0bf81caddbc64e81b8b2989e8dbb5a0ec49e489a,Security_and_MachineLearning/src/defensive_chap7/face_auth.py,,,#,11

Before Change

model = load_model(trained_model_weights)

// Use Loss=categorical_crossentropy.
print("Compile model.")
model.compile(loss="categorical_crossentropy",
              optimizer="adam",
              metrics=["accuracy"])

After Change

        // Prediction.
        preds = model.predict(x)[0]
        predict_idx = np.argmax(preds)

        // Final judgement.
        judge = "Reject"
        prob = preds[predict_idx] * 100
        if prob > THRESHOLD:
            judge = "Unlock"
        msg = "{} ({:.1f}%). res="{}"".format(classes[predict_idx], prob, judge)

Instances