mnist_cnn: Prototype code for image downscaling

Author: jonnor

examples/mnist_cnn/convert.py

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+
+import sys
+import numpy
+import skimage.io
+
+p = sys.argv[1]
+o = sys.argv[2]
+a = numpy.load(p)
+print(a.shape)
+
+skimage.io.imsave(o, a)

examples/mnist_cnn/downscale.py

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+
+import array
+
+def average2d(inp, rowstride, x, y, size):
+    acc = 0
+    for r in range(y, y+size):
+        for c in range(x, x+size):
+            acc += inp[(r*rowstride)+c]
+
+    avg = acc // (size*size)
+    return avg
+
+def downscale(inp, out, in_size, out_size):
+
+    # assumes square, single-channel (grayscale) images
+    assert len(inp) == in_size*in_size
+    assert len(out) == out_size*out_size
+    assert (in_size % out_size) == 0, (in_size, out_size)
+    factor = in_size // out_size
+
+    for row in range(out_size):
+        for col in range(out_size):
+            o = (row * out_size) + col
+            out[o] = average2d(inp, in_size, col*factor, row*factor, factor)
+
+
+def test_downscale():
+
+    import npyfile
+
+    shape, data = npyfile.load('inp.npy')
+    print(data)
+
+    npyfile.save('orig.npy', data, shape)
+
+    insize = 96
+    outsize = 32
+    out = array.array('B', (0 for _ in range(outsize*outsize)))
+
+    downscale(data, out, insize, outsize)
+
+    npyfile.save('out.npy', out, (outsize, outsize))
+
+
+
+if __name__ == '__main__':
+    test_downscale()

examples/mnist_cnn/downscalecheck.py

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+
+import skimage.io
+import skimage.color
+import skimage.transform
+import numpy
+
+p = 'data/rps-cv-images/rock/dnss2tOuxRmL0ZjZ.png'
+a = skimage.io.imread(p)
+print(a.shape, a.dtype)
+
+o = skimage.color.rgb2gray(a)
+o = skimage.transform.resize(o, (96, 96))
+o = (o * 255).astype(numpy.uint8)
+
+print(o.shape, o.dtype)
+
+numpy.save('inp.npy', o, allow_pickle=False)