56db9bf9d2
- Add FeatureExtractor for CLIP-based image/text feature extraction - Add ObjectiveMetricsCalculator for technical quality metrics - Add VLMEvaluator for vision language model evaluation - Add HybridQualityGate combining objective + VLM evaluation - Enhance CharacterMemory with visual feature support - Add quality optional dependency (torch, ftfy, regex) - Add unit tests for new modules 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
65 lines
1.9 KiB
Python
65 lines
1.9 KiB
Python
# Copyright (C) 2025 AIDC-AI
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# Tests for ObjectiveMetricsCalculator
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import pytest
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from pathlib import Path
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from pixelle_video.services.quality.objective_metrics import (
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ObjectiveMetricsCalculator,
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TechnicalMetrics,
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)
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class TestTechnicalMetrics:
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"""Tests for TechnicalMetrics dataclass"""
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def test_default_values(self):
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metrics = TechnicalMetrics()
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assert metrics.sharpness_score == 0.0
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assert metrics.overall_technical == 0.0
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assert metrics.issues == []
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def test_to_dict(self):
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metrics = TechnicalMetrics(
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sharpness_score=0.8,
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brightness_score=0.5,
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issues=["test issue"]
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)
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d = metrics.to_dict()
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assert d["sharpness_score"] == 0.8
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assert "test issue" in d["issues"]
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class TestObjectiveMetricsCalculator:
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"""Tests for ObjectiveMetricsCalculator"""
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def test_init_default(self):
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calc = ObjectiveMetricsCalculator()
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assert calc.sharpness_threshold == 0.3
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def test_init_custom(self):
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calc = ObjectiveMetricsCalculator(sharpness_threshold=0.5)
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assert calc.sharpness_threshold == 0.5
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def test_analyze_nonexistent_image(self):
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calc = ObjectiveMetricsCalculator()
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metrics = calc.analyze_image("/nonexistent/path.png")
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assert len(metrics.issues) > 0
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assert "failed" in metrics.issues[0].lower()
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def test_analyze_real_image(self, tmp_path):
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"""Test with a real image file"""
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from PIL import Image
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# Create test image
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img = Image.new("RGB", (256, 256), color=(128, 128, 128))
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img_path = tmp_path / "test.png"
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img.save(img_path)
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calc = ObjectiveMetricsCalculator()
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metrics = calc.analyze_image(str(img_path))
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assert 0.0 <= metrics.sharpness_score <= 1.0
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assert 0.0 <= metrics.brightness_score <= 1.0
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assert 0.0 <= metrics.overall_technical <= 1.0
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