| #------------------------------------------------------------- |
| # |
| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you under the Apache License, Version 2.0 (the |
| # "License"); you may not use this file except in compliance |
| # with the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, |
| # software distributed under the License is distributed on an |
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| # KIND, either express or implied. See the License for the |
| # specific language governing permissions and limitations |
| # under the License. |
| # |
| #------------------------------------------------------------- |
| |
| /* |
| * Simple utility to crop image of shape [N, 3 * Hin * Win] into [N, 3 * Hout * Wout] |
| * Assumption: Hout < Hin, Wout < Win and input contains values [0, ..] |
| */ |
| crop_rgb = function(matrix[double] input, int Hin, int Win, int Hout, int Wout) return (matrix[double] out) { |
| start_h = ceil((Hin - Hout) / 2) |
| end_h = start_h + Hout - 1 |
| start_w = ceil((Win - Wout) / 2) |
| end_w = start_w + Wout - 1 |
| mask = matrix(0, rows=Hin, cols=Win) |
| temp_mask = matrix(1, rows=Hout, cols=Wout) |
| mask[start_h:end_h, start_w:end_w] = temp_mask |
| mask = matrix(mask, rows=1, cols=Hin*Win) |
| mask = cbind(mask, mask, mask) |
| out = removeEmpty(target=(input+1), margin="cols", select=mask) - 1 |
| } |
| |
| /* |
| * Simple utility to crop image of shape [N, Hin * Win] into [N, Hout * Wout] |
| * Assumption: Hout < Hin, Wout < Win and input contains values [0, ..] |
| * |
| * Example PySpark script: |
| * import matplotlib.pyplot as plt |
| * from sklearn import datasets |
| * digits = datasets.load_digits() |
| * image = digits.images[3,].reshape(1, -1) |
| * plt.imshow(image.reshape(8,8), cmap=plt.cm.gray_r) |
| * plt.show() |
| * |
| * script = """ |
| * crop_grayscale = function(matrix[double] input, int Hin, int Win, int Hout, int Wout) return (matrix[double] out) { |
| * start_h = ceil((Hin - Hout) / 2) |
| * end_h = start_h + Hout - 1 |
| * start_w = ceil((Win - Wout) / 2) |
| * end_w = start_w + Wout - 1 |
| * mask = matrix(0, rows=Hin, cols=Win) |
| * temp_mask = matrix(1, rows=Hout, cols=Wout) |
| * mask[start_h:end_h, start_w:end_w] = temp_mask |
| * mask = matrix(mask, rows=1, cols=Hin*Win) |
| * out = removeEmpty(target=(input+1), margin="cols", select=mask) - 1 |
| * } |
| * Y = crop_grayscale(X, 8, 8, 6, 6) |
| * """ |
| * from systemml import MLContext, dml |
| * ml = MLContext(sc) |
| * script = dml(script).input(X=image).output("Y") |
| * out = ml.execute(script).get("Y").toNumPy() |
| * plt.imshow(out.reshape(6,6), cmap=plt.cm.gray_r) |
| * plt.show() |
| * |
| */ |
| crop_grayscale = function(matrix[double] input, int Hin, int Win, int Hout, int Wout) return (matrix[double] out) { |
| start_h = ceil((Hin - Hout) / 2) |
| end_h = start_h + Hout - 1 |
| start_w = ceil((Win - Wout) / 2) |
| end_w = start_w + Wout - 1 |
| mask = matrix(0, rows=Hin, cols=Win) |
| temp_mask = matrix(1, rows=Hout, cols=Wout) |
| mask[start_h:end_h, start_w:end_w] = temp_mask |
| mask = matrix(mask, rows=1, cols=Hin*Win) |
| out = removeEmpty(target=(input+1), margin="cols", select=mask) - 1 |
| } |
