Always show recording link even if recordings are currently disabled (#2787)

* Always show recording link even if recordings are currently disabled

* Fix test to consider all cameras to have recording link

Makefile

@@ -3,7 +3,7 @@ default_target: amd64_frigate
 COMMIT_HASH := $(shell git log -1 --pretty=format:"%h"|tail -1)
 
 version:
-	echo "VERSION='0.10.1-$(COMMIT_HASH)'" > frigate/version.py
+	echo "VERSION='0.10.0-$(COMMIT_HASH)'" > frigate/version.py
 
 web:
 	docker build --tag frigate-web --file docker/Dockerfile.web web/

docs/docs/configuration/advanced.md

@@ -43,11 +43,6 @@ If you are storing your database on a network share (SMB, NFS, etc), you may get
 
 This may need to be in a custom location if network storage is used for the media folder.
 
-```yaml
-database:
-  path: /path/to/frigate.db
-```
-
 ### `model`
 
 If using a custom model, the width and height will need to be specified.

docs/docs/configuration/camera_specific.md

@@ -19,34 +19,6 @@ output_args:
   rtmp: -c:v libx264 -an -f flv
 ```
 
-### JPEG Stream Cameras
-
-Cameras using a live changing jpeg image will need input parameters as below
-
-```yaml
-input_args:
-- -r
-- 5 # << enter FPS here
-- -stream_loop
-- -1
-- -f
-- image2
-- -avoid_negative_ts
-- make_zero
-- -fflags
-- nobuffer
-- -flags
-- low_delay
-- -strict
-- experimental
-- -fflags
-- +genpts+discardcorrupt
-- -use_wallclock_as_timestamps
-- 1
-```
-
-Outputting the stream will have the same args and caveats as per [MJPEG Cameras](#mjpeg-cameras)
-
 ### RTMP Cameras
 
 The input parameters need to be adjusted for RTMP cameras

docs/docs/configuration/index.md

@@ -159,26 +159,11 @@ detect:
   enabled: True
   # Optional: Number of frames without a detection before frigate considers an object to be gone. (default: 5x the frame rate)
   max_disappeared: 25
-  # Optional: Configuration for stationary object tracking
-  stationary:
-    # Optional: Frequency for running detection on stationary objects (default: shown below)
-    # When set to 0, object detection will never be run on stationary objects. If set to 10, it will be run on every 10th frame.
-    interval: 0
-    # Optional: Number of frames without a position change for an object to be considered stationary (default: 10x the frame rate or 10s)
-    threshold: 50
-    # Optional: Define a maximum number of frames for tracking a stationary object (default: not set, track forever)
-    # This can help with false positives for objects that should only be stationary for a limited amount of time.
-    # It can also be used to disable stationary object tracking. For example, you may want to set a value for person, but leave
-    # car at the default.
-    # WARNING: Setting these values overrides default behavior and disables stationary object tracking.
-    #          There are very few situations where you would want it disabled. It is NOT recommended to
-    #          copy these values from the example config into your config unless you know they are needed.
-    max_frames:
-      # Optional: Default for all object types (default: not set, track forever)
-      default: 3000
-      # Optional: Object specific values
-      objects:
-        person: 1000
+  # Optional: Frequency for running detection on stationary objects (default: shown below)
+  # When set to 0, object detection will never be run on stationary objects. If set to 10, it will be run on every 10th frame.
+  stationary_interval: 0
+  # Optional: Number of frames without a position change for an object to be considered stationary (default: 10x the frame rate or 10s)
+  stationary_threshold: 50
 
 # Optional: Object configuration
 # NOTE: Can be overridden at the camera level
@@ -236,20 +221,11 @@ motion:
   # Optional: motion mask
   # NOTE: see docs for more detailed info on creating masks
   mask: 0,900,1080,900,1080,1920,0,1920
-  # Optional: improve contrast (default: shown below)
-  # Enables dynamic contrast improvement. This should help improve night detections at the cost of making motion detection more sensitive
-  # for daytime.
-  improve_contrast: False
 
 # Optional: Record configuration
 # NOTE: Can be overridden at the camera level
 record:
   # Optional: Enable recording (default: shown below)
-  # WARNING: Frigate does not currently support limiting recordings based
-  #          on available disk space automatically. If using recordings,
-  #          you must specify retention settings for a number of days that
-  #          will fit within the available disk space of your drive or Frigate
-  #          will crash.
   enabled: False
