code: def conv_layer(self, idx, inputs, filters, size, stride):
      channels = inputs.get_shape()[3]
      weight = tf.Variable(
          tf.truncated_normal(
              [size, size, int(channels), filters], stddev=0.1
          )
      )
      biases = tf.Variable(tf.constant(0.1, shape=[filters]))
  
      pad_size = size // 2
      pad_mat = np.array(
          [[0, 0], [pad_size, pad_size], [pad_size, pad_size], [0, 0]]
      )
      inputs_pad = tf.pad(inputs, pad_mat)
  
      conv = tf.nn.conv2d(
          inputs_pad,
          weight,
          strides=[1, stride, stride, 1],
          padding="VALID",
          name=str(idx) + "_conv",
      )
      conv_biased = tf.add(conv, biases, name=str(idx) + "_conv_biased")
      if self.disp_console:
          print(
              "    Layer  %d : Type = Conv, Size = %d * %d, Stride = %d, Filters = %d, Input channels = %d"
              % (idx, size, size, stride, filters, int(channels))
          )
  
      return tf.maximum(
          self.alpha * conv_biased,
          conv_biased,
          name=str(idx) + "_leaky_relu",
      )
  
file_path: AdvBox/applications/StealthTshirt/StealthTshirtDemo.py
imports: import numpy
  import tensorflow
  import cv2
  import time
  import sys
  import os
  import pdb
label_desc: Use image node_id 4 for calling the Faster_YOLO obj's underlying member method code with example usage: obj.conv_layer(idx, inputs, filters, size, stride) and returns: tf