Breaking Changes

Version 6.1.19 onwards

  • match_past_detections, past_det_max_diff_area and max_detection_size (and associated label prefixes) need to be in the general section of ml_sequence. In the previous release they were stuffed inside each model sequence which lead to problems (imagine an event where snapshot and alarm had different objects and you were checking both. In pass 1, snapshot would match but alarm would not, so you’d see objects in alarm. In pass 2, alarm would match, but not snapshot and it would keep going on like this, effectively making match_past_detections useless. To avoid this, I am checking for match_past_detections after all matching is done)
  • You can now choose to ignore certain labels when you match past detections using ignore_past_detection_labels
  • stream_sequence now has a few new fields fields:
    • delay_between_frames. If specified, will wait for those many seconds before processing each frame.
    • delay_between_snapshots. If specified, will wait for those many seconds when processing snapshot frames. This allows you to do something like this: frame_set: snapshot,snapshot,snapshot,alarm with a delay_between_snapshots:2, which means it will keep analyzing snapshot 3 times, but with 2 seconds in between, which lets you grab multiple snapshot frames as it changes during an event. This is really only useful for this specific case.

Version 6.1.18 onwards

  • I now support face detection using TPU (NOT recognition). See objectconfig.ini for an example
  • You can now add descriptive names for each model sequence to better differentiate in logs
  • Each model sequence now has an enabled flag (default is yes). If no that means the model won’t be loaded. This is a good way to temporarily remove models while keeping config files intact
  • We now also have a same_model_strategy value of union - when set to union it will combine detection from all models for that type

Version 6.1.17 onwards

  • You can now localize past_det_max_diff_area, max_detection_size to specific objects by prefixing the object name. Example car_max_detection_size if present will override values for max_detection_size for objects that are cars. Same holds true for car_past_det_max_diff_area if match_past_detections=yes
  • mlapiconfig.ini also supports the above values - you no longer have to keep putting these to objectconfig.ini

Version 6.1.12 onwards

  • A lot of config changes, if you are using mlapi. Basically, I’m no longer fully supporting settings in objectconfig.ini transferring to mlapi. See Exceptions when using mlapi

Version 6.1.0 onwards

  • You can now string together multiple models in arbitrary fashion to suit your needs. There is a new entry in objectconfig.ini called ml_sequence that you can use to create your own sequence. Note that if ml_sequence is present, it will override any/all parameters in the [object], [face] and [alpr] sections. Please read this section to understand how this works.
  • The hog model has been removed. Note this refers to the hog person detection model, not the hog detection of a face. That still exists. With Yolo, TinyYolo, coral there was no need to support this very low performance model anymore.
  • You can now also specify arbitrary frames for analysis. See See here for details (look at options attribute).
  • To enable the new *_sequence attributes mentioned above, make use_sequence=yes in objectconfig.ini
  • A new attribute, disable_locks. When set to yes, it will result in locks not being grabbed before inferencing. The entire idea of grabbing locks is so that you have control on how many simultaneous processes use your CPU/GPU/TPU resources, so I’d recommend you don’t enable it. Set it to yes only if you are facing lock issues (such as timeouts)

Version 6.0.5 onwards

  • You can now specify object detection patterns on a per polygon/zone basis. The format is <polygonname>_zone_detection_pattern This works for imported ZM zones too. Please read the comments in objectconfig.ini. Note that this attribute will not be automatically added to a migrated objectconfig.ini file as the actual attribute name will change depending on your zone name
  • zmeventnotification.ini has a new attribute called replace_push_messages in the [fcm] section. When enabled (default is no), push messages will replace each other in the notification bar. This was the old Android behaviour prior to FCMv1. You can go back to this mode of operation for both iOS and Android if you enable this.

Version 6.0.1 onwards

  • zmeventnotification.ini new attribute in [fcm] called use_fcmv1 with a default of yes`. It is recommended you keep this on as this switches from the legacy FCM protocol to the FCM v1 which allows for better features (which I will add over time).
  • objectconfig.ini has a new attribute fast_gif in [animation]. If you are creating animations for push and generating GIFs, this creates a 2x speed GIF.

