Prevent filtering of empty images (#1424)

* Update data.py * Update data.py * Update config.py * Update data.py * Update data.py
tensorpack · Apr 15, 2020 · 963e510 · 963e510
1 parent 92aab65
commit 963e510
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diff --git a/examples/FasterRCNN/config.py b/examples/FasterRCNN/config.py
@@ -106,6 +106,8 @@ def __ne__(self, _):
 # whether the coordinates in your registered dataset are
 # absolute pixel values in range [0, W or H] or relative values in [0, 1]
 _C.DATA.ABSOLUTE_COORD = True
+# Filter Negative Samples from dataset
+_C.DATA.FILTER_EMPTY_ANNOTATIONS = True
 # Number of data loading workers.
 # In case of horovod training, this is the number of workers per-GPU (so you may want to use a smaller number).
 # Set to 0 to disable parallel data loading

diff --git a/examples/FasterRCNN/data.py b/examples/FasterRCNN/data.py
@@ -345,7 +345,8 @@ def get_train_dataflow():
     # Filter out images that have no gt boxes, but this filter shall not be applied for testing.
     # The model does support training with empty images, but it is not useful for COCO.
     num = len(roidbs)
-    roidbs = list(filter(lambda img: len(img["boxes"][img["is_crowd"] == 0]) > 0, roidbs))
+    if cfg.DATA.FILTER_EMPTY_ANNOTATIONS:
+        roidbs = list(filter(lambda img: len(img["boxes"][img["is_crowd"] == 0]) > 0, roidbs))       
     logger.info(
         "Filtered {} images which contain no non-crowd groudtruth boxes. Total #images for training: {}".format(
             num - len(roidbs), len(roidbs)