ilia
a43ab20df6
- vision/refine.py: tighten crops to the paper band (removes mat margins and hands beside receipts) and inpaint border-connected skin regions so fingers disappear from output - llm/vision.py: identify documents with a local Ollama vision model (qwen2.5vl); extracts vendor/date/total/form code and flags quality issues (fingers, blur, glare); falls back to Tesseract when down - pipeline: drop blank pages, dedupe consecutive captures of the same document, record refine/LLM fields in report and export summary
78 lines
2.4 KiB
Python
78 lines
2.4 KiB
Python
"""End-to-end orientation-detection tests against synthetic text pages.
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Skipped automatically if the tesseract binary isn't installed.
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"""
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from __future__ import annotations
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import shutil
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import cv2
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import numpy as np
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import pytest
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from PIL import Image, ImageDraw, ImageFont
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from paperpod.vision.orient import apply_rotation, auto_rotate
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pytestmark = pytest.mark.skipif(
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shutil.which("tesseract") is None, reason="tesseract binary not installed"
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)
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_FONT_CANDIDATES = [
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"/System/Library/Fonts/Helvetica.ttc",
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"/System/Library/Fonts/Supplemental/Arial.ttf",
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]
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def _font(size: int) -> ImageFont.FreeTypeFont | ImageFont.ImageFont:
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for path in _FONT_CANDIDATES:
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try:
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return ImageFont.truetype(path, size)
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except OSError:
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continue
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return ImageFont.load_default()
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def _text_page() -> np.ndarray:
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"""A tall white page with a few lines of real words (upright, 0 degrees).
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Rendered with a real TrueType font (not cv2.putText's blocky stroke
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font), which produces normal glyph shapes; cv2.putText text fragments
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into dozens of spurious single-character "words" when rotated sideways,
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which isn't representative of real documents/photos.
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"""
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img = Image.new("RGB", (400, 600), (255, 255, 255))
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draw = ImageDraw.Draw(img)
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font = _font(22)
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lines = [
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"INVOICE FROM ACME CORP",
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"Date: January 5, 2024",
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"Description of services rendered",
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"Thank you for your business",
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"Please remit payment within 30 days",
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]
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for i, line in enumerate(lines):
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draw.text((20, 80 + i * 60), line, fill=(0, 0, 0), font=font)
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return cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR)
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@pytest.mark.parametrize("applied_rotation", [0, 90, 180, 270])
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def test_auto_rotate_corrects_known_rotation(applied_rotation):
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"""Rotating upright text by N clockwise needs (360-N) clockwise to undo."""
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upright = _text_page()
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rotated_input = apply_rotation(upright, applied_rotation)
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corrected, result = auto_rotate(rotated_input)
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assert result.rotation == (360 - applied_rotation) % 360
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assert corrected.shape == upright.shape
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def test_apply_rotation_identity_at_zero():
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page = _text_page()
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assert np.array_equal(apply_rotation(page, 0), page)
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def test_apply_rotation_180_is_involutive():
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page = _text_page()
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twice = apply_rotation(apply_rotation(page, 180), 180)
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assert np.array_equal(twice, page)
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