Spaces:
Running
Running
File size: 3,321 Bytes
37e3d5a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 | #!/usr/bin/env python3
"""Tests for the stdlib objectness proxy (OSIM-lite), Plan 1.3 task #18.
Proves the property the Divine Eye needed: structural similarity that is invariant to
background colour and absolute brightness (the photo-vs-procedural axes), while still
separating different shapes. Pure stdlib, zero token.
Run: python3 forge/tests/test_objectness.py
"""
import struct
import sys
import tempfile
import unittest
import zlib
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "stage4_review"))
from objectness import cosine, descriptor, objectness_similarity # noqa: E402
PNG_SIG = b"\x89PNG\r\n\x1a\n"
def write_png(path, w, h, pixel_fn):
def chunk(tag, data):
return struct.pack(">I", len(data)) + tag + data + struct.pack(">I", zlib.crc32(tag + data) & 0xFFFFFFFF)
raw = bytearray()
for y in range(h):
raw.append(0)
for x in range(w):
raw += bytes(pixel_fn(x, y))
ihdr = struct.pack(">IIBBBBB", w, h, 8, 2, 0, 0, 0)
path.write_bytes(PNG_SIG + chunk(b"IHDR", ihdr) + chunk(b"IDAT", zlib.compress(bytes(raw), 9)) + chunk(b"IEND", b""))
def diag_bar(fg, bg):
# a thick diagonal bar (same shape/orientation regardless of colours)
def fn(x, y):
return fg if abs((x - y)) < 40 else bg
return fn
def horiz_bar(fg, bg):
def fn(x, y):
return fg if 90 <= y < 150 else bg
return fn
class ObjectnessTest(unittest.TestCase):
def setUp(self):
self.d = Path(tempfile.mkdtemp())
self.W = self.H = 240
# same diagonal shape, but opposite brightness AND opposite background
self.dark_on_white = self.d / "dark_on_white.png"
write_png(self.dark_on_white, self.W, self.H, diag_bar((40, 40, 44), (250, 250, 250)))
self.bright_on_dark = self.d / "bright_on_dark.png"
write_png(self.bright_on_dark, self.W, self.H, diag_bar((205, 205, 210), (18, 20, 26)))
# a different shape (horizontal bar)
self.horiz = self.d / "horiz.png"
write_png(self.horiz, self.W, self.H, horiz_bar((40, 40, 44), (250, 250, 250)))
def test_identical_descriptor_cosine_is_one(self):
a = descriptor(self.dark_on_white)
self.assertAlmostEqual(cosine(a, a), 1.0, places=6)
def test_invariant_to_background_and_brightness(self):
# SAME shape, opposite bg + opposite brightness -> must still score high
# (this is exactly where SSIM/IoU/edge collapse for photo-vs-procedural)
s = objectness_similarity(self.dark_on_white, self.bright_on_dark)
self.assertGreater(s, 0.9, f"expected high objectness for same shape, got {s}")
def test_separates_different_shapes(self):
diag_vs_horiz = objectness_similarity(self.dark_on_white, self.horiz)
same = objectness_similarity(self.dark_on_white, self.bright_on_dark)
self.assertLess(diag_vs_horiz, same, "different shapes must score below same-shape")
self.assertLess(diag_vs_horiz, 0.8, f"diagonal vs horizontal should be clearly lower, got {diag_vs_horiz}")
def test_score_bounded(self):
s = objectness_similarity(self.dark_on_white, self.horiz)
self.assertGreaterEqual(s, 0.0)
self.assertLessEqual(s, 1.0)
if __name__ == "__main__":
unittest.main(verbosity=2)
|