88 lines
2.7 KiB
Python
Executable File
88 lines
2.7 KiB
Python
Executable File
"""Definition of VisualCommunication model."""
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from __future__ import annotations
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import logging
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from base64 import b64decode
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from base64 import b64encode
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from io import BytesIO
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from pathlib import Path
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from minio import Minio
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from PIL import Image
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from pydantic import BaseModel
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from shared.data_store import get
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from shared.data_store import put
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from shared.dto import ModelData
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class VisualCommunication(BaseModel):
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"""Visual communication model."""
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name: str
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object_name: str
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annotation: ModelData | None = None
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prediction: ModelData | None = None
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class Config:
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"""BaseModel configuration."""
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arbitrary_types_allowed = True
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@classmethod
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def classname(cls) -> str:
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"""Return classname."""
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return cls.__name__
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@classmethod
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def from_file(cls, path: Path, minio_client: Minio) -> VisualCommunication:
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"""Instantiate from file."""
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assert isinstance(path, Path)
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assert isinstance(minio_client, Minio)
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# determine name
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name = path.stem
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# open and upload image to minio
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image = Image.open(path)
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image.load()
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buffer = BytesIO()
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image.save(buffer, 'png')
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object_name = put(
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client=minio_client,
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buffer=buffer,
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)
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return VisualCommunication(name=name, object_name=object_name)
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@classmethod
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def decode_image(cls, content: str) -> Image.Image:
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"""Extract image from webencoded content."""
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_, content_data = content.split(',')
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return Image.open(BytesIO(b64decode(content_data)))
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def get_image(self, minio_client: Minio) -> Image.Image:
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"""Load image data from minio."""
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assert isinstance(minio_client, Minio)
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# get buffer from minio
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buffer = get(
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client=minio_client,
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object_name=self.object_name,
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)
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# convert data to image
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im = Image.open(buffer)
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return im
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def webencoded_image(self, minio_client: Minio) -> str:
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"""Convert image to be displayed on webpage."""
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assert isinstance(minio_client, Minio)
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# get image from minio
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image = self.get_image(minio_client)
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# convert images to bytes string
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buffer = BytesIO()
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image.save(buffer, format='png')
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img_enc = b64encode(buffer.getvalue()).decode('utf-8')
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return f"data:image/png;base64, {img_enc}"
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def generate_random_prediction(self, force: bool = False) -> None:
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"""Generate random prediction values."""
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if not force and self.prediction is not None:
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logging.warning('set force=True to overwrite existing values.')
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self.prediction = ModelData.from_random()
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