Version 6.0.0 onwards

  • The ES has a new attribute in [customize] called es_rules. A sample file gets automatically installed when you run the install script in /var/lib/zmeventnotification

  • Its use is optional. It is a JSON file with various rules for the ES that are not configuration related. Over the next few releases, this fill will replace the cryptic context of tokens.txt As of now, it can be used to specify custom times for notification. This list will grow over time.

  • A new perl dependency (optional) has been added to Installation of the Event Server (ES) if you need flexible datetime parsing for ES rules.

    On the Object Detection part:

  • This is going to be a big bad breaking change release, but continues the path to unification between various components I’ve developed.

  • To help with this ‘big bad breaking change’, I’ve provided an upgrade script. When you run ./ it will automatically run it at the end and put a migrated-objectconfig.ini in your current directory (from where you ran ./ You can also run it manually by invoking tools/ -c /etc/zm/objectconfig.ini

  • All the ml code has now moved to pyzm and both local hook and mlapi use pyzm. This means when I update ml code, both systems get it right always

  • This version also supports Google Coral Edge TPU

  • Several objectconfig.ini attributes have been replaced and some removed towards this unification goal:

    • models is now detection_sequence
    • yolo is no longer used. Instead object is used. object could be multiple object detection techniques, yolo or otherwise.
    • [ml] is now [remote]
    • [object] is a new section, which contains two new attributes:
      • object_framework which can be opencv or coral_edgetpu
      • object_processor which can be cpu, gpu or tpu
    • yolo_min_confidence is now object_min_confidence
    • config, weights, labels are now object_config, object_weights and object_labels respectively.
    • None of the tiny_ attributes exist anymore. Simply switch weights, labels and config files to switch between full and tiny
    • yolo_type doesn’t exist anymore (as tiny_ attributes are removed, so it doesn’t make sense)
    • alpr_pattern is now alpr_detection_pattern
    • detect_pattern no longer exists. You now have a per detection type pattern, which allows you to specify patterns based on the detection type:
      • object_detection_pattern - for all objects
      • alpr_detection_pattern - for for license plates
      • face_detection_pattern - for all faces detected
      • [general] has various new attributes that allow you to limit concurrent processing:
        • cpu_max_processes specific how many simultaneous instances of model execution will be allowed at one time. When more than this number is reached, processes will wait till in-flight processes complete. cpu_max_lock_wait specifies how long each process will wait (default 2 mins) before throwing an error.
        • tpu_max_processes and tpu_max_lock_wait same as above but for TPU
        • gpu_max_processes and gpu_max_lock_wait same as above but for GPU

Version 5.15.7 onwards

  • The <>/models/tinyyolo directory is now <>/models/tinyyolov3. will automatically move it, but remember to change your objectonfig.ini path if you are using tiny yolo.
  • You now have an option to use the new Tiny Yolo V4 models which will be automatically downloaded unless you disabled it (You’ll need OpenCV master as of Jul 11, 2020 as support for it was only merged 6 days ago)
  • A new attribute, ject_area has been introduced in objectconfig.ini. This specifies the largest area a detected object should take inside the image. You can keep it as a % or px value. Remember the image is resized to 416x416. better to keep in %

Version 5.15.6 onwards

  • I got lazy with 5.15.5. There were some errors that I fixed post 5.15 which I ‘post-pushed’ into 5.15.5. It is possible you installed 5.15.5 and don’t have these fixes. In other words, if your 5.15.5 is broken, Please upgrade.
  • In this release, I’ve also taken a necessary step towards model naming normalization. Basically, Yolo models are now YoloV3 and CSPN is now Yolov4. This is because this is the terminology Alexey has started using in his repo. This means you will have to change your objectconfig.ini and align it with the same objectconfig.ini provided in this repo. I’ve also normalized the names of the config, weights and name files for each model. The short of all of this is, look under the [yolo] section of the sample config and replace your current yolo paths. Note that I assume you use to install. If not, you’ll have to manually rename the old model names to the new ones. (Note that YoloV4 requires OpenCV 4.4 or above)

