wip

model_pred/check_model_on_cpu/check.py

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+import numpy as np
+import tensorflow as tf
+from tensorflow import keras
+
+model = keras.models.load_model('../sign_car_detection_model')
+
+
+class_names = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z', 'del', 'nothing', 'space']
+
+path_to_img = 'C_test_own.png'
+
+def pred_sign_char(path_to_img: str):
+
+    pred = []
+    test_image = tf.keras.utils.load_img(path_to_img, target_size = (256, 256))
+    test_image = tf.keras.utils.img_to_array(test_image)
+    test_image = np.expand_dims(test_image, axis = 0)
+    result = model.predict(test_image)
+
+
+    print(result)
+    pred.append(class_names[np.argmax(result)])
+    print(pred)
+    return pred[0]
+
+    
+pred_sign_char(path_to_img)