Merge pull request #80 from FocoosAI/hotfix/bbox-coordinates

hotfix(detection): fix wrong bbox coordinates

focoos/local_model.py

@@ -41,7 +41,6 @@
 from focoos.utils.vision import (
     get_postprocess_fn,
     image_preprocess,
-    scale_detections,
     sv_to_fai_detections,
 )
 
@@ -190,21 +189,18 @@ def infer(
         resize = None  #!TODO  check for segmentation
         if self.metadata.task == FocoosTask.DETECTION:
             resize = 640 if not self.metadata.im_size else self.metadata.im_size
-        logger.debug(f"Resize: {resize}")
+
         t0 = perf_counter()
         im1, im0 = image_preprocess(image, resize=resize)
+        logger.debug(f"Input image size: {im0.shape}, Resize to: {resize}")
         t1 = perf_counter()
         detections = self.runtime(im1.astype(np.float32))
 
         t2 = perf_counter()
 
         detections = self.postprocess_fn(
-            out=detections, im0_shape=(im0.shape[1], im0.shape[0]), conf_threshold=threshold
+            out=detections, im0_shape=(im0.shape[0], im0.shape[1]), conf_threshold=threshold
         )
-
-        if resize:
-            detections = scale_detections(detections, (resize, resize), (im0.shape[1], im0.shape[0]))
-
         out = sv_to_fai_detections(detections, classes=self.metadata.classes)
         t3 = perf_counter()
         latency = {

focoos/utils/vision.py

@@ -296,8 +296,8 @@ def det_postprocess(out: List[np.ndarray], im0_shape: Tuple[int, int], conf_thre
         sv.Detections: A sv.Detections object containing the filtered bounding boxes, class ids, and confidences.
     """
     cls_ids, boxes, confs = out
-    boxes[:, 0::2] *= im0_shape[1]
-    boxes[:, 1::2] *= im0_shape[0]
+    boxes[:, :, 0::2] *= im0_shape[1]
+    boxes[:, :, 1::2] *= im0_shape[0]
     high_conf_indices = (confs > conf_threshold).nonzero()
 
     return sv.Detections(

tests/test_local_model.py

@@ -189,10 +189,6 @@ def mock_infer_setup(
     mock_image_preprocess = mocker.patch("focoos.local_model.image_preprocess")
     mock_image_preprocess.return_value = (image_ndarray, image_ndarray)
 
-    # Mock scale_detections
-    mock_scale_detections = mocker.patch("focoos.local_model.scale_detections")
-    mock_scale_detections.return_value = mock_sv_detections
-
     # Mock sv_to_focoos_detections
     mock_sv_to_focoos_detections = mocker.patch("focoos.local_model.sv_to_fai_detections")
     mock_sv_to_focoos_detections.return_value = mock_focoos_detections.detections
@@ -219,7 +215,6 @@ def __call__(self, *args, **kwargs):
     return (
         mock_image_preprocess,
         mock_runtime_call,
-        mock_scale_detections,
         mock_sv_to_focoos_detections,
         mock_annotate,
     )

tests/utils/test_vision.py

@@ -208,9 +208,9 @@ def test_masks_to_xyxy():
 
 
 def test_det_post_process():
-    cls_ids = np.array([1, 2, 3])
-    boxes = np.array([[0.1, 0.2, 0.3, 0.4], [0.5, 0.6, 0.7, 0.8], [0.9, 1.0, 1.1, 1.2]])
-    confs = np.array([0.8, 0.9, 0.7])
+    cls_ids = np.array([[1, 2, 3]])
+    boxes = np.array([[[0.1, 0.2, 0.3, 0.4], [0.5, 0.6, 0.7, 0.8], [0.9, 1.0, 1.1, 1.2]]])
+    confs = np.array([[0.8, 0.9, 0.7]])
     out = [cls_ids, boxes, confs]
 
     im0_shape = (640, 480)
@@ -316,9 +316,9 @@ def test_instance_postprocess():
 def test_confidence_threshold_filtering():
     """Test that confidence threshold filtering works correctly"""
     out = [
-        np.array([0, 1, 2]),  # cls_ids
-        np.array([[0.1, 0.1, 0.3, 0.3], [0.4, 0.4, 0.6, 0.6], [0.7, 0.7, 0.9, 0.9]]),  # boxes
-        np.array([0.95, 0.55, 0.85]),  # confs
+        np.array([[0, 1, 2]]),  # cls_ids
+        np.array([[[0.1, 0.1, 0.3, 0.3], [0.4, 0.4, 0.6, 0.6], [0.7, 0.7, 0.9, 0.9]]]),  # boxes
+        np.array([[0.95, 0.55, 0.85]]),  # confs
     ]
 
     result = det_postprocess(out, (100, 100), conf_threshold=0.8)