title: Cant convert to different data types
body: <p>I am trying to run a .txt file with raw data into my code but I keep getting a value error. It was working before, but now I am getting this error:</p>
  <p>ValueError: could not convert string to float: '.'</p>
  <p>Here is my file with the raw data:</p>
  <pre><code>0.0980224609375
  0.10589599609375
  0.0980224609375
  0.0980224609375
  0.0980224609375
  0.11767578125
  0.130.0980224609375    --&gt; The error is here I assume since there are 2 periods
  0.10198974609375
  0.10198974609375
  0.0980224609375
  </code></pre>
  <p>This data can not be changed, so how can I convert this from a string to float without getting an error? Here is my code:</p>
  <pre><code># Read and pre-process input images
  n, c, h, w = net.inputs[input_blob].shape
  images = np.ndarray(shape=(n, c, h, w))
  for i in range(n):
      image = cv2.imread(args.input[i])
      if image.shape[:-1] != (h, w):
          log.warning(&quot;Image {} is resized from {} to {}&quot;.format(args.input[i], image.shape[:-1], (h, w)))
          image = cv2.resize(image, (w, h))
      # Swapping Red and Blue channels 
      #image[:, :, [0, 2]] = image[:, :, [2, 0]]
      # Change data layout from HWC to CHW
      image = image.transpose((2, 0, 1))  
      images[i] = image
      
      eoim = image
      eoim16 = eoim.astype(np.float16)
      
      # divide by 255 to get value in range 0-&gt;1 if necessary (depends on input pