Ignore nonpositive detection lengths when importing VIAME CSV

client/platform/desktop/backend/serializers/viame.spec.ts

@@ -246,6 +246,35 @@ describe('VIAME Python Compatibility Check', () => {
   });
 });
 
+describe('Detection length import', () => {
+  [0, -1, -2.5, 12.5].forEach((columnLength) => {
+    [undefined, 0, -1, -2.5, 7.5].forEach((attributeLength) => {
+      it(`imports positive lengths from column ${columnLength} and attribute ${attributeLength}`, async () => {
+        let csv = `0,1.png,0,10,10,20,20,1,${columnLength},fish,0.9,(atr) other 3`;
+        if (attributeLength !== undefined) {
+          csv += `,(atr) length ${attributeLength}`;
+        }
+        const [data] = await parse(Readable.from([csv]));
+        const track = Object.values(data.tracks)[0];
+        const feature = track.features[0];
+        const expected = attributeLength !== undefined && attributeLength > 0
+          ? attributeLength : columnLength;
+        expect(feature.attributes?.other).toBe(3);
+        const { attributes } = processTrackAttributes([track]);
+        if (expected > 0) {
+          expect(feature.attributes?.length).toBe(expected);
+          expect(feature.fishLength).toBe(expected);
+          expect(attributes).toHaveProperty('detection_length');
+        } else {
+          expect(feature.attributes).not.toHaveProperty('length');
+          expect(feature).not.toHaveProperty('fishLength');
+          expect(attributes).not.toHaveProperty('detection_length');
+        }
+      });
+    });
+  });
+});
+
 describe('Attribute value parsing', () => {
   it('keeps filename-like attribute values as full strings', async () => {
     const csv = [

client/platform/desktop/backend/serializers/viame.ts

@@ -379,12 +379,15 @@ function _parseFeature(row: string[]) {
     frame: rowInfo.frame,
     bounds: rowInfo.bounds,
   };
-  if (rowInfo.fishLength !== -1 && Number.isFinite(rowInfo.fishLength)) {
+  if (rowInfo.fishLength > 0 && Number.isFinite(rowInfo.fishLength)) {
     feature.fishLength = rowInfo.fishLength;
   }
   if (rowData.attributes) {
     feature.attributes = rowData.attributes;
   }
+  if (feature.attributes?.length !== undefined && Number(feature.attributes.length) <= 0) {
+    delete feature.attributes.length;
+  }
   const syncedFeature = syncDetectionLengthFields(feature);
   if (rowData.geoFeatureCollection.features.length > 0) {
     syncedFeature.geometry = rowData.geoFeatureCollection;

server/dive_utils/serializers/viame.py

@@ -68,12 +68,15 @@ def _resolve_detection_length(
     fish_length_from_column: float,
 ) -> Tuple[Dict[str, Any], Optional[float]]:
     """Resolve length from attributes.length or the VIAME length column."""
+    attributes = dict(attributes or {})
     attr_length: Optional[float] = None
     if attributes and 'length' in attributes:
         try:
             candidate = float(attributes['length'])
-            if candidate == candidate:  # not NaN
+            if candidate > 0:
                 attr_length = candidate
+            elif candidate <= 0:
+                attributes.pop('length')
         except (TypeError, ValueError):
             attr_length = None
 

server/tests/test_deserialize_viame_csv.py

@@ -22,3 +22,25 @@ def test_read_viame_csv(
         expected_tracks, sort_keys=True
     )
     assert json.dumps(attributes, sort_keys=True) == json.dumps(expected_attributes, sort_keys=True)
+
+
+@pytest.mark.parametrize("column_length", [0, -1, -2.5, 12.5])
+@pytest.mark.parametrize("attribute_length", [None, 0, -1, -2.5, 7.5])
+def test_import_detection_length(column_length, attribute_length):
+    row = f"0,1.png,0,10,10,20,20,1,{column_length},fish,0.9,(atr) other 3"
+    if attribute_length is not None:
+        row += f",(atr) length {attribute_length}"
+    converted, attributes, *_ = viame.load_csv_as_tracks_and_attributes([row])
+    feature = converted['tracks']['0']['features'][0]
+    expected = (
+        attribute_length if attribute_length is not None and attribute_length > 0 else column_length
+    )
+    assert feature['attributes']['other'] == 3
+    if expected > 0:
+        assert feature['attributes']['length'] == expected
+        assert feature['fishLength'] == expected
+        assert 'detection_length' in attributes
+    else:
+        assert 'length' not in feature['attributes']
+        assert 'fishLength' not in feature
+        assert 'detection_length' not in attributes