Create test_ensemble.py
Browse files- test_ensemble.py +78 -0
test_ensemble.py
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#!/usr/bin/env python3
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"""
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Basic testing script for the Enhanced Ensemble Model
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"""
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import unittest
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from PIL import Image
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import numpy as np
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from app import EnhancedEnsembleMemeAnalyzer
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class TestEnhancedEnsemble(unittest.TestCase):
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@classmethod
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def setUpClass(cls):
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"""Initialize the analyzer once for all tests"""
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cls.analyzer = EnhancedEnsembleMemeAnalyzer()
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# Create a simple test image
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cls.test_image = Image.fromarray(np.random.randint(0, 255, (224, 224, 3), dtype=np.uint8))
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def test_sentiment_analysis(self):
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"""Test sentiment analysis functionality"""
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# Test positive sentiment
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positive_result = self.analyzer.analyze_sentiment("I love this content! It's amazing!")
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self.assertIn(positive_result["label"], ["POSITIVE", "NEUTRAL"])
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self.assertGreater(positive_result["score"], 0)
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# Test negative sentiment
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negative_result = self.analyzer.analyze_sentiment("This is terrible and offensive content")
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self.assertIn(negative_result["label"], ["NEGATIVE", "NEUTRAL"])
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self.assertGreater(negative_result["score"], 0)
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def test_ocr_extraction(self):
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"""Test OCR text extraction"""
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result = self.analyzer.extract_text_from_image(self.test_image)
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self.assertIsInstance(result, str)
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def test_multimodal_classification(self):
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"""Test multimodal content classification"""
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result = self.analyzer.classify_multimodal_content(self.test_image, "test text")
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self.assertIn("is_hateful", result)
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self.assertIn("hate_probability", result)
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self.assertIn("confidence", result)
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self.assertIsInstance(result["is_hateful"], bool)
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self.assertGreaterEqual(result["hate_probability"], 0)
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self.assertLessEqual(result["hate_probability"], 1)
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def test_ensemble_prediction(self):
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"""Test ensemble prediction functionality"""
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# Mock sentiment result
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sentiment_result = {
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"label": "NEGATIVE",
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"score": 0.85,
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"probabilities": [0.85, 0.10, 0.05]
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}
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# Mock multimodal result
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multimodal_result = {
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"is_hateful": True,
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"hate_probability": 0.75,
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"safe_probability": 0.25,
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"confidence": 0.80,
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"detailed_scores": []
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}
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ensemble_result = self.analyzer.ensemble_prediction(
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sentiment_result, multimodal_result, "test text"
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)
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self.assertIn("risk_level", ensemble_result)
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self.assertIn("risk_score", ensemble_result)
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self.assertIn("confidence", ensemble_result)
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self.assertIn(ensemble_result["risk_level"], ["HIGH", "MEDIUM", "LOW", "SAFE"])
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if __name__ == "__main__":
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unittest.main()
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