Version 5.15.5 onwards

  • zmeventnotification.ini has a new attribute, topic under [mqtt] which lets you set the topic name for the messages
  • objectconfig.ini has a new attribute, only_triggered_zm_zones. When set to yes, this will remove objects that don’t fall into zones that ZM detects motion in. Make sure you read the comments in objectconfig.ini above the attribute to understand its limitations

Version 5.14.4 onwards

  • Added ability for users to PR contrib modules See Guidelines for contrib
  • zmeventnotification.ini adds two new attributes that makes it simpler for users to keep object detection plugin hooks intact and also trigger their own scripts for housekeeping. See the ini script for documentation on event_start_hook_notify_userscript and event_end_hook_notify_userscript

Version 5.13.3 onwards

  • New attribute es_debug_level in zmeventnotification.ini that controls debug level verbosity. Default is 2
  • New CSPNet support with ResNeXt (requires OpenCV 4.3 or above) - Note that this requires a manual model download as the model is in a google drive link and all automated download scripts are hacks that stop working after a while.
  • You can now choose which models to download as part of ./ See install-specific-models

Version 5.11 onwards

  • If you are using local SDK for ALPR, their SDK and cloud versions have slightly different API formats. There is a new attribute called alpr_api_type in objectconfig.ini that should be set to local to handle this.
  • skip_monitors in zmeventnotification.ini is now called hook_skip_monitors to correctly reflect this only means hooks will be skipped for these monitors. A new attribute skip_monitors has been added that controls which monitors the ES will skip completely (That is, no analysis/notifications at all for these monitors)
  • Added support for live animations as part of push messages. This requires an upgraded zmNinja app ( or above) as well as ZoneMinder master (1.35) as of Mar 17 2020. Without these two updates, live notifications will not work. Specifically: - This introduces a new section in objectconfig.ini called [animation]. Please read the config for more details. - You are also going to have to re-run to install new dependencies

Version 5.9.9 onwards

  • You can now hyper charge your push notifications, including getting desktop notifications. See below
  • I now support 3rd party push notification systems. A popular one is pushover that a lot of people seem to use for customizing the quality of push notifications, including critical notifications, quiet time et. al. This adds the following parameters: - A new section called [push] in zmeventnotification.ini that adds two new attributes: use_api_push and api_push_script - I’ve provided a sample push script that supports pushover. This gets automatically installed when you use into /var/lib/zmeventnotification/bin/ - This also adds a new channel type called api to the pre-existing fcm,web,mqtt set. - You are of course, encouraged to write your own 3rd party plugins for push and PR back to the project. - Read more in this article

Version 5.7.7 onwards

  • For those who are happy to use the legacy openALPR self compiled version for license plate detection that does not use DNNs, I support that. This adds new parameters to objectconfig.ini. See objectconfig.ini for new parameters under the “If you are using OpenALPR command line” section.

Version 5.7.4 onwards

  • I know support the new OpenCV 4.1.2 GPU backend support for CUDA. This will only work if you are on OpenCV 4.1.2 and have compiled it correctly to use CUDA and are using the right architecture. - This adds a new attribute use_opencv_dnn_cuda in objectconfig.ini which by default is no. Please read the comments in objectconfig.ini about how to use this.
  • The ES supports a control channel using which you can control its behavior remotely - This adds new attributes use_escontrol_interface, escontrol_interface_file and escontrol_interface_password to zmeventnotification.ini. Read more about it Category: escontrol messages.
  • If you are using face recognition, you now have the option of automatically saving unknown faces to a specific folders. That way it’s easy for you to review them later and retrain your known faces. - This introduces the following new attributes to objectconfig.ini: save_unknown_faces, save_unknown_faces_leeway_pixels and unknown_images_path. Their documentation is part of objectconfig.ini
  • The detection script(s) now attach a JSON payload of the detected objects along with the text, separated by --SPLIT--. If you are hacking your own scripts, you need to handle this. The ES automatically handles it when sending notifications.

