language_identification_prediction.py

# pick random test data sample from one batch
x = random.randint(0, len(Xtest) - 1)

print("Sample:\n", test_df['Text'].to_numpy()[x], sep = "")

input = cv.transform([test_df['Text'].to_numpy()[x]]).toarray()

output = model.predict(input)
pred = np.argmax(output[0])    # finding max
print("\nPredicted: ", languages[pred])    # Picking the label from class_names based on the model output
print("Probability: ", output[0][pred])

output_true = test_df['language'].to_numpy()[x]

print("\nTrue: ", output_true)