feat: added tracking stage, per-session logic, optimal detection pairing

Author: mohamedelabbas1996

ami/jobs/models.py

@@ -17,6 +17,7 @@
 from ami.jobs.tasks import run_job
 from ami.main.models import Deployment, Project, SourceImage, SourceImageCollection
 from ami.ml.models import Pipeline
+from ami.ml.tracking import perform_tracking_for_job
 from ami.utils.schemas import OrderedEnum
 
 logger = logging.getLogger(__name__)
@@ -502,6 +503,7 @@ def run(cls, job: "Job"):
             status=JobState.SUCCESS,
             progress=1,
         )
+        perform_tracking_for_job(job)
         job.update_status(JobState.SUCCESS, save=False)
         job.finished_at = datetime.datetime.now()
         job.save()

ami/main/migrations/0067_detection_next_detection.py

@@ -0,0 +1,25 @@
+# Generated by Django 4.2.10 on 2025-05-29 16:21
+
+from django.db import migrations, models
+import django.db.models.deletion
+
+
+class Migration(migrations.Migration):
+    dependencies = [
+        ("main", "0066_alter_taxalist_projects_alter_taxon_projects_tag_and_more"),
+    ]
+
+    operations = [
+        migrations.AddField(
+            model_name="detection",
+            name="next_detection",
+            field=models.OneToOneField(
+                blank=True,
+                help_text="The detection that follows this one in the tracking sequence.",
+                null=True,
+                on_delete=django.db.models.deletion.SET_NULL,
+                related_name="previous_detection",
+                to="main.detection",
+            ),
+        ),
+    ]

ami/main/models.py

@@ -2137,6 +2137,14 @@ class Detection(BaseModel):
     classifications: models.QuerySet["Classification"]
     source_image_id: int
     detection_algorithm_id: int
+    next_detection = models.OneToOneField(
+        "self",
+        on_delete=models.SET_NULL,
+        null=True,
+        blank=True,
+        related_name="previous_detection",
+        help_text="The detection that follows this one in the tracking sequence.",
+    )
 
     # def bbox(self):
     #     return (

ami/ml/models/pipeline.py

@@ -47,7 +47,6 @@
     SourceImageResponse,
 )
 from ami.ml.tasks import celery_app, create_detection_images
-from ami.ml.tracking import assign_occurrences_by_tracking
 from ami.utils.requests import create_session
 
 logger = logging.getLogger(__name__)
@@ -882,14 +881,14 @@ def save_results(
 
     # Create a new occurrence for each detection (no tracking yet)
     # @TODO remove when we implement tracking!
-    # create_and_update_occurrences_for_detections(
-    #     detections=detections,
-    #     logger=job_logger,
-    # )
-    job_logger.info(f"Creating occurrences for {len(detections)} detections ")
-    job_logger.info("type logger: " + str(type(job_logger)))
-
-    assign_occurrences_by_tracking(detections=detections, logger=job_logger)
+    create_and_update_occurrences_for_detections(
+        detections=detections,
+        logger=job_logger,
+    )
+    # job_logger.info(f"Creating occurrences for {len(detections)} detections ")
+    # check if every image in the sessions in processed
+
+    # assign_occurrences_by_tracking(detections=detections, logger=job_logger)
 
     # Update precalculated counts on source images and events
     source_images = list(source_images)