class_docstr: 🤗 Constructor for the object detection trainer
code: def __init__(self, feature_extractor, model):
      self.device = torch.device(
          "cuda" if torch.cuda.is_available() else "cpu"
      )
  
      self.feature_extractor = feature_extractor
      self.model = model
      print("Model loaded!")
  
      # Colors for visualization
      self.COLORS = [
          [0.000, 0.447, 0.741],
          [0.850, 0.325, 0.098],
          [0.929, 0.694, 0.125],
          [0.494, 0.184, 0.556],
          [0.466, 0.674, 0.188],
          [0.301, 0.745, 0.933],
      ]
  
file_path: HugsVision/build/lib/hugsvision/inference/ObjectDetectionInference.py
imports: import os
  from datetime import datetime
  import torch
  from transformers import DetrFeatureExtractor, DetrForObjectDetection, pipeline
  from PIL import Image
  import matplotlib
  import matplotlib.pyplot
label_desc: Use image node_id 1 to create a new ObjectDetectionInference object  with example: obj = ObjectDetectionInference(feature_extractor, model)