rename bounding_boxes file to cartesian_coordinate for better meaning

Author: xiuliren

chunkflow/chunk/affinity_map/base.py

@@ -2,7 +2,7 @@
 
 import numpy as np
 
-from chunkflow.lib.bounding_boxes import Cartesian
+from chunkflow.lib.cartesian_coordinate import Cartesian
 from chunkflow.chunk import Chunk
 
 class AffinityMap(Chunk):

chunkflow/chunk/base.py

@@ -16,7 +16,7 @@
 import cc3d
 from cloudvolume.lib import yellow, Bbox
 
-from chunkflow.lib.bounding_boxes import BoundingBox, Cartesian
+from chunkflow.lib.cartesian_coordinate import BoundingBox, Cartesian
 
 # from typing import Tuple
 # Offset = Tuple[int, int, int]

chunkflow/chunk/image/convnet/inferencer.py

@@ -11,7 +11,7 @@
 import numpy as np
 from tqdm import tqdm
 
-from chunkflow.lib.bounding_boxes import Cartesian, to_cartesian
+from chunkflow.lib.cartesian_coordinate import Cartesian, to_cartesian
 
 from .patch.base import PatchInferencerBase
 from chunkflow.chunk import Chunk

chunkflow/chunk/probability_map.py

@@ -0,0 +1,38 @@
+import math
+
+import numpy as np
+from .base import Chunk
+from skimage.feature import peak_local_max
+
+from chunkflow.lib.cartesian_coordinate import Cartesian
+
+
+class ProbabilityMap(Chunk):
+    def __init__(self, array: np.ndarray, voxel_offset: Cartesian = None, voxel_size: Cartesian = None):
+        super().__init__(array, voxel_offset, voxel_size)
+        assert np.issubdtype(self.dtype, np.floating)
+
+    def detect_points(self, min_distance: int = 1, threshold_abs: float=None, 
+            threshold_rel: float = None, exclude_border: int=True, indices: bool=True, 
+            num_peaks_per_label: int = math.inf):
+        # prob = chunk.array.copy()
+        prob = self.array
+        prob -= np.mean(prob)
+        prob[prob<0.] = 0.
+        prob /= prob.max()
+
+        coords = peak_local_max(
+            prob, 
+            min_distance=min_distance, 
+            threshold_abs=threshold_abs,
+            threshold_rel=threshold_rel,
+            exclude_border=exclude_border,
+            indices=indices,
+            num_peaks_per_label = num_peaks_per_label,
+        )
+
+        confidences = prob[coords[:, 0], coords[:, 1], coords[:, 2]]
+        
+        coords += np.asarray(self.voxel_offset, dtype=coords.dtype).reshape(1,3)
+        print('number of detected points: ', coords.shape[0])
+        return coords, confidences

chunkflow/chunk/segmentation.py

@@ -11,7 +11,7 @@
 
 # from ...lib.gala import evaluate
 from chunkflow.lib.gala import evaluate
-from chunkflow.lib.bounding_boxes import Cartesian
+from chunkflow.lib.cartesian_coordinate import Cartesian
 
 import kimimaro
 import fastremap

chunkflow/flow/flow.py

@@ -21,7 +21,7 @@
 from cloudfiles import CloudFiles
 
 from chunkflow.lib.aws.sqs_queue import SQSQueue
-from chunkflow.lib.bounding_boxes import Cartesian, BoundingBox, BoundingBoxes
+from chunkflow.lib.cartesian_coordinate import Cartesian, BoundingBox, BoundingBoxes
 from chunkflow.lib.synapses import Synapses
 
 from chunkflow.chunk import Chunk

chunkflow/flow/load_pngs.py

@@ -3,7 +3,7 @@
 
 import numpy as np
 
-from chunkflow.lib.bounding_boxes import BoundingBox, Cartesian
+from chunkflow.lib.cartesian_coordinate import BoundingBox, Cartesian
 from chunkflow.chunk import Chunk
 
 from tqdm import tqdm

chunkflow/flow/load_precomputed.py

@@ -4,7 +4,7 @@
 from cloudvolume import CloudVolume
 from cloudfiles import CloudFiles
 
-from chunkflow.lib.bounding_boxes import BoundingBox, Cartesian
+from chunkflow.lib.cartesian_coordinate import BoundingBox, Cartesian
 from chunkflow.chunk.validate import validate_by_template_matching
 from tinybrain import downsample_with_averaging
 from chunkflow.chunk import Chunk

chunkflow/flow/mask.py

@@ -4,7 +4,7 @@
 from cloudvolume import CloudVolume
 
 from chunkflow.chunk import Chunk
-from chunkflow.lib.bounding_boxes import Cartesian
+from chunkflow.lib.cartesian_coordinate import Cartesian
 from .base import OperatorBase
 
 

chunkflow/flow/plugin.py

@@ -7,7 +7,7 @@
 
 import numpy as np
 
-from chunkflow.lib.bounding_boxes import Cartesian
+from chunkflow.lib.cartesian_coordinate import Cartesian
 
 from .base import OperatorBase