class_docstr: 🤗 Constructor for the object detection trainer
code: def predict_img(self, img, threshold=0.2, visualize=False):
      # # Change resolution to 128x128
      # img.thumbnail((self.resolution,self.resolution))
  
      # Transform the image
      encoding = self.feature_extractor(images=img, return_tensors="pt")
  
      # Predict and get the corresponding bounding boxes
      outputs = self.model(
          pixel_values=encoding["pixel_values"],
          pixel_mask=None,
      )
  
      return self.visualize_predictions(
          img, outputs, threshold, visualize=visualize
      )
  
file_path: HugsVision/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 6 for calling the ObjectDetectionInference obj's underlying member method code with example usage: obj.predict_img(img, threshold, visualize) and returns: self