Version 5.2 onwards

  • use_hooks is a new attribute that controls whether hooks will be used or not
  • send_event_end_notification is a new attribute that controls whether end notifications are sent

Version 5.0 onwards

  • no longer tries to install opencv on its own. You will have to install opencv and opencv-contrib on your own. See install instructions in Machine Learning Hooks.
  • The hook_script attribute is deprecated. You now have hook_on_event_start and hook_on_event_end which lets you invoke different scripts when an event starts or ends. You also have the concepts of channels, that allows you to decide whether to send a notification even if hooks don’t return anything. Read up about notify_on_hook_success and notify_on_hook_fail in zmeventnotification.ini
  • Now that we support pre/post event hooks, the script names have changed too ( is and we have a new script called that is really just a dummy script. Change it to what you need to do at the end of an event, if you enable event end notifications)
  • You can now offload the entire machine learning processes to a remote server. All you need to do is to use ml_gateway and related options in objectconfig.ini. The “ML gateway” is my mlapi project
  • The ES now supports a restart_interval config item in zmeventnotification.ini. If not 0, this will restart the ES after those many seconds (example 7200 is 2 hours). This may be needed if you find the ES locking up after a few hours. I think 5.0 resolves this locking issue (see this issue) but if it doesn’t use this, umm, hack for now.

Version 4.6 onwards

  • If you are using hooks, make sure you run sudo ./ again - it will create additional files in /var/lib/zmeventnotification
  • The hook files and are now called and Furthermore, these scripts no longer reside in /usr/bin. They will now reside in /var/lib/zmeventnotification/bin. I suppose I did not need to namespace and move, but I thought of the latter after I did the namespace changing.
  • If you are using face recognition, 4.6.1 and above now allow multiple faces per person. Note that it is recommended you train them before you run detection. See the documentation for it in Machine Learning Hooks.

Version 4.4 onwards

  • If you are using picture messaging, then the URL format has changed. Please REMOVE &username=<user>&password=<passwd> from the URL and put them into the picture_portal_username and picture_portal_password fields respectively

Version 4.1 onwards

  • Hook versions will now always be <ES version>.x, so in this case 4.1.x
  • Hooks have now migrated to using a proper python ZM logger module so it better integrates with ZM logging
  • To view detection logs, you now need to follow the standard ZM logging process. See Logging documentation for more details)
  • You no longer have to manually install python requirements, the setup process should automatically install them
  • If you are using MQTT and your MQTT:Simple library was installed a while ago, you may need to update it. A new login method was added to that library on Dec 2018 which is required (ref)

Version 3.9 onwards

  • Hooks now add ALPR, so you need to run sudo -H pip install -r requirements.txt again
  • See modified objectconfig.ini if you want to add ALPR. Currently works with, so you will need an API key. See hooks docs for more info

Version 3.7 onwards

  • There were some significant changes to ZM (will be part of 1.34), which includes migration to Bcrypt for passwords. Changes were made to support Bcrypt, which means you will have to add additional libraries. See the installation guide.

version 3.3 onwards

  • Please use yes or no instead of 1 and 0 in zmeventnotification.ini to maintain consistency with objectconfig.ini
  • In zmeventnotification.ini, store_frame_in_zm is now hook_pass_image_path

version 3.2 onwards

  • Changes in paths for everything. - event server config file now defaults to /etc/zm
  • hook config now defaults to /etc/zm
  • Push token file now defaults to /var/lib/zmeventnotification/push
  • all object detection data files default to /var/lib/zmeventnotification
  • If you are migrating from a previous version:
    • Make a copy of your /etc/zmeventnotification.ini and /var/detect/objectconfig.ini (if you are using hooks)
    • Run sudo -H ./ again inside the repo, let it set up all the files
    • Compare your old config files to the news ones at /etc/zm and make necessary changes
    • Make sure everything works well
    • You can now delete the old /var/detect folder as well as /etc/zmeventnotification.ini
    • Run zmNinja again to make sure its token is registered in the new tokens file (in /var/lib/zmeeventnotification/push/tokens.txt)