Change Log

[v1.3.1] - 2022-07-12

Fixed

• DynTrap crashes using new pipeline in Send mode - fixed

  • WriterSettings object controled the path variable, this dictates where files are buffered on disk

  • path is now made a property of the base-class OutputSettings, WriterSettings is removed.

  • We now have a base-class with required settings for send or disk modes, and an extension class, SenderSettings adds info for uploading detections to servers.

Added

• New setttings fields are added to allow users to set

  • upload to fastcat-cloud or to use thier own server

  • add a userID and apiKey for fastcat-cloud uploads

  • specify the FCC endpoints (in case these change in future, or we have multiple mirrors)

• New sender modes in comms.py

  • allow video and image detections to be uploaded to FCC

• Sender configuration testing in comms.Output function

  • tests if the server, userId, api keys are configured appropriately, if this fails, the user is notified via the log and a Writer instance is used instead

• Output methods in the Sender class now handle cases where the server is unavailable by saving to disk if the connection fails.

• Ability to register the users FASTCAT-Cloud details in tuner.py

• Ability to post detections to FASTCAT-Cloud, made changes in comms.py, creates a log of

• Feature to delete metadata files after conversion to output formats, switched on by default. May be turned off in tuner.py

• Ability to use FASTCAT-Cloud api to perform animal detection.

Changed

• Sender now inherits from Writer

• H264 to mp4 format conversion moved to imdecode.py

• SenderSettings is created by default rather than OutputSettings. This allows FASTCAT-Cloud details to be simply passed to the animal filtering stages. Should be refactored in the future.

[v1.3.0] - 2022-06-04

Fixed

• Increase Serial timeout to read full sensor line

• Memory overflow for reading large motion events from disk, new event processor only loads frames as and when required from IO

Added - 2022-06-09

• ability to output log to a set file or standard out

• a much faster solution for SOTV of motion vectors. Can be seen in motion.py and mvector_sum.pyx, is written with Cython and tackles the biggest bottleneck of ndarray access time by accessing the memory directly using C. Around 50x faster than the original solution, produces the same results.

• facility to read and save raw format YUV files

  • can now save YUV stream to clip.dat per event

  • decoding of all saved image frames now performed within imdecode.py

  • added YUV format to settings and tuner

  • YUV format uses less IO bandwidth, RPi zero w can now run at 20fps

Changed - 2022-06-04

• removed many settings from tuner.py

  • bitrate, removed from tuner.py and settings.py now set by default at 17000000, proven to work in testing on rpi0, rpi4

  • raw-framerate-divisor, removed from tuner.py, still configurable via settings.py now set to 1 (ie not required)

  • raw-pixel-format, removed from tuner.py, still configurable via settings.py now set to RGBA, stops PiCamera complaining

  • buffer size, removed from tuner.py, still configurable via settings.py now set to 20 secs, tested and works on rpi0, rpi4

• event processing now in its own file DynAIkonTrap/filtering/event.py

  • makes filter.py more concise

  • not built as a pipeline element (ie no input and output queues), perhaps to-do although seems superfluous…

• EventData class no longer carries frame buffers for an entire event

  • remember_from_disk.py no longer reads frame buffers, instead it scans the event file, making sure buffers exist and produces file pointers for the beginnning of each buffer, these are added to EventData

  • EventData also contains fields for frame width, height and pixel format, seems neater to pass them around as EventData than configure each pipeline element with those settings

[v1.2.1] - 2021-11-24

Added

• Support for TFLite trained SSDLite MobileNet v2 models

  • TFLite compiled binary wheel files for raspberry pi devices are included in python_wheels/tflite_runtime

    • at present installing through pip is experimental on RPi 4 and not possible on RPi Zero W, must be built from source.

  • animal.py modified to run inference using tflite networks or yolov4-tiny

  • animal.py run_raw and run modified to produce a human_confidence as well as animal_confidence

  • configuration for human detection, fast animal detection (tflite model) and thresholds for each added to settings.

Fixed

- fixed output queue length in `event_rememberer` to 1 not 10, this stops the system loading way too many motion events and exhausting memory (kswaps)
- fixed indexing error in reading from motion buffer within `camera_to_disk.py`

Changed

- methods which use `animal.run` have been modified to accept human and animal values
- changes in `setup.sh` insure tflite install is attempted

[v1.2.0] - 2021-10-31

Added

• Camera recording to disk module, modified PiCamera; DynCamera

• EventRememberer which to load events from disk into processing pipeline

• Filtermodes BY_FRAME and BY_EVENT to add functionality to process events with Filter module

• Event output added to comms.py

• modified main.py to support old and new pipelines depending on settings

• Modified settings to include parameters for: pipeline, bitrate, framerate divisor, buffer length, raw image format and detector fraction

Changed

• Motion Queue Settings semantics changed to processing settings. To better fit other pipeline which does not use a motion queue.

[v1.1.0] - 2021-08-15

Added

• Check for settings.json version vs. DynAIkonTrap version in case settings are copied from one trap to another

• Added support for multiple output video codecs and settings to choose between them

• Pillow to requirements.txt easiest way to load raw images as far as I can tell. If this can be done with OpenCV it would be nicer.

Fixed

• Implementation of UrSense interface following updated documentation

• Catches pycamera ModuleNotFoundError when running the camera trap with emulated input on desktop

Changed

• Video sensor logs to JSON for easier machine reading – parsing this back to the previous VTT output is trivial

• Interface to initialise Output – output mode is now handled internally

• Documentation – including wiki – migrated to Sphinx

Added

• context buffer so that clips of animals include “run in” and “trail off” frames.

• LabelledFrames now include a motion_status label of enumerated type MotionStatus

• filtering.py adds all frames to a motion_sequence regardless of motion score but labels frames passing through it.

• frames without motion are assigned a priority of -1.0 and a MotionStatus of STILL this ensures they are never returned by get_highest_priority() - thus never assessed for containing an animal.

• MotionQueue does not add motion sequences to its queue which do not contain motion. ie end_motion_sequence() now searches the sequence to make sure at least one frame is labelled with motion before appending to queue.

Changed

• MotionSequence class is now called Sequence

• MotionQueue class is now called MotionLabelledQueue

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[v1.0.0] - 2021-06-12

Added

• First release of DynAIkonTrap