   # Optional: Number of minutes to wait between cleanup runs (default: shown below)
   # This can be used to reduce the frequency of deleting recording segments from disk if you want to minimize i/o

docs/docs/configuration/objects.mdx

@@ -5,11 +5,7 @@ title: Objects
 
 import labels from "../../../labelmap.txt";
 
-Frigate includes the object models listed below from the Google Coral test data.
-
-Please note: 
- - `car` is listed twice because `truck` has been renamed to `car` by default. These object types are frequently confused.
- - `person` is the only tracked object by default. See the [full configuration reference](https://docs.frigate.video/configuration/index#full-configuration-reference) for an example of expanding the list of tracked objects.
+By default, Frigate includes the following object models from the Google Coral test data. Note that `car` is listed twice because `truck` has been renamed to `car` by default. These object types are frequently confused.
 
 <ul>
   {labels.split("\n").map((label) => (

docs/docs/configuration/record.md

@@ -21,18 +21,4 @@ record:
 
 This configuration will retain recording segments that overlap with events and have active tracked objects for 10 days. Because multiple events can reference the same recording segments, this avoids storing duplicate footage for overlapping events and reduces overall storage needs.
 
-When `retain -> days` is set to `0`, segments will be deleted from the cache if no events are in progress.
-
-## What do the different retain modes mean?
-
-Frigate saves from the stream with the `record` role in 10 second segments. These options determine which recording segments are kept for 24/7 recording (but can also affect events). 
-
-Let's say you have frigate configured so that your doorbell camera would retain the last **2** days of 24/7 recording. 
-- With the `all` option all 48 hours of those two days would be kept and viewable. 
-- With the `motion` option the only parts of those 48 hours would be segments that frigate detected motion. This is the middle ground option that won't keep all 48 hours, but will likely keep all segments of interest along with the potential for some extra segments.
-- With the `active_objects` option the only segments that would be kept are those where there was a true positive object that was not considered stationary.
-
-The same options are available with events. Let's consider a scenario where you drive up and park in your driveway, go inside, then come back out 4 hours later.
-- With the `all` option all segments for the duration of the event would be saved for the event. This event would have 4 hours of footage.
-- With the `motion` option all segments for the duration of the event with motion would be saved. This means any segment where a car drove by in the street, person walked by, lighting changed, etc. would be saved. 
-- With the `active_objects` it would only keep segments where the object was active. In this case the only segments that would be saved would be the ones where the car was driving up, you going inside, you coming outside, and the car driving away. Essentially reducing the 4 hours to a minute or two of event footage. 
+When `retain_days` is set to `0`, segments will be deleted from the cache if no events are in progress.

docs/docs/configuration/rtmp.md

@@ -5,4 +5,4 @@ title: RTMP
 
 Frigate can re-stream your video feed as a RTMP feed for other applications such as Home Assistant to utilize it at `rtmp://<frigate_host>/live/<camera_name>`. Port 1935 must be open. This allows you to use a video feed for detection in frigate and Home Assistant live view at the same time without having to make two separate connections to the camera. The video feed is copied from the original video feed directly to avoid re-encoding. This feed does not include any annotation by Frigate.
 
-Some video feeds are not compatible with RTMP. If you are experiencing issues, check to make sure your camera feed is h264 with AAC audio. If your camera doesn't support a compatible format for RTMP, you can use the ffmpeg args to re-encode it on the fly at the expense of increased CPU utilization. Some more information about it can be found [here](../faqs#audio-in-recordings). 
+Some video feeds are not compatible with RTMP. If you are experiencing issues, check to make sure your camera feed is h264 with AAC audio. If your camera doesn't support a compatible format for RTMP, you can use the ffmpeg args to re-encode it on the fly at the expense of increased CPU utilization.

docs/docs/faqs.md

@@ -11,24 +11,9 @@ This error message is due to a shm-size that is too small. Try updating your shm
 
