py

utools.py

@@ -0,0 +1,21 @@
+import tflite_runtime.interpreter as tflite   
+import tflite_runtime
+import numpy as np
+ROWS_PER_FRAME=543
+def load_relevant_data_subset(df):
+    data_columns = ['x', 'y', 'z']
+    data=df[data_columns]
+    n_frames = int(len(data) / ROWS_PER_FRAME)#单个文件的总帧数
+    data = data.values.reshape(n_frames, ROWS_PER_FRAME, len(data_columns))
+    return data.astype(np.float32)
+
+def mark_pred(model_path_1,aa):
+    interpreter = tflite.Interpreter(model_path_1)
+    found_signatures = list(interpreter.get_signature_list().keys())
+    prediction_fn = interpreter.get_signature_runner("serving_default")
+    output_1 = prediction_fn(inputs=aa)
+    return output_1
+
+def softmax(x, axis=None):
+    x_exp = np.exp(x - np.max(x, axis=axis, keepdims=True))
+    return x_exp / np.sum(x_exp, axis=axis, keepdims=True)