mirror of
https://github.com/NohamR/Reclass.git
synced 2026-05-10 19:59:21 +00:00
6a4cb47ed4
- Suppress PE_Frame on QsciScintilla in MenuBarStyle to eliminate the 1px dark (#171717) Fusion outline around the editor area - Add --screenshot flag for automated pixel regression testing - Add type inference engine (typeinfer.h) with hex pattern analysis - Show inferred type hints on hex nodes in compose output - Style workspace tree corner/header widgets to match theme - Fix integer overflow in compose.cpp array element addressing - Fix integer overflow in core.h structSpan calculation - Add bounds check on activePaneIdx in controller - Use QPointer for deferred dock lambda safety - Workspace delegate uses icon Normal/Disabled for viewed state
93 lines
3.0 KiB
Python
93 lines
3.0 KiB
Python
"""
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Pixel boundary test: validates no Fusion outline leak at the workspace→editor seam.
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Usage:
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python tests/test_pixels.py [screenshot.png]
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If no screenshot given, launches Reclass.exe --screenshot to grab one.
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Scans for the specific Fusion outline artifact: color (23,23,23) which is
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window.darker(140) for the VS2022 Dark theme background #1e1e1e.
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"""
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import sys, os, subprocess
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from PIL import Image
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from collections import defaultdict
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GRAB_PATH = os.path.join("build", "test_grab.png")
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def get_screenshot(path):
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if not os.path.exists(path):
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print(f"Launching Reclass.exe --screenshot {path}")
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subprocess.run(["./build/Reclass.exe", "--screenshot", path],
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timeout=15, check=True)
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return Image.open(path)
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def scan_for_artifact(img):
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"""Scan entire image for the Fusion outline color (23,23,23).
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Also find all near-black pixels (< 28,28,28) that aren't the
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theme background (30,30,30)."""
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w, h = img.size
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px = img.load()
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target = (23, 23, 23)
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bg = (30, 30, 30)
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target_hits = []
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dark_hits = defaultdict(list) # color → [(x,y), ...]
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for y in range(h):
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for x in range(w):
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r, g, b = px[x, y][:3]
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if r == target[0] and g == target[1] and b == target[2]:
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target_hits.append((x, y))
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elif r < 28 and g < 28 and b < 28 and (r, g, b) != (0, 0, 0):
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# Near-black but not pure black (text anti-aliasing) and not bg
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dark_hits[(r, g, b)].append((x, y))
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return target_hits, dark_hits
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def summarize_region(hits):
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"""Summarize a list of (x,y) hits."""
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if not hits:
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return "none"
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xs = [p[0] for p in hits]
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ys = [p[1] for p in hits]
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return (f"{len(hits)}px x=[{min(xs)}..{max(xs)}] y=[{min(ys)}..{max(ys)}] "
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f"size={max(xs)-min(xs)+1}x{max(ys)-min(ys)+1}")
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def main():
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path = sys.argv[1] if len(sys.argv) > 1 else GRAB_PATH
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img = get_screenshot(path)
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w, h = img.size
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print(f"Image: {w}x{h}")
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target_hits, dark_hits = scan_for_artifact(img)
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print(f"\n(23,23,23) Fusion outline pixels: {summarize_region(target_hits)}")
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if dark_hits:
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print(f"\nOther near-black pixels (< 28,28,28):")
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for c, positions in sorted(dark_hits.items(), key=lambda t: -len(t[1])):
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print(f" ({c[0]:3},{c[1]:3},{c[2]:3}): {summarize_region(positions)}")
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if target_hits:
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# Show row distribution (condensed)
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rows = defaultdict(list)
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for x, y in target_hits:
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rows[y].append(x)
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print(f"\n(23,23,23) row detail:")
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for y in sorted(rows.keys()):
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xs = sorted(rows[y])
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if len(xs) > 5:
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print(f" y={y}: {len(xs)}px x=[{xs[0]}..{xs[-1]}]")
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else:
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print(f" y={y}: {len(xs)}px x={xs}")
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print(f"\nFAIL: Found {len(target_hits)} Fusion outline pixels (23,23,23)")
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sys.exit(1)
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else:
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print("\nPASS: No Fusion outline artifact found")
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sys.exit(0)
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if __name__ == "__main__":
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main()
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