fix event logits

app.py

@@ -89,9 +89,9 @@ def inference(x, count_only_api, api_key, img_size=192, seq_len=64, stride_lengt
     period_lengths = np.zeros(len(all_frames) + seq_len + stride_length)
     periodicities = np.zeros(len(all_frames) + seq_len + stride_length)
     full_marks = np.zeros(len(all_frames) + seq_len + stride_length)
-    event_type_logits = np.zeros((len(all_frames) + seq_len + stride_length, 4))
+    event_type_logits = np.zeros((len(all_frames) + seq_len + stride_length, 6))
     period_length_overlaps = np.zeros(len(all_frames) + seq_len + stride_length)
-    event_type_logit_overlaps = np.zeros((len(all_frames) + seq_len + stride_length, 4))
+    event_type_logit_overlaps = np.zeros((len(all_frames) + seq_len + stride_length, 6))
     for _ in range(seq_len + stride_length):  # pad full sequence
         all_frames.append(all_frames[-1])
     batch_list = []
@@ -283,7 +283,7 @@ def inference(x, count_only_api, api_key, img_size=192, seq_len=64, stride_lengt
     
     # make a bar plot of the event type distribution
 
-    bar = px.bar(x=['single rope speed', 'double dutch', 'double unders', 'single bounce'], 
+    bar = px.bar(x=['single rope speed', 'double dutch', 'double unders', 'single bounce', 'double bounce', 'triple under', 'other'], 
                  y=event_type_probs,
                  template="plotly_dark",
                  title="Event Type Distribution",