
* TODO-SP
* TODO-SP
* update regardless, it's an extension now
* update name and expose toggle
* ui: sunnypilot Panel -> Steering Panel
* Update selfdrive/ui/sunnypilot/qt/offroad/settings/lateral_panel.h
* merge
* move to steering panel
* no need for this
* live params in a thread
* no live for now
* new structs
* more ui
* more flexible
* more ui
* no longer needed
* another ui
* cereal changes
* bump opendbc
* simplify checks
* all in one place
* split Enhanced Lat Accel
* handle unrecognized platform
* test for fingerprinting
* fix fingerprint
* NNLC: Mock data for unrecognized cars
* fix fingerprints
* test to verify model loading
* bump neural_network_data
* use pytest
* use different one for now
* fix ui preview alignments
* typing
* more type
* show a platform
* show match
* init params for tests
* ok ruff
* make sure to loop through tests
* ok again ruff
* ok we need this lol
---------
Co-authored-by: DevTekVE <devtekve@gmail.com>
* init
* more init
* keep it alive
* fixes
* more fixes
* more fix
* new submodule for nn data
* bump submodule
* update path to submodule
* spacing???
* update submodule path
* update submodule path
* bump
* dump
* bump
* introduce params
* Add Neural Network Lateral Control toggle to developer panel
This introduces a new toggle for enabling Neural Network Lateral Control (NNLC), providing detailed descriptions of its functionality and compatibility. It includes UI integration, car compatibility checks, and feedback links for unsupported vehicles.
* decouple even more
* static
* codespell
* remove debug
* in structs
* fix import
* convert to capnp
* fixes
* debug
* only initialize if NNLC is enabled or allow to enable
* oops
* fix initialization
* only allow engage if nnlc is off
* fix toggle param
* fix tests
* lint
* fix more test
* capnp test
* try this out
* validate if it's not None
* make it 33 to match
* align
* share the same friction input calculation
* return stock values if not enabled
* unused
* split base and child
* space
* rename
* NeuralNetworkFeedForwardModel
* less
* just use file name
* try this
* more explicit
* rename
* move it
* child class for additional controllers
* rename
* time to split out custom lateral acceleration
* move around
* space
* fix
* TODO-SP
* TODO-SP
* update regardless, it's an extension now
* update name and expose toggle
* ui: sunnypilot Panel -> Steering Panel
* Update selfdrive/ui/sunnypilot/qt/offroad/settings/lateral_panel.h
* merge
* move to steering panel
* no need for this
* live params in a thread
* no live for now
* new structs
* more ui
* more flexible
* more ui
* no longer needed
* another ui
* cereal changes
* bump opendbc
* simplify checks
* all in one place
* split Enhanced Lat Accel
---------
Co-authored-by: DevTekVE <devtekve@gmail.com>
* init
* do it for hyundai
* Bump submodules
* no complaints
* use latest opendbc pr ref
* don't need this for leaf for now
* bump opendbc
* gotta set the sp safety flags in test models and safety replay!
* actually fetch CP_SP
* set safety param for lda button availability (lol forgot)
* use GET_FLAG
* Add TODO-SP
* bump submodules
* temp unavailable
* fix
* replay multiple
* clean up
* bump
* rename
* reason is in liveTracks
* more rename
* bump
* fix
* bump
* fix
* need to totally ignore it, or it will throw commIssues for radarErrors or not alive
* this is just simpler -- good thing kept struct
* rm
* bool fields
* liveTracks.valid is already set using errors
* fix
* clean up
* same but diff
* fix
* fix
* fix test
* clean up
* rm radarErrors
* whoops
* no struct
* Revert "no struct"
This reverts commit ed8ec02493673f850800344c73c969508fc38991.
* bump
* update
* Add support for TinyGrad model runner processing
Introduced a new function `is_tinygrad_model` to detect TinyGrad as an active model runner. Updated the `is_stock_model` logic to account for TinyGrad models and added a new process entry for TinyGrad in the model manager. This enables handling TinyGrad models alongside existing configurations.
adding modeld back
Add support for `modeld_v2` and update paths for consistency
Updated `SConscript` files to integrate `modeld_v2` alongside `modeld` and adjusted script paths for correct metadata handling. Adjusted various configurations and scripts, such as `labeler.yaml` and `build_release.sh`, to include `modeld_v2` and ensure cohesive project structure.
Refactor imports to use updated `modeld_v2` paths.
Replaced outdated `modeld` references with their `modeld_v2` counterparts for consistency and clarity across the codebase. Also updated `.gitignore` to accommodate new directory structure. This change ensures better maintainability and alignment with the new directory schema.
Refactor and reorganize modeld to sunnypilot/modeld_v2 structure.
Moved and renamed `modeld` components to the new `sunnypilot/modeld_v2` directory for better organization and modularity. Updated imports and file references to align with the new structure, ensuring compatibility and functionality. Streamlined project structure to improve maintainability and future development.
* typo
* Use `stock` model runner and refactor model checks.
Replaces outdated model detection logic with unified `stock` runner integration, simplifying the decision flow for model selection. Includes `stock` as a new enum in the `Runner` type and updates affected references accordingly.
* Handle missing 'sim_pose' in model outputs gracefully.
Added conditional checks to ensure the code handles cases where 'sim_pose' is absent in the model outputs. Fallback behaviors use 'plan' data when 'sim_pose' is unavailable, preventing potential errors and enhancing robustness.
