from sklearn.neural_network import MLPRegressorann = MLPRegressor(hidden_layer_sizes= tuple(100 for _ in range(10)))ann.fit(training_inputs, training_outputs)ann.predict([[1,1]])predicted_outputs = ann.predict(training_inputs)predicted_image_array = np.zeros_like(image_array)i = 0for row,rgbs in enumerate(predicted_image_array): for column in range(len(rgbs)): r,g,b = predicted_outputs[i] predicted_image_array[row][column] = [r*255,g*255,b*255] i += 1Image.fromarray(predicted_image_array)