 A solid green image means that frigate has not received any frames from ffmpeg. Check the logs to see why ffmpeg is exiting and adjust your ffmpeg args accordingly.
 
-### How can I get sound or audio in my recordings? {#audio-in-recordings}
+### How can I get sound or audio in my recordings?
 
-By default, Frigate removes audio from recordings to reduce the likelihood of failing for invalid data. If you would like to include audio, you need to override the output args to remove `-an` for where you want to include audio. The recommended audio codec is `aac`. Not all audio codecs are supported by RTMP, so you may need to re-encode your audio with `-c:a aac`. The default ffmpeg args are shown [here](/configuration/index/#full-configuration-reference).
-
-:::tip
-
-When using `-c:a aac`, do not forget to replace `-c copy` with `-c:v copy`. Example:
-
-```diff title="frigate.yml"
-ffmpeg:
-  output_args:
--    record: -f segment -segment_time 10 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c copy -an
-+    record: -f segment -segment_time 10 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c:v copy -c:a aac
-```
-
-This is needed because the `-c` flag (without `:a` or `:v`) applies for both audio and video, thus making it conflicting with `-c:a aac`.
-
-:::
+By default, Frigate removes audio from recordings to reduce the likelihood of failing for invalid data. If you would like to include audio, you need to override the output args to remove `-an` for where you want to include audio. The recommended audio codec is `aac`. Not all audio codecs are supported by RTMP, so you may need to re-encode your audio with `-c:a aac`. The default ffmpeg args are shown [here](configuration/index#full-configuration-reference).
 
 ### My mjpeg stream or snapshots look green and crazy
 

docs/docs/hardware.md

@@ -21,17 +21,19 @@ I may earn a small commission for my endorsement, recommendation, testimonial, o
 
 ## Server
 
-My current favorite is the Minisforum GK41 because of the dual NICs that allow you to setup a dedicated private network for your cameras where they can be blocked from accessing the internet. There are many used workstation options on eBay that work very well. Anything with an Intel CPU and capable of running Debian should work fine. As a bonus, you may want to look for devices with a M.2 or PCIe express slot that is compatible with the Google Coral. I may earn a small commission for my endorsement, recommendation, testimonial, or link to any products or services from this website.
+My current favorite is the Odyssey X86 Blue J4125 because the Coral M.2 compatibility and dual NICs that allow you to setup a dedicated private network for your cameras where they can be blocked from accessing the internet. I may earn a small commission for my endorsement, recommendation, testimonial, or link to any products or services from this website.
 
-| Name                                                                                                                            | Inference Speed | Coral Compatibility | Notes                                                                                                                                   |
-| ------------------------------------------------------------------------------------------------------------------------------- | --------------- | ------------------- | --------------------------------------------------------------------------------------------------------------------------------------- |
-| <a href="https://amzn.to/3oH4BKi" target="_blank" rel="nofollow noopener sponsored">Odyssey X86 Blue J4125</a> (affiliate link) | 9-10ms          | M.2 B+M             | Dual gigabit NICs for easy isolated camera network. Easily handles several 1080p cameras.                                               |
-| <a href="https://amzn.to/3ptnb8D" target="_blank" rel="nofollow noopener sponsored">Minisforum GK41</a> (affiliate link)        | 9-10ms          | USB                 | Dual gigabit NICs for easy isolated camera network. Easily handles several 1080p cameras.                                               |
-| <a href="https://amzn.to/35E79BC" target="_blank" rel="nofollow noopener sponsored">Beelink GK55</a> (affiliate link)           | 9-10ms          | USB                 | Dual gigabit NICs for easy isolated camera network. Easily handles several 1080p cameras.                                               |
