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Add aspect-ratio measurement as a soft trimming signal, reported against every standard card size

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Barely Removable 2026-08-22 11:03:54 -07:00
parent b28305dd25
commit f464faca43
5 changed files with 139 additions and 2 deletions
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35
vision.py
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@ -643,6 +643,7 @@ def grade_card(images, api_key=None, model=None, effort=None, zoom_details=True)
can_measure = zoom_details and images and cardimage.available()
measured = cardimage.edge_wear_profile(images[0][0]) if can_measure else None
centering = cardimage.centering_profile(images[0][0]) if can_measure else None
aspect = cardimage.aspect_profile(images[0][0]) if can_measure else None
prompt_parts = []
if centering:
@ -705,6 +706,39 @@ def grade_card(images, api_key=None, model=None, effort=None, zoom_details=True)
"strip images to describe what the wear looks like and to "
"catch what the measurement does not look for at all, such as "
"a nick, a chip, or a crushed edge.")
if aspect:
standard_rows = "\n".join(
" {}: {:.4f} standard → {:.1f}% deviation".format(
name, data["standard_ratio"], data["deviation_percent"])
for name, data in aspect["against_standards"].items())
prompt_parts.append(
"MEASURED CARD PROPORTIONS — the width:height ratio of the card's "
"own detected outline in this photo, computed from the pixels: "
"{:.4f}. Compared against every standard card size, since which "
"one is relevant depends on the card's era, which is for you to "
"judge, not this measurement:\n{}\n"
"Use the deviation against whichever standard actually matches "
"the card type and era you're identifying it as — a modern card "
"compared against the tobacco-era ratio, or vice versa, will show "
"a large 'deviation' that means nothing at all.\n"
"Unlike the centering and edge numbers above, this one comes with "
"NO reliability check already applied, because the code cannot "
"tell a genuinely non-standard card apart from one simply "
"photographed at a slight rotation — both inflate the measured "
"box the same way. That call needs the photo, which only you "
"have: look at whether the card actually sits square in the "
"frame before trusting this number at all. A deviation under "
"roughly 3% against the RELEVANT standard is normal photo-crop "
"noise and means nothing either way. A larger one on a photo that "
"looks square-on is worth connecting to the corner-squareness "
"guidance above — it can corroborate a miscut or trimming "
"suspicion you already have visual grounds for, but it should "
"never be the ONLY reason you raise one; a rotated or "
"slightly-cropped photo produces exactly the same number on a "
"perfectly normal card. This only catches UNEVEN trimming (more "
"removed from one side than another) — it cannot see a symmetric "
"trim taken off all four sides evenly.".format(
aspect["measured_ratio"], standard_rows))
if crops:
prompt_parts.append(
"The close-ups above are upscaled crops of the full card photo, each "
@ -734,6 +768,7 @@ def grade_card(images, api_key=None, model=None, effort=None, zoom_details=True)
"card_note": (parsed.get("card_note") or "").strip(),
"edge_measurements": measured,
"centering_measurement": centering,
"aspect_measurement": aspect,
"estimated_grade": _clean_grade(parsed.get("estimated_grade")),
"grade_low": low,
"grade_high": high,