Merge pull request #107 from clamsproject/102-fix-label-overpopulation

removes slate subtypes from training label set

metadata.py

@@ -30,11 +30,11 @@ def appmetadata() -> AppMetadata:
     # which had default mappings for each model.
     labelMap = [
         "B:bars",
-        "S:slate", "S-H:slate", "S-C:slate", "S-D:slate", "S-G:slate",
+        "S:slate",
         "W:other_opening", "L:other_opening", "O:other_opening", "M:other_opening",
         "I:chyron", "N:chyron", "Y:chyron",
         "C:credit", "R:credit",
-        "E:other_text", "K:other_text", "G:other_text", "T:other_text", "F:other_text" ]
+        "E:other_text", "K:other_text", "G:other_text", "T:other_text", "F:other_text"]
 
     metadata = AppMetadata(
         name="Scenes-with-text Detection",

modeling/__init__.py

@@ -2,8 +2,10 @@
 positive_label = 'POS'
 
 # full typology from https://github.com/clamsproject/app-swt-detection/issues/1
-FRAME_TYPES = ["B", "S", "S:H", "S:C", "S:D", "S:B", "S:G", "W", "L", "O",
+FRAME_TYPES = ["B", "S", "W", "L", "O",
                "M", "I", "N", "E", "P", "Y", "K", "G", "T", "F", "C", "R"]
+FRAME_TYPES_WITH_SUBTYPES = ["B", "SH", "SC", "SD", "SB", "SG", "W", "L", "O",
+                             "M", "I", "N", "E", "P", "Y", "K", "G", "T", "F", "C", "R"]
 
 # These are time frames that are typically static (that is, the text does not
 # move around or change as with rolling credits). These are frame names after