diff --git a/trapdata/api/api.py b/trapdata/api/api.py
index b9be78c..4969b79 100644
--- a/trapdata/api/api.py
+++ b/trapdata/api/api.py
@@ -81,11 +81,24 @@ def _get_source_image(source_images, source_image_id):
 
 
 @app.post("/pipeline/process")
+@app.post("/pipeline/process/")
 async def process(data: PipelineRequest) -> PipelineResponse:
+    # Ensure that the source images are unique, filter out duplicates
+    source_images_index = {
+        source_image.id: source_image for source_image in data.source_images
+    }
+    incoming_source_images = list(source_images_index.values())
+    if len(incoming_source_images) != len(data.source_images):
+        logger.warning(
+            f"Removed {len(data.source_images) - len(incoming_source_images)} duplicate source images"
+        )
+
     source_image_results = [
-        SourceImageResponse(**image.model_dump()) for image in data.source_images
+        SourceImageResponse(**image.model_dump()) for image in incoming_source_images
+    ]
+    source_images = [
+        SourceImage(**image.model_dump()) for image in incoming_source_images
     ]
-    source_images = [SourceImage(**image.model_dump()) for image in data.source_images]
 
     start_time = time.time()
     detector = MothDetector(
diff --git a/trapdata/api/models/classification.py b/trapdata/api/models/classification.py
index 7f9b1bc..dc2266a 100644
--- a/trapdata/api/models/classification.py
+++ b/trapdata/api/models/classification.py
@@ -3,7 +3,6 @@
 
 import numpy as np
 import torch
-from rich import print
 
 from trapdata.common.logs import logger
 from trapdata.ml.models.classification import (
@@ -37,6 +36,9 @@ def __init__(
         self.detections = list(detections)
         self.results: list[Detection] = []
         super().__init__(*args, **kwargs)
+        logger.info(
+            f"Initialized {self.__class__.__name__} with {len(self.detections)} detections"
+        )
 
     def get_dataset(self):
         return ClassificationImageDataset(
@@ -89,19 +91,32 @@ def save_results(
                 timestamp=datetime.datetime.now(),
             )
             self.update_classification(detection, classification)
-            print(detection)
+            # print(detection)
         self.results.extend(self.detections)
         logger.info(f"Saving {len(self.results)} detections with classifications")
         return self.results
 
-    def update_classification(self, detection: Detection, new_classification: Classification) -> None:
+    def update_classification(
+        self, detection: Detection, new_classification: Classification
+    ) -> None:
         # Remove all existing classifications from this algorithm
-        detection.classifications = [c for c in detection.classifications if c.algorithm != self.name]
+        detection.classifications = [
+            c for c in detection.classifications if c.algorithm != self.name
+        ]
         # Add the new classification for this algorithm
         detection.classifications.append(new_classification)
+        logger.debug(
+            f"Updated classification for detection {detection.bbox}. Total classifications: {len(detection.classifications)}"
+        )
 
     def run(self) -> list[Detection]:
+        logger.info(
+            f"Starting {self.__class__.__name__} run with {len(self.results)} detections"
+        )
         super().run()
+        logger.info(
+            f"Finished {self.__class__.__name__} run. Processed {len(self.results)} detections"
+        )
         return self.results
 
 
@@ -134,8 +149,11 @@ def save_results(
                 # Specific to binary classification / the filter model
                 terminal=False,
             )
-            print(detection)
-            if not self.filter_results or classification.classification == self.positive_binary_label:
+            # print(detection)
+            if (
+                not self.filter_results
+                or classification.classification == self.positive_binary_label
+            ):
                 self.update_classification(detection, classification)
 
         self.results.extend(self.detections)
@@ -149,15 +167,11 @@ class MothClassifierPanama(
     pass
 
 
-class MothClassifierPanama2024(
-    MothClassifier, PanamaMothSpeciesClassifier2024
-):
+class MothClassifierPanama2024(MothClassifier, PanamaMothSpeciesClassifier2024):
     pass
 
 
-class MothClassifierUKDenmark(
-    MothClassifier, UKDenmarkMothSpeciesClassifier2024
-):
+class MothClassifierUKDenmark(MothClassifier, UKDenmarkMothSpeciesClassifier2024):
     pass
 
 
diff --git a/trapdata/api/models/localization.py b/trapdata/api/models/localization.py
index f4198ed..91497f2 100644
--- a/trapdata/api/models/localization.py
+++ b/trapdata/api/models/localization.py
@@ -2,8 +2,6 @@
 import datetime
 import typing
 
-from rich import print
-
 from trapdata.common.logs import logger
 from trapdata.ml.models.localization import (
     MothObjectDetector_FasterRCNN_2023,
@@ -98,7 +96,7 @@ def save_detection(image_id, coords):
                 timestamp=datetime.datetime.now(),
                 crop_image_url=crop_url,
             )
-            print(detection)
+            # print(detection)
             return detection
 
         with concurrent.futures.ThreadPoolExecutor() as executor:
diff --git a/trapdata/cli/base.py b/trapdata/cli/base.py
index eecf487..616c645 100644
--- a/trapdata/cli/base.py
+++ b/trapdata/cli/base.py
@@ -93,7 +93,7 @@ def run_api():
     """
     import uvicorn
 
-    uvicorn.run("trapdata.api.api:app", host="0.0.0.0", port=2001, reload=True)
+    uvicorn.run("trapdata.api.api:app", host="0.0.0.0", port=2000, reload=True)
 
 
 if __name__ == "__main__":