Carry an image state through the socket.io upload

README.md

@@ -100,7 +100,10 @@ The detector also has a **SocketIO** upload endpoint that can be used to upload
 - `metadata`: a dictionary representing the image metadata. If metadata contains detections and/or annotations, UUIDs for the classes are automatically determined based on the category names. Metadata should follow the schema of the `ImageMetadata` data class.
 - `upload_priority`: Optional boolean flag to prioritize the upload (defaults to False)
 
-The endpoint returns None if the upload was successful and an error message otherwise.
+The endpoint returns `{'status': 'OK'}` if the upload was successful and `{'error': '<message>'}` otherwise.
+
+Besides detections and annotations, the metadata may carry `tags`, `source`, `created` and `state`.
+`state` names the state the image should enter the loop in (e.g. `trash`); when it is omitted the loop applies its own default (`inbox`).
 
 For both ways to upload an image, the tag `picked_by_system` is automatically added to the image metadata.
 

learning_loop_node/data_classes/image_metadata.py

@@ -46,6 +46,8 @@ class ImageMetadata():
         'description': 'Creation date of the image'})
     source: Optional[str] = field(default=None, metadata={
         'description': 'Source of the image'})
+    state: str | None = field(default=None, metadata={
+        'description': 'State the image should enter the loop in (e.g. "trash"); None uses the loop default'})
 
     def __len__(self):
         return len(self.box_detections) + len(self.point_detections) + len(self.segmentation_detections) + len(self.classification_detections)

learning_loop_node/detector/detector_node.py

@@ -339,7 +339,9 @@ async def upload(sid, data: Dict) -> Dict:
                 - bytes: bytes of the ndarray (retrieved via `ndarray.tobytes(order='C')`)
                 - dtype: data type of the ndarray as string (e.g. `uint8`, `float32`, etc.)
                 - shape: shape of the ndarray as tuple of ints (e.g. `(480, 640, 3)`)
-            - metadata: The metadata for the image (optional)
+            - metadata: The metadata for the image (optional). Besides detections and annotations it
+              may carry `tags`, `source`, `created` and `state`. A `state` of e.g. "trash" makes the
+              loop file the image into that state instead of its default one.
             - upload_priority: Whether to upload with priority (optional)
             """
             self.log.debug('Processing upload via socketio.')

learning_loop_node/tests/detector/test_client_communication.py

@@ -89,6 +89,23 @@ async def test_sio_upload(test_detector_node: DetectorNode, sio_client):
     assert len(get_outbox_files(test_detector_node.outbox)) == 2, 'There should be one image and one .json file.'
 
 
+async def test_sio_upload_with_state(test_detector_node: DetectorNode, sio_client):
+    """The state from the metadata has to reach the json file the outbox uploads to the loop."""
+    assert len(get_outbox_files(test_detector_node.outbox)) == 0
+
+    image = np.array(Image.open(test_image_path))
+    result = await sio_client.call('upload', {
+        'image': {'bytes': image.tobytes(), 'shape': image.shape, 'dtype': str(image.dtype)},
+        'metadata': {'state': 'trash'},
+    })
+    assert result.get('status') == 'OK'
+
+    json_files = [file for file in get_outbox_files(test_detector_node.outbox) if file.endswith('.json')]
+    assert len(json_files) == 1
+    with open(json_files[0]) as f:
+        assert json.load(f)['state'] == 'trash'
+
+
 # NOTE: This test seems to be flaky.
 async def test_about_endpoint(test_detector_node: DetectorNode):
     await asyncio.sleep(16)