-| <a href="https://amzn.to/3psFlHi" target="_blank" rel="nofollow noopener sponsored">Intel NUC</a> (affiliate link)              | 8-10ms          | USB                 | Overkill for most, but great performance. Can handle many cameras at 5fps depending on typical amounts of motion. Requires extra parts. |
-| <a href="https://amzn.to/3a6TBh8" target="_blank" rel="nofollow noopener sponsored">BMAX B2 Plus</a> (affiliate link)           | 10-12ms         | USB                 | Good balance of performance and cost. Also capable of running many other services at the same time as frigate.                          |
-| <a href="https://amzn.to/2YjpY9m" target="_blank" rel="nofollow noopener sponsored">Atomic Pi</a> (affiliate link)              | 16ms            | USB                 | Good option for a dedicated low power board with a small number of cameras. Can leverage Intel QuickSync for stream decoding.           |
-| <a href="https://amzn.to/2YhSGHH" target="_blank" rel="nofollow noopener sponsored">Raspberry Pi 4 (64bit)</a> (affiliate link) | 10-15ms         | USB                 | Can handle a small number of cameras.                                                                                                   |
+| Name                                                                                                                             | Inference Speed | Coral Compatibility | Notes                                                                                                                         |
+| -------------------------------------------------------------------------------------------------------------------------------- | --------------- | ------------------- | ----------------------------------------------------------------------------------------------------------------------------- |
+| <a href="https://amzn.to/3oH4BKi" target="_blank" rel="nofollow noopener sponsored">Odyssey X86 Blue J4125</a> (affiliate link)  | 9-10ms          | M.2 B+M             | Dual gigabit NICs for easy isolated camera network. Easily handles several 1080p cameras.                                     |
+| <a href="https://amzn.to/3oxEC8m" target="_blank" rel="nofollow noopener sponsored">Minisforum GK41</a> (affiliate link)         | 9-10ms          | USB                 | Great alternative to a NUC. Easily handles several 1080p cameras.                                                             |
+| <a href="https://amzn.to/3ixJFlb" target="_blank" rel="nofollow noopener sponsored">Minisforum GK50</a> (affiliate link)         | 9-10ms          | USB                 | Dual gigabit NICs for easy isolated camera network. Easily handles several 1080p cameras.                                     |
+| <a href="https://amzn.to/3l7vCEI" target="_blank" rel="nofollow noopener sponsored">Intel NUC</a> (affiliate link)               | 8-10ms          | USB                 | Overkill for most, but great performance. Can handle many cameras at 5fps depending on typical amounts of motion.             |
+| <a href="https://amzn.to/3a6TBh8" target="_blank" rel="nofollow noopener sponsored">BMAX B2 Plus</a> (affiliate link)            | 10-12ms         | USB                 | Good balance of performance and cost. Also capable of running many other services at the same time as frigate.                |
+| <a href="https://amzn.to/2YjpY9m" target="_blank" rel="nofollow noopener sponsored">Atomic Pi</a> (affiliate link)               | 16ms            | USB                 | Good option for a dedicated low power board with a small number of cameras. Can leverage Intel QuickSync for stream decoding. |
+| <a href="https://amzn.to/2WIpwRU" target="_blank" rel="nofollow noopener sponsored">Raspberry Pi 3B (32bit)</a> (affiliate link) | 60ms            | USB                 | Can handle a small number of cameras, but the detection speeds are slow due to USB 2.0.                                       |
+| <a href="https://amzn.to/2YhSGHH" target="_blank" rel="nofollow noopener sponsored">Raspberry Pi 4 (32bit)</a> (affiliate link)  | 15-20ms         | USB                 | Can handle a small number of cameras. The 2GB version runs fine.                                                              |
+| <a href="https://amzn.to/2YhSGHH" target="_blank" rel="nofollow noopener sponsored">Raspberry Pi 4 (64bit)</a> (affiliate link)  | 10-15ms         | USB                 | Can handle a small number of cameras. The 2GB version runs fine.                                                              |
 
 ## Google Coral TPU
 

docs/docs/installation.md

@@ -21,12 +21,6 @@ Windows is not officially supported, but some users have had success getting it
 
