// because we will probably do this async
public AnalysisResult AnalyzeFrame()
{
AnalysisResult result = new AnalysisResult();
InterestingObjects.Clear();
HashSet <string> failureReasons = new HashSet <string>();
string reason = string.Empty;
if (null != _areas && _areas.Count() > 0)
{
if (null != _imageObjects)
{
foreach (ImageObject imageObject in _imageObjects)
{
// Each area cares about specific types of objects.
// The overlap for each type varies as does the confidences.
// Right now we don't care about the number of frames the object is in or whether
// the object is moving into or out of the area.
foreach (AreaOfInterest area in _areas)
{
// The search critera defines whether we are looking for people, vehicles, animals, etc.
if (null != area.SearchCriteria)
{
foreach (ObjectCharacteristics criteria in area.SearchCriteria)
{
// First find out what type of object the AI thinks this is.
ImageObjectType objectType = ObjectTypeFromLabel(imageObject.Label);
if (criteria.ObjectType != ImageObjectType.Irrelevant)
{
// If this is a type of object we generally might care about for security purposes
// then we compare the overlap to to minimum overlap to see if we still care
// (and yes, there are more elegant ways to do this, but it is easier to debug like this
if (criteria.ObjectType == objectType)
{
int percentOverlap = ObjectToAreaOverlap(imageObject, area);
if (percentOverlap >= criteria.MinPercentOverlap)
{
if (area.AOIType == AOIType.IgnoreObjects)
{
reason = area.AOIName + ": Object in ignored area - " + imageObject.Label;
failureReasons.Add(reason);
// yes, it met all of our critera, but the critera was to ignore it.
// It still may also be in an area we do care about, but we worry about that
// in the next loop
}
else
{
// OK, we probably care, but how confident are we that this object is something we care about
if ((int)Math.Round(imageObject.Confidence * 100) >= criteria.Confidence)
{
// BUT WAIT, THERE'S MORE!
if (criteria.MinimumXSize == 0 || imageObject.ObjectRectangle.Width > criteria.MinimumXSize)
{
if (criteria.MinimumYSize == 0 || imageObject.ObjectRectangle.Height > criteria.MinimumYSize)
{
InterestingObject interesting = new InterestingObject(area, imageObject, percentOverlap);
InterestingObjects.Add(interesting);
Dbg.Trace("Adding interesting object before 2nd chance ignore: " + interesting.FoundObject.Label);
}
else
{
reason = area.AOIName + ": Minimum height - too low - " + imageObject.Label;
failureReasons.Add(reason);
}
}
else
{
reason = area.AOIName + ": Minimum width too low - " + imageObject.Label;
failureReasons.Add(reason);
}
}
else
{
reason = area.AOIName + ": Confidence level too low: " + (imageObject.Confidence * 100).ToString() + " - " + imageObject.Label;
failureReasons.Add(reason);
}
}
}
else
{
reason = area.AOIName + ": Less than minimum overlap: " + percentOverlap.ToString() + " - " + imageObject.Label;
failureReasons.Add(reason);
}
}
else
{
if (objectType != ImageObjectType.Irrelevant)
{
reason = area.AOIName + ": Object mismatch: " + criteria.ObjectType.ToString() + " - " + objectType.ToString() + " - " + imageObject.Label;
failureReasons.Add(reason);
}
}
}
else /*failureReasons.Add(area.AOIName + ": Object Irrelevant - " + imageObject.Label); */ } {
}
}
else
{
reason = "No search critera";
failureReasons.Add(reason);
}
}
// Double check the object to be sure it isn't in a ignore zone.
// This is a little screwy -- we added one, then we delete the one we just added.
// However, there are few good ways to do it since an object may be in several areas,
// yet we dont't want it if it really should be ignored
foreach (var ignore in _areas)
{
if (ignore.AOIType == AOIType.IgnoreObjects)
{
// Again, we look at the search criteria to see if it was the type of object we ignore
if (null != ignore.SearchCriteria)
{
foreach (var criteria in ignore.SearchCriteria)
{
ImageObjectType objectType = ObjectTypeFromLabel(imageObject.Label);
if (criteria.ObjectType == objectType)
{
// Yes, it is the type of object we ignore
int ignoreOverlap = ObjectToAreaOverlap(imageObject, ignore); // Does it overlap
{
if (ignoreOverlap > criteria.MinPercentOverlap) //
{
bool foundOne = false;
do
{
var io = InterestingObjects.FirstOrDefault(x => x.FoundObject.ID == imageObject.ID);
if (io.FoundObject != null)
{
foundOne = true;
reason = ignore.AOIName + ": Ignore area second pass validation - Object: " + io.FoundObject.Label;
failureReasons.Add(reason);
Dbg.Trace("Removing object on second pass ignore area validation: " + io.FoundObject.Label);
InterestingObjects.Remove(io);
}
else
{
foundOne = false;
}
} while (foundOne);
}
}
}
}
}
else
{
Dbg.Write("FrameAnalyzer.AnalyzeFrame - On double check ignore areas no search critera found ");
}
}
}
}
}
else
{
failureReasons.Add("No Interesting Objects");
}
// InterestingObjects = RemoveDuplicateAreas(InterestingObjects);
}
else
{
failureReasons.Add("No areas defined");
}
result.InterestingObjects = InterestingObjects;
result.FailureReasons = failureReasons;
foreach (var failure in failureReasons)
{
Dbg.Trace(failure);
}
return(result);
}
public static async Task Publish(string camera, AreaOfInterest area, Frame frame, InterestingObject io)
{
bool result = true;
_loggedError = false;
_loggedNotConnected = false;
if (area != null && frame != null)
{
string baseTopic = Storage.GetGlobalString("MQTTMotionTopic");
baseTopic = baseTopic.Replace("{Camera}", camera);
baseTopic = baseTopic.Replace("{Area}", area.AOIName);
baseTopic = baseTopic.Replace("{Motion}", "on");
string topic = baseTopic;
topic = topic.Replace("{Object}", io.FoundObject.Label);
string payload = Storage.GetGlobalString("MQTTMotionPayload");
payload = payload.Replace("{File}", frame.Item.PendingFile);
payload = payload.Replace("{Confidence}", ((int)(io.FoundObject.Confidence * 100.0)).ToString());
if (payload.Contains("{Image}"))
{
payload = payload.Replace("{Image}", LoadImage(frame.Item.PendingFile));
}
payload = payload.Replace("{Object}", io.FoundObject.Label);
payload = payload.Replace("{Motion}", "on");
await SendToServer(topic, payload).ConfigureAwait(false);
}
}