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25ed5881a1
* start with translate * translate and clean - notebook * spacy model in requirements * translate in module * clean in module * upload coverage only for ubuntu * update ubuntu version on runner * update dependencies * start tests for text * skip gcv test * fix age * more text tests * more text tests * add comment * test translation * fix numpy version; add reference data for trans * use utf-8 for windows
78 строки
2.4 KiB
Python
78 строки
2.4 KiB
Python
import os
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import pytest
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import spacy
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import misinformation.text as tt
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TESTDICT = {
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"IMG_3755": {
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"filename": "./test/data/IMG_3755.jpg",
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},
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"IMG_3756": {
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"filename": "./test/data/IMG_3756.jpg",
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},
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"IMG_3757": {
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"filename": "./test/data/IMG_3757.jpg",
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},
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}
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LANGUAGES = ["de", "om", "en"]
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os.environ[
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"GOOGLE_APPLICATION_CREDENTIALS"
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] = "../data/seismic-bonfire-329406-412821a70264.json"
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def test_TextDetector():
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for item in TESTDICT:
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test_obj = tt.TextDetector(TESTDICT[item])
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assert test_obj.subdict["text"] is None
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assert test_obj.subdict["text_language"] is None
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assert test_obj.subdict["text_english"] is None
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assert test_obj.subdict["text_cleaned"] is None
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@pytest.mark.gcv
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def test_get_text_from_image():
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for item in TESTDICT:
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test_obj = tt.TextDetector(TESTDICT[item])
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test_obj.get_text_from_image()
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ref_file = "./test/data/text_" + item + ".txt"
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with open(ref_file, "r", encoding="utf8") as file:
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reference_text = file.read()
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assert test_obj.subdict["text"] == reference_text
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def test_translate_text():
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for item, lang in zip(TESTDICT, LANGUAGES):
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test_obj = tt.TextDetector(TESTDICT[item])
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ref_file = "./test/data/text_" + item + ".txt"
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trans_file = "./test/data/text_translated_" + item + ".txt"
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with open(ref_file, "r", encoding="utf8") as file:
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reference_text = file.read()
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with open(trans_file, "r", encoding="utf8") as file:
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translated_text = file.read()
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test_obj.subdict["text"] = reference_text
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test_obj.translate_text()
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assert test_obj.subdict["text_language"] == lang
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assert test_obj.subdict["text_english"] == translated_text
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def test_init_spacy():
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test_obj = tt.TextDetector(TESTDICT["IMG_3755"])
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ref_file = "./test/data/text_IMG_3755.txt"
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with open(ref_file, "r") as file:
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reference_text = file.read()
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test_obj.subdict["text_english"] = reference_text
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test_obj._init_spacy()
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assert isinstance(test_obj.doc, spacy.tokens.doc.Doc)
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def test_clean_text():
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nlp = spacy.load("en_core_web_md")
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doc = nlp("I like cats and fjejg")
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test_obj = tt.TextDetector(TESTDICT["IMG_3755"])
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test_obj.doc = doc
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test_obj.clean_text()
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result = "I like cats and"
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assert test_obj.subdict["text_clean"] == result
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