 Frigate uses the following locations for read/write operations in the container. Docker volume mappings can be used to map these to any location on your host machine.
 
-:::caution
-
-Note that Frigate does not currently support limiting recordings based on available disk space automatically. If using recordings, you must specify retention settings for a number of days that will fit within the available disk space of your drive or Frigate will crash.
-
-:::
-
 - `/media/frigate/clips`: Used for snapshot storage. In the future, it will likely be renamed from `clips` to `snapshots`. The file structure here cannot be modified and isn't intended to be browsed or managed manually.
 - `/media/frigate/recordings`: Internal system storage for recording segments. The file structure here cannot be modified and isn't intended to be browsed or managed manually.
 - `/media/frigate/frigate.db`: Default location for the sqlite database. You will also see several files alongside this file while frigate is running. If moving the database location (often needed when using a network drive at `/media/frigate`), it is recommended to mount a volume with docker at `/db` and change the storage location of the database to `/db/frigate.db` in the config file.
@@ -124,7 +118,6 @@ services:
     shm_size: "64mb" # update for your cameras based on calculation above
     devices:
       - /dev/bus/usb:/dev/bus/usb # passes the USB Coral, needs to be modified for other versions
-      - /dev/apex_0:/dev/apex_0 # passes a PCIe Coral, follow driver instructions here https://coral.ai/docs/m2/get-started/#2a-on-linux
       - /dev/dri/renderD128 # for intel hwaccel, needs to be updated for your hardware
     volumes:
       - /etc/localtime:/etc/localtime:ro

frigate/config.py

@@ -122,7 +122,6 @@ class MotionConfig(FrigateBaseModel):
         ge=1,
         le=255,
     )
-    improve_contrast: bool = Field(default=False, title="Improve Contrast")
     contour_area: Optional[int] = Field(default=30, title="Contour Area")
     delta_alpha: float = Field(default=0.2, title="Delta Alpha")
     frame_alpha: float = Field(default=0.2, title="Frame Alpha")
@@ -163,29 +162,6 @@ class RuntimeMotionConfig(MotionConfig):
         extra = Extra.ignore
 
 
-class StationaryMaxFramesConfig(FrigateBaseModel):
-    default: Optional[int] = Field(title="Default max frames.", ge=1)
-    objects: Dict[str, int] = Field(
-        default_factory=dict, title="Object specific max frames."
-    )
-
-
-class StationaryConfig(FrigateBaseModel):
-    interval: Optional[int] = Field(
-        default=0,
-        title="Frame interval for checking stationary objects.",
-        ge=0,
-    )
-    threshold: Optional[int] = Field(
-        title="Number of frames without a position change for an object to be considered stationary",
-        ge=1,
-    )
-    max_frames: StationaryMaxFramesConfig = Field(
-        default_factory=StationaryMaxFramesConfig,
-        title="Max frames for stationary objects.",
-    )
-
-
 class DetectConfig(FrigateBaseModel):
     height: int = Field(default=720, title="Height of the stream for the detect role.")
     width: int = Field(default=1280, title="Width of the stream for the detect role.")
@@ -196,9 +172,14 @@ class DetectConfig(FrigateBaseModel):
     max_disappeared: Optional[int] = Field(
         title="Maximum number of frames the object can dissapear before detection ends."
     )
-    stationary: StationaryConfig = Field(
-        default_factory=StationaryConfig,
-        title="Stationary objects config.",
+    stationary_interval: Optional[int] = Field(
+        default=0,
+        title="Frame interval for checking stationary objects.",
+        ge=0,
+    )
+    stationary_threshold: Optional[int] = Field(
+        title="Number of frames without a position change for an object to be considered stationary",
+        ge=1,
     )
 
 
@@ -791,8 +772,8 @@ class FrigateConfig(FrigateBaseModel):
 
             # Default stationary_threshold configuration
             stationary_threshold = camera_config.detect.fps * 10
-            if camera_config.detect.stationary.threshold is None:
-                camera_config.detect.stationary.threshold = stationary_threshold
+            if camera_config.detect.stationary_threshold is None:
+                camera_config.detect.stationary_threshold = stationary_threshold
 
             # FFMPEG input substitution
             for input in camera_config.ffmpeg.inputs:

frigate/motion.py

@@ -38,15 +38,14 @@ class MotionDetector:
         )
 
         # Improve contrast
-        if self.config.improve_contrast:
-            minval = np.percentile(resized_frame, 4)
-            maxval = np.percentile(resized_frame, 96)
-            # don't adjust if the image is a single color
-            if minval < maxval:
-                resized_frame = np.clip(resized_frame, minval, maxval)
-                resized_frame = (
-                    ((resized_frame - minval) / (maxval - minval)) * 255
-                ).astype(np.uint8)
+        minval = np.percentile(resized_frame, 4)
+        maxval = np.percentile(resized_frame, 96)
+        # don't adjust if the image is a single color
+        if minval < maxval:
+            resized_frame = np.clip(resized_frame, minval, maxval)
+            resized_frame = (
+                ((resized_frame - minval) / (maxval - minval)) * 255
+            ).astype(np.uint8)
 
         # mask frame
         resized_frame[self.mask] = [255]

frigate/object_processing.py

@@ -161,7 +161,7 @@ class TrackedObject:
             # if the motionless_count reaches the stationary threshold
             if (
                 self.obj_data["motionless_count"]
-                == self.camera_config.detect.stationary.threshold
+                == self.camera_config.detect.stationary_threshold
             ):
                 significant_change = True
 
@@ -194,7 +194,7 @@ class TrackedObject:
             "area": self.obj_data["area"],
             "region": self.obj_data["region"],
             "stationary": self.obj_data["motionless_count"]
-            > self.camera_config.detect.stationary.threshold,
+            > self.camera_config.detect.stationary_threshold,
             "motionless_count": self.obj_data["motionless_count"],
             "position_changes": self.obj_data["position_changes"],
             "current_zones": self.current_zones.copy(),

frigate/objects.py

@@ -93,39 +93,18 @@ class ObjectTracker:
 
         return True
 
-    def is_expired(self, id):
-        obj = self.tracked_objects[id]
-        # get the max frames for this label type or the default
-        max_frames = self.detect_config.stationary.max_frames.objects.get(
-            obj["label"], self.detect_config.stationary.max_frames.default
-        )
-
-        # if there is no max_frames for this label type, continue
-        if max_frames is None:
-            return False
-
-        # if the object has exceeded the max_frames setting, deregister
-        if (
-            obj["motionless_count"] - self.detect_config.stationary.threshold
-            > max_frames
-        ):
-            return True
-
     def update(self, id, new_obj):
         self.disappeared[id] = 0
         # update the motionless count if the object has not moved to a new position
         if self.update_position(id, new_obj["box"]):
             self.tracked_objects[id]["motionless_count"] += 1
-            if self.is_expired(id):
-                self.deregister(id)
-                return
         else:
             # register the first position change and then only increment if
             # the object was previously stationary
             if (
                 self.tracked_objects[id]["position_changes"] == 0
                 or self.tracked_objects[id]["motionless_count"]
-                >= self.detect_config.stationary.threshold
+                >= self.detect_config.stationary_threshold
             ):
                 self.tracked_objects[id]["position_changes"] += 1
             self.tracked_objects[id]["motionless_count"] = 0
@@ -133,11 +112,9 @@ class ObjectTracker:
         self.tracked_objects[id].update(new_obj)
 
     def update_frame_times(self, frame_time):
-        for id in list(self.tracked_objects.keys()):
+        for id in self.tracked_objects.keys():
             self.tracked_objects[id]["frame_time"] = frame_time
             self.tracked_objects[id]["motionless_count"] += 1
-            if self.is_expired(id):
-                self.deregister(id)
 
     def match_and_update(self, frame_time, new_objects):
         # group by name

frigate/video.py

@@ -511,8 +511,8 @@ def process_frames(
                 if obj["motionless_count"] >= 10
                 # and it isn't due for a periodic check
                 and (
-                    detect_config.stationary.interval == 0
-                    or obj["motionless_count"] % detect_config.stationary.interval != 0
+                    detect_config.stationary_interval == 0
+                    or obj["motionless_count"] % detect_config.stationary_interval != 0
                 )
                 # and it hasn't disappeared
                 and object_tracker.disappeared[obj["id"]] == 0