Merge branch 'florence-2-fts-in-workflows' of github.com:roboflow/inf…

…erence into florence-2-fts-in-workflows

inference/core/entities/requests/inference.py

@@ -22,6 +22,7 @@ def __init__(self, **kwargs):
     model_config = ConfigDict(protected_namespaces=())
     id: str
     api_key: Optional[str] = ApiKey
+    usage_billable: bool = True
     start: Optional[float] = None
     source: Optional[str] = None
     source_info: Optional[str] = None

inference/core/interfaces/http/http_api.py

@@ -2270,6 +2270,7 @@ async def legacy_infer_from_request(
                             raise MissingServiceSecretError(
                                 "Service secret is required to disable inference usage tracking"
                             )
+                        logger.info("Not counting inference for usage")
                 else:
                     request_model_id = model_id
                 logger.debug(

inference/core/version.py

@@ -1,4 +1,4 @@
-__version__ = "0.26.0"
+__version__ = "0.26.1"
 
 
 if __name__ == "__main__":

inference/core/workflows/core_steps/analytics/line_counter/v2.py

@@ -26,6 +26,8 @@
 
 OUTPUT_KEY_COUNT_IN: str = "count_in"
 OUTPUT_KEY_COUNT_OUT: str = "count_out"
+OUTPUT_KEY_DETECTIONS_IN: str = "detections_in"
+OUTPUT_KEY_DETECTIONS_OUT: str = "detections_out"
 IN: str = "in"
 OUT: str = "out"
 DETECTIONS_IN_OUT_PARAM: str = "in_out"
@@ -86,6 +88,20 @@ def describe_outputs(cls) -> List[OutputDefinition]:
                 name=OUTPUT_KEY_COUNT_OUT,
                 kind=[INTEGER_KIND],
             ),
+            OutputDefinition(
+                name=OUTPUT_KEY_DETECTIONS_IN,
+                kind=[
+                    OBJECT_DETECTION_PREDICTION_KIND,
+                    INSTANCE_SEGMENTATION_PREDICTION_KIND,
+                ],
+            ),
+            OutputDefinition(
+                name=OUTPUT_KEY_DETECTIONS_OUT,
+                kind=[
+                    OBJECT_DETECTION_PREDICTION_KIND,
+                    INSTANCE_SEGMENTATION_PREDICTION_KIND,
+                ],
+            ),
         ]
 
     @classmethod
@@ -136,9 +152,13 @@ def run(
             )
         line_zone = self._batch_of_line_zones[metadata.video_identifier]
 
-        line_zone.trigger(detections=detections)
+        mask_in, mask_out = line_zone.trigger(detections=detections)
+        detections_in = detections[mask_in]
+        detections_out = detections[mask_out]
 
         return {
             OUTPUT_KEY_COUNT_IN: line_zone.in_count,
             OUTPUT_KEY_COUNT_OUT: line_zone.out_count,
+            OUTPUT_KEY_DETECTIONS_IN: detections_in,
+            OUTPUT_KEY_DETECTIONS_OUT: detections_out,
         }

inference/usage_tracking/collector.py

@@ -2,6 +2,7 @@
 import atexit
 import json
 import mimetypes
+import numbers
 import socket
 import sys
 import time
@@ -315,6 +316,7 @@ def _update_usage_payload(
         fps: float = 0,
     ):
         source = str(source) if source else ""
+        frames = frames if isinstance(frames, numbers.Number) else 0
         api_key_hash = self._calculate_api_key_hash(api_key=api_key)
         if not resource_id and resource_details:
             resource_id = UsageCollector._calculate_resource_hash(resource_details)
@@ -332,7 +334,9 @@ def _update_usage_payload(
                 source_usage["timestamp_start"] = time.time_ns()
             source_usage["timestamp_stop"] = time.time_ns()
             source_usage["processed_frames"] += frames if not inference_test_run else 0
-            source_usage["fps"] = round(fps, 2)
+            source_usage["fps"] = (
+                round(fps, 2) if isinstance(fps, numbers.Number) else 0
+            )
             source_usage["source_duration"] += (
                 frames / fps if fps and not inference_test_run else 0
             )
@@ -355,7 +359,7 @@ def record_usage(
         resource_id: str = "",
         inference_test_run: bool = False,
         fps: float = 0,
-    ) -> DefaultDict[str, Any]:
+    ):
         if not api_key:
             return
         if self._settings.opt_out and not api_key:
@@ -388,7 +392,7 @@ async def async_record_usage(
         resource_id: str = "",
         inference_test_run: bool = False,
         fps: float = 0,
-    ) -> DefaultDict[str, Any]:
+    ):
         if self._async_lock:
             async with self._async_lock:
                 self.record_usage(

tests/inference/unit_tests/usage_tracking/test_collector.py

@@ -855,3 +855,31 @@ def test_system_info_with_no_dedicated_deployment_id():
     }
     for k, v in expected_system_info.items():
         assert system_info[k] == v
+
+
+def test_record_malformed_usage():
+    # given
+    collector = UsageCollector()
+
+    # when
+    collector.record_usage(
+        source=None,
+        category="model",
+        frames=None,
+        api_key="fake",
+        resource_details=None,
+        resource_id=None,
+        inference_test_run=None,
+        fps=None,
+    )
+
+    # then
+    assert "fake" in collector._usage
+    assert "model:None" in collector._usage["fake"]
+    assert collector._usage["fake"]["model:None"]["processed_frames"] == 0
+    assert collector._usage["fake"]["model:None"]["fps"] == 0
+    assert collector._usage["fake"]["model:None"]["source_duration"] == 0
+    assert collector._usage["fake"]["model:None"]["category"] == "model"
+    assert collector._usage["fake"]["model:None"]["resource_id"] == None
+    assert collector._usage["fake"]["model:None"]["resource_details"] == "{}"
+    assert collector._usage["fake"]["model:None"]["api_key_hash"] == "fake"

tests/workflows/unit_tests/core_steps/analytics/test_line_counter_v2.py

@@ -63,8 +63,8 @@ def test_line_counter() -> None:
     )
 
     # then
-    assert frame1_result == {"count_in": 0, "count_out": 0}
-    assert frame2_result == {"count_in": 1, "count_out": 1}
+    assert frame1_result == {"count_in": 0, "count_out": 0, "detections_in": frame1_detections[[False, False, False, False]], "detections_out": frame1_detections[[False, False, False, False]]}
+    assert frame2_result == {"count_in": 1, "count_out": 1, "detections_in": frame2_detections[[True, False, False, False]], "detections_out": frame2_detections[[False, True, False, False]]}
 
 
 def test_line_counter_no_trackers() -> None: