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from models.schemas import MeasurementResult
import time
from draft_computation import run
class MeasurementService:
"""
A service to handle the draft measurement logic.
This is a placeholder that simulates a PyTorch model's output.
"""
def measure(self, image_bytes: bytes) -> MeasurementResult:
"""
Simulates running a deep learning model on the image.
Args:
image_bytes: The raw bytes of the image file.
Returns:
A MeasurementResult object with simulated data.
"""
# Simulate model processing time
time.sleep(2) # Simulate a 2-second processing time
results = run(image_bytes)
print(results)
return MeasurementResult(
draft_measurement=7.85, # Example measurement in meters
confidence_score=0.958
), results
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