зеркало из
https://github.com/ssciwr/AMMICO.git
synced 2025-10-29 21:16:06 +02:00
d4cda187e3
* convert into dict output * faces class * return cleaned dict * empty methods that are required * with dict updates * with dominant emotion confidence as tuple * multiple images * update notebook
41 строка
1.2 KiB
Python
41 строка
1.2 KiB
Python
from google.cloud import vision
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import io
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from misinformation import utils
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class TextDetector(utils.AnalysisMethod):
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def __init__(self, subdict: dict) -> None:
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super().__init__(subdict)
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self.subdict.update(self.set_keys())
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def set_keys(self) -> dict:
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params = {"text": None}
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return params
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def analyse_image(self):
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"""Detects text on the image."""
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path = self.subdict["filename"]
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client = vision.ImageAnnotatorClient()
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with io.open(path, "rb") as image_file:
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content = image_file.read()
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image = vision.Image(content=content)
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response = client.text_detection(image=image)
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texts = response.text_annotations
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# here check if text was found
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self.subdict = {"text": []}
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for text in texts:
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self.subdict["text"].append(text.description)
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if response.error.message:
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raise Exception(
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"{}\nFor more info on error messages, check: "
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"https://cloud.google.com/apis/design/errors".format(
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response.error.message
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)
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)
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return self.subdict
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