mirror of
https://github.com/igv/FSRCNN-TensorFlow.git
synced 2026-08-18 00:57:28 +08:00
gen.py: support for shrinking/expanding layers
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igv
@@ -41,24 +41,40 @@ def header1(file, n, d):
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file.write('//!SAVE FEATURE{}\n'.format((n//4)%(d//4) + 1))
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file.write('//!COMPONENTS 4\n')
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def header2(file, r, mi, m, n, s):
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def header2(file, d, n, s):
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base_header(file)
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file.write('//!DESC shrinking {}\n'.format((n//4)%(s//4) + 1))
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for i in range(d//4):
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file.write('//!BIND {}{}\n'.format("FEATURE", i + 1))
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file.write('//!SAVE SHRINKED{}\n'.format((n//4)%(s//4) + 1))
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file.write('//!COMPONENTS 4\n')
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def header3(file, r, mi, m, n, s, inp):
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base_header(file)
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file.write('//!DESC mapping {}_{}\n'.format(mi + 1, (n//4)%(s//4) + 1))
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for i in range(s//4):
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file.write('//!BIND {}{}\n'.format("FEATURE" if r == 0 and mi == 0 else "MODEL", i+1 + (0 if (r * m + mi) % 2 == 0 else 20)))
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file.write('//!BIND {}{}\n'.format(inp if r == 0 and mi == 0 else "MODEL", i+1 + (0 if (r * m + mi) % 2 == 0 else 20)))
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if mi == m-1 and (mi+1)*(r+1) > 1:
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file.write('//!BIND FEATURE{}\n'.format((n//4)%(s//4) + 1))
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file.write('//!BIND {}{}\n'.format(inp, (n//4)%(s//4) + 1))
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file.write('//!SAVE MODEL{}\n'.format((n//4)%(s//4) + 1 + (20 if (r * m + mi) % 2 == 0 else 0)))
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file.write('//!COMPONENTS 4\n')
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def header3(file, m, r, n, d):
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def header4(file, s, m, r, n, d):
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base_header(file)
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file.write('//!DESC sub-pixel convolution {}\n'.format((n//4)%(d//4) + 1))
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file.write('//!BIND MODEL{}\n'.format((n//4)%(d//4) + 1 + (20 if (r * m) % 2 == 1 else 0)))
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file.write('//!SAVE MODEL{}\n'.format((n//4)%(d//4) + 1 + (20 if (r * m) % 2 == 1 else 0)))
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file.write('//!DESC expanding {}\n'.format((n//4)%(d//4) + 1))
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for i in range(s//4):
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file.write('//!BIND MODEL{}\n'.format(i + 1 + (20 if (r * m) % 2 == 1 else 0)))
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file.write('//!SAVE EXPANDED{}\n'.format((n//4)%(d//4) + 1 + (20 if (r * m) % 2 == 1 else 0)))
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file.write('//!COMPONENTS 4\n')
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def header4(file, m, r, d, grl):
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def header5(file, m, r, n, d, inp):
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base_header(file)
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file.write('//!DESC sub-pixel convolution {}\n'.format((n//4)%(d//4) + 1))
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file.write('//!BIND {}{}\n'.format(inp, (n//4)%(d//4) + 1 + (20 if (r * m) % 2 == 1 else 0)))
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file.write('//!SAVE {}{}\n'.format(inp, (n//4)%(d//4) + 1 + (20 if (r * m) % 2 == 1 else 0)))
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file.write('//!COMPONENTS 4\n')
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def header6(file, m, r, d, inp, grl):
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base_header(file)
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file.write('//!WIDTH LUMA.w {} *\n'.format(scale))
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file.write('//!HEIGHT LUMA.h {} *\n'.format(scale))
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@@ -66,7 +82,7 @@ def header4(file, m, r, d, grl):
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if grl:
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file.write('//!BIND HOOKED\n')
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for i in range(d//4):
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file.write('//!BIND MODEL{}\n'.format(i+1 + (20 if (r * m) % 2 == 1 else 0)))
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file.write('//!BIND {}{}\n'.format(inp, i+1 + (20 if (r * m) % 2 == 1 else 0)))
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file.write('//!OFFSET -{}.0 -{}.0\n'.format(scale//2, scale//2))
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def main():
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@@ -75,6 +91,9 @@ def main():
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d, s, m, r = [int(i) for i in fname[7:fname.index('.')].split("_")]
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if s == 0:
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s = d
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shrinking = False
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else:
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shrinking = True
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dst = fname.replace("_", "-").replace("weights", "FSRCNNX_x{}_".format(scale)).replace("txt", "glsl")
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with open(dst, 'w') as file:
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@@ -94,9 +113,29 @@ def main():
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y, x = p%(feature_radius*2+1)-feature_radius, p//(feature_radius*2+1)-feature_radius
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p += 1
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file.write('res += vec4({}) * float(LUMA_texOff(vec2({},{})));\n'.format(format_weights(weights[l], n), x, y))
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if shrinking:
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ln = get_line_number("alpha1", fname)
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alphas = read_weights(fname, ln)
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file.write('res = max(res, vec4(0.0)) + vec4({}) * min(res, vec4(0.0));\n'.format(format_weights(alphas[0], n)))
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file.write('return res;\n')
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file.write('}\n\n')
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if shrinking:
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# Shrinking layer
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ln = get_line_number("w2", fname)
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weights = read_weights(fname, ln, d)
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ln = get_line_number("b2", fname)
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biases = read_weights(fname, ln)
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for n in range(0, s, 4):
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header2(file, d, n, s)
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file.write('vec4 hook()\n')
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file.write('{\n')
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file.write('vec4 res = vec4({});\n'.format(format_weights(biases[0], n)))
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for l in range(0, d, 4):
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file.write('res += mat4({},{},{},{}) * FEATURE{}_texOff(vec2(0.0));\n'.format(format_weights(weights[l], n), format_weights(weights[l+1], n), format_weights(weights[l+2], n), format_weights(weights[l+3], n), l//4+1))
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file.write('return res;\n')
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file.write('}\n\n')
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# Mapping layers
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for ri in range(r):
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for mi in range(m):
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@@ -104,8 +143,9 @@ def main():
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weights = read_weights(fname, ln, s*9)
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ln = get_line_number("b{}".format(mi + 3), fname)
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biases = read_weights(fname, ln)
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inp = "SHRINKED" if shrinking else "FEATURE"
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for n in range(0, s, 4):
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header2(file, ri, mi, m, n, s)
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header3(file, ri, mi, m, n, s, inp)
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file.write('vec4 hook()\n')
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file.write('{\n')
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file.write('vec4 res = vec4({});\n'.format(format_weights(biases[0], n)))
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@@ -118,7 +158,7 @@ def main():
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file.write('res += mat4({},{},{},{}) * {}{}_texOff(vec2({},{}));\n'.format(
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format_weights(weights[l], n), format_weights(weights[l+1], n),
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format_weights(weights[l+2], n), format_weights(weights[l+3], n),
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"FEATURE" if ri == 0 and mi == 0 else "MODEL",
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inp if ri == 0 and mi == 0 else "MODEL",
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idx + 1 + (20 if (ri * m + mi) % 2 == 1 else 0), x, y))
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ln = get_line_number("alpha{}".format(3 if mi == m - 1 else mi + 4), fname)
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alphas = read_weights(fname, ln)
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@@ -131,6 +171,26 @@ def main():
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file.write('return res;\n')
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file.write('}\n\n')
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if shrinking:
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# Expanding layer
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ln = get_line_number("w{}".format(m + 3), fname)
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weights = read_weights(fname, ln, d)
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ln = get_line_number("b{}".format(m + 3), fname)
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biases = read_weights(fname, ln)
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ln = get_line_number("alpha{}".format(m + 3), fname)
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alphas = read_weights(fname, ln)
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for n in range(0, d, 4):
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header4(file, s, m, r, n, d)
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file.write('vec4 hook()\n')
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file.write('{\n')
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file.write('vec4 res = vec4({});\n'.format(format_weights(biases[0], n)))
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for l in range(0, s, 4):
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file.write('res += mat4({},{},{},{}) * MODEL{}_texOff(vec2(0.0));\n'.format(format_weights(weights[l], n), format_weights(weights[l+1], n), format_weights(weights[l+2], n), format_weights(weights[l+3], n),
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l//4 + 1 + (20 if (r * m) % 2 == 1 else 0)))
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file.write('res = max(res, vec4(0.0)) + vec4({}) * min(res, vec4(0.0));\n'.format(format_weights(alphas[0], n)))
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file.write('return res;\n')
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file.write('}\n\n')
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# Sub-pixel convolution
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ln = get_line_number("w{}".format(m + 4), fname)
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weights = read_weights(fname, ln, dsize**2)
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@@ -152,8 +212,9 @@ def main():
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weights = list(reversed(weights))
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sort = [weights[id[l]].strip(",") for l in range(0, len(id))]
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inp = "EXPANDED" if shrinking else "MODEL"
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for n in range(0, d, 4):
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header3(file, m, r, n, d)
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header5(file, m, r, n, d, inp)
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file.write('vec4 hook()\n')
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file.write('{\n')
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file.write('vec4 res = vec4(0);\n')
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@@ -166,7 +227,7 @@ def main():
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s1 = radius*2+1 if j == 0 and dsize % 2 == 1 else radius*2
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for xi, x in enumerate(range(-radius + (0 if j == 0 and dsize % 2 == 1 else 1), radius + 1)):
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l = yi * s1 + xi
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file.write('dot(vec4({}), MODEL{}_texOff(vec2({},{}))){}\n'.format(format_weights(sort[l+total], n),
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file.write('dot(vec4({}), {}{}_texOff(vec2({},{}))){}\n'.format(format_weights(sort[l+total], n), inp,
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(n//4)%(d//4) + 1 + (20 if (r * m) % 2 == 1 else 0), x, y, ';' if l == s1 * s2 - 1 else '+'))
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total = total + l + 1
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file.write('return res;\n')
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@@ -176,17 +237,17 @@ def main():
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ln = get_line_number("b{}".format(m + 4), fname)
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biases = read_weights(fname, ln)
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grl = get_line_number("b{}".format(m + 5), fname)
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header4(file, m, r, d, grl)
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header6(file, m, r, d, inp, grl)
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file.write('vec4 hook()\n')
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file.write('{\n')
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file.write('float res = {};\n'.format(float(biases[0])))
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v = 1 + (20 if (r * m) % 2 == 1 else 0)
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file.write('vec2 fcoord = fract(MODEL{}_pos * MODEL{}_size);\n'.format(v, v))
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file.write('vec2 base = MODEL{}_pos + (vec2(0.5) - fcoord) * MODEL{}_pt;\n'.format(v, v))
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file.write('vec2 fcoord = fract({}{}_pos * {}{}_size);\n'.format(inp, v, inp, v))
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file.write('vec2 base = {}{}_pos + (vec2(0.5) - fcoord) * {}{}_pt;\n'.format(inp, v, inp, v))
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file.write('ivec2 index = ivec2(fcoord * vec2({}));\n'.format(scale))
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file.write('res += (MODEL{}_tex(base)'.format(v))
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file.write('res += ({}{}_tex(base)'.format(inp, v))
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for i in range(d//4-1):
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file.write('+MODEL{}_tex(base)'.format(i + 1 + v))
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file.write('+{}{}_tex(base)'.format(inp, i + 1 + v))
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file.write(')[index.y * {} + index.x];\n'.format(scale))
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if grl:
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