add flush to print statements

birdnet_custom_v2.4/model.py

@@ -105,7 +105,7 @@ class Model(ModelBase):
 
         # Get  feature embeddings
         self.output_layer_index = output_details[0]["index"] - 1
-        print("Default classifier loaded")
+        print("Default classifier loaded", flush = True)
 
         # now load the custom classifier
         self.custom_classifier = tflite.Interpreter(
@@ -138,7 +138,7 @@ class Model(ModelBase):
         Returns:
             np.array: Feature embedding produces by the default birdnet CNN.
         """
-        print(" get embeddings")
+        print(" get embeddings", flush = True))
         self.model.resize_tensor_input(
             self.input_layer_index, [len(data), *data[0].shape]
         )

birdnet_custom_v2.4/preprocessor.py

@@ -43,7 +43,7 @@ class Preprocessor(ppb.PreprocessorBase):
         Returns:
             list: chunked audio data
         """
-        print("process audio data custom")
+        print("process audio data custom", flush=True)
         seconds = self.sample_secs
         minlen = 1.5
 
@@ -71,6 +71,7 @@ class Preprocessor(ppb.PreprocessorBase):
             "process audio data custom: complete, read ",
             str(len(self.chunks)),
             "chunks.",
+            flush=True
         )
 
         return self.chunks

birdnet_default_v2.4/preprocessor.py

@@ -43,7 +43,7 @@ class Preprocessor(ppb.PreprocessorBase):
         Returns:
             list: chunked audio data
         """
-        print("process audio data default")
+        print("process audio data default", flush=True)
         seconds = self.sample_secs
         minlen = 1.5
 
@@ -70,8 +70,7 @@ class Preprocessor(ppb.PreprocessorBase):
         print(
             "process audio data default: complete, read ",
             str(len(self.chunks)),
-            "chunks.",
-        )
+            "chunks.",flush=True)
 
         return self.chunks
 

google_bird_classification/preprocessor.py

@@ -45,7 +45,7 @@ class Preprocessor(ppb.PreprocessorBase):
         Returns:
             list: chunked audio data
         """
-        print("process audio data custom ")
+        print("process audio data custom", flush=True)
 
         self.chunks = []
 
@@ -66,6 +66,7 @@ class Preprocessor(ppb.PreprocessorBase):
             "process audio data google: complete, read ",
             str(len(self.chunks)),
             "chunks.",
+            flush=True
         )
 
         return self.chunks