Adding model and dataset to the LFS

.gitattributes

@@ -0,0 +1,2 @@
+keypoint.csv filter=lfs diff=lfs merge=lfs -text
+point_history.csv filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -129,3 +129,5 @@ dmypy.json
 .pyre/
 
 .DS_Store
+
+.idea/

model/keypoint_classifier/keypoint_classifier.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+import numpy as np
+import tensorflow as tf
+
+
+class KeyPointClassifier(object):
+    def __init__(
+        self,
+        model_path='model/keypoint_classifier/keypoint_classifier.tflite',
+        num_threads=1,
+    ):
+        self.interpreter = tf.lite.Interpreter(model_path=model_path,
+                                               num_threads=num_threads)
+
+        self.interpreter.allocate_tensors()
+        self.input_details = self.interpreter.get_input_details()
+        self.output_details = self.interpreter.get_output_details()
+
+    def __call__(
+        self,
+        landmark_list,
+    ):
+        input_details_tensor_index = self.input_details[0]['index']
+        self.interpreter.set_tensor(
+            input_details_tensor_index,
+            np.array([landmark_list], dtype=np.float32))
+        self.interpreter.invoke()
+
+        output_details_tensor_index = self.output_details[0]['index']
+
+        result = self.interpreter.get_tensor(output_details_tensor_index)
+
+        result_index = np.argmax(np.squeeze(result))
+
+        return result_index

model/keypoint_classifier/keypoint_classifier_label.csv

@@ -0,0 +1,4 @@
+Open
+Close
+Pointer
+OK

model/point_history_classifier/point_history_classifier.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+import numpy as np
+import tensorflow as tf
+
+
+class PointHistoryClassifier(object):
+    def __init__(
+        self,
+        model_path='model/point_history_classifier/point_history_classifier.tflite',
+        score_th=0.5,
+        invalid_value=0,
+        num_threads=1,
+    ):
+        self.interpreter = tf.lite.Interpreter(model_path=model_path,
+                                               num_threads=num_threads)
+
+        self.interpreter.allocate_tensors()
+        self.input_details = self.interpreter.get_input_details()
+        self.output_details = self.interpreter.get_output_details()
+
+        self.score_th = score_th
+        self.invalid_value = invalid_value
+
+    def __call__(
+        self,
+        point_history,
+    ):
+        input_details_tensor_index = self.input_details[0]['index']
+        self.interpreter.set_tensor(
+            input_details_tensor_index,
+            np.array([point_history], dtype=np.float32))
+        self.interpreter.invoke()
+
+        output_details_tensor_index = self.output_details[0]['index']
+
+        result = self.interpreter.get_tensor(output_details_tensor_index)
+
+        result_index = np.argmax(np.squeeze(result))
+
+        if np.squeeze(result)[result_index] < self.score_th:
+            result_index = self.invalid_value
+
+        return result_index

model/point_history_classifier/point_history_classifier_label.csv

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+Stop
+Clockwise
+Counter Clockwise
+Move