Fu DaiandClaude Opus 4.8
1a585693be
FastAPI service wrapping the Surya-OCR-2 model (datalab-to) served through vLLM: legacy /v1/api/ai/* endpoints, an OpenAI-compatible /v1/chat/completions endpoint, a coalescing request batcher, a local OCR CLI, Docker packaging, multilingual example outputs, and quantization/concurrency benchmarks. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
49 lines
1.5 KiB
Python
49 lines
1.5 KiB
Python
import json
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from scripts.quant.bbox_iou import iou, match_boxes, bbox_iou_over_dirs
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def test_iou_identical_is_one():
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assert iou([0, 0, 10, 10], [0, 0, 10, 10]) == 1.0
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def test_iou_disjoint_is_zero():
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assert iou([0, 0, 10, 10], [20, 20, 30, 30]) == 0.0
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def test_iou_half_overlap():
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# two 10x10 boxes overlapping in a 10x5 region -> 50/150
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assert abs(iou([0, 0, 10, 10], [0, 5, 10, 15]) - (50 / 150)) < 1e-9
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def test_match_boxes_counts_missed_and_extra():
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ref = [[0, 0, 10, 10], [100, 100, 110, 110]]
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cand = [[0, 0, 10, 10], [200, 200, 210, 210], [300, 300, 310, 310]]
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result = match_boxes(ref, cand, iou_threshold=0.5)
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assert result["matched"] == 1
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assert result["missed"] == 1 # ref box at 100,100 unmatched
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assert result["extra"] == 2 # two cand boxes unmatched
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assert abs(result["mean_matched_iou"] - 1.0) < 1e-9
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def test_match_boxes_empty():
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result = match_boxes([], [], iou_threshold=0.5)
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assert result == {"matched": 0, "missed": 0, "extra": 0, "mean_matched_iou": 0.0}
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def test_bbox_iou_over_dirs(tmp_path):
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ref_dir = tmp_path / "ref"
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cand_dir = tmp_path / "cand"
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ref_dir.mkdir()
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cand_dir.mkdir()
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(ref_dir / "p1.json").write_text(json.dumps({"boxes": [[0, 0, 10, 10]]}))
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(cand_dir / "p1.json").write_text(json.dumps({"boxes": [[0, 0, 10, 10]]}))
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result = bbox_iou_over_dirs(ref_dir, cand_dir, iou_threshold=0.5)
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assert abs(result["mean_bbox_iou"] - 1.0) < 1e-9
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assert result["mean_missed_lines"] == 0.0
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assert result["mean_extra_lines"] == 0.0
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