fix: gradio example link instead of file

api/routers/camera_stream.py

@@ -44,7 +44,9 @@ async def websocket_detect(
     logger.info(f"Client ID >>{camera_id}<< Connected...")
 
     step_counter = itertools.count()
-    pipeline = ProcessingPipeline(detector, depth_model, safety_detector, redis)
+    pipeline = ProcessingPipeline(
+        detector, depth_model, safety_detector, redis, config=state.settings
+    )
 
     # Queue removing old images in case they were being stacked
     frame_queue: asyncio.Queue = asyncio.Queue(maxsize=1)

config/config.yaml

@@ -5,6 +5,7 @@ project_name: Tracking Config
 project_desc: |
   Tracking System for detection, providing real-time camera status throught a Dashboard.
 task: indoor
+experiment: false
 intervals:
   system_metrics_seconds: 3.0 # Logging system metrics every
   frames_summary_every: 30 # Number of frames to create a logs summary

config/settings.py

@@ -83,6 +83,7 @@ class AppConfig(BaseSettings):
     intervals: IntervalsConfig
     redis_url: str
     dagshub_user_token: str
+    experiment: bool
 
     @classmethod
     def settings_customise_sources(

main.py

@@ -32,6 +32,7 @@ async def lifespan(app: FastAPI):
     logger.info("Starting Server.... ")
     # asyncio.create_task(log_system_metrics(logger, logger_interval_sec=settings.intervals.system_metrics_seconds))
 
+    logger.info("Downloading Models..")
     detection_model_path = hf_fetch_model(
         repo_id="Ultralytics/YOLO26",
         filename=settings.yolo.model_name,
@@ -54,6 +55,7 @@ async def lifespan(app: FastAPI):
     )
     app.state.safety_detection_model = YOLO_Detector(safety_detection_path)
 
+    logger.info("Connecting to Redis Server...")
     app.state.redis = aioredis.from_url(settings.redis_url, decode_responses=True)
     # Checking connection to redis - TODO add to health check
     try:

services/pipeline.py

@@ -12,11 +12,12 @@ import json
 
 
 class ProcessingPipeline:
-    def __init__(self, detector, depth_model, safety_detector, redis):
+    def __init__(self, detector, depth_model, safety_detector, redis, config):
         self.detector = detector
         self.depth_model = depth_model
         self.safety_detector = safety_detector
         self.redis = redis
+        self.config = config
 
     def _decode_frame(self, fb):
         return cv.imdecode(np.frombuffer(fb, np.uint8), cv.IMREAD_COLOR)
@@ -39,7 +40,11 @@ class ProcessingPipeline:
         loop = asyncio.get_running_loop()
 
         with profile_step(
-            "frame_processing_time", decode_duration_seconds, camera_id, frame_count
+            "frame_processing_time",
+            decode_duration_seconds,
+            camera_id,
+            frame_count,
+            experiment=self.config.experiment,
         ):
             frame_bytes = await loop.run_in_executor(
                 None, self._decode_frame, frame_bytes
@@ -50,6 +55,7 @@ class ProcessingPipeline:
             detection_duration_seconds,
             camera_id,
             frame_count,
+            experiment=self.config.experiment,
         ):
             detection_task = loop.run_in_executor(
                 None, self.detector.detect, frame_bytes
@@ -68,7 +74,11 @@ class ProcessingPipeline:
         depth_points = []
         if boxes_center:
             with profile_step(
-                "depth_duration_seconds", depth_duration_seconds, camera_id, frame_count
+                "depth_duration_seconds",
+                depth_duration_seconds,
+                camera_id,
+                frame_count,
+                experiment=self.config.experiment,
             ):
                 depth_points = await loop.run_in_executor(
                     None, self.depth_model.calculate_depth, frame_bytes, boxes_center

tests/test_pipeline.py

@@ -24,11 +24,15 @@ async def test_pipeline_success(mock_deps):
     mock_deps["detector"].detect.return_value.detections = [mock_detection]
     mock_deps["safety"].detect.return_value = []  # No dangers
 
+    mock_config = MagicMock()
+    mock_config.experiment = False
+
     pipeline = ProcessingPipeline(
         detector=mock_deps["detector"],
         safety_detector=mock_deps["safety"],
         depth_model=mock_deps["depth"],
         redis=mock_deps["redis"],
+        config=mock_config,
     )
 
     with (
@@ -51,11 +55,15 @@ async def test_pipeline_success(mock_deps):
 async def test_pipeline_no_detections(mock_deps):
     mock_deps["detector"].detect.return_value.detections = []
 
+    mock_config = MagicMock()
+    mock_config.experiment = False
+
     pipeline = ProcessingPipeline(
         detector=mock_deps["detector"],
         safety_detector=mock_deps["safety"],
         depth_model=mock_deps["depth"],
         redis=mock_deps["redis"],
+        config=mock_config,
     )
 
     with (

utils/profiling.py

@@ -4,7 +4,13 @@ import mlflow
 
 
 @contextmanager
-def profile_step(expr_name: str, prometheus_logger, camera_id, frame_count=None):
+def profile_step(
+    expr_name: str,
+    prometheus_logger,
+    camera_id,
+    frame_count=None,
+    experiment: bool = False,
+):
     """With statement utility to time block of code"""
     start_time = time.time()
 
@@ -14,8 +20,9 @@ def profile_step(expr_name: str, prometheus_logger, camera_id, frame_count=None)
     finally:
         duration = round(time.time() - start_time, 4)
         prometheus_logger.labels(camera_id).observe(duration)
-        mlflow.log_metric(
-            expr_name,
-            duration,
-            frame_count,
-        )
+        if experiment:
+            mlflow.log_metric(
+                expr_name,
+                duration,
+                frame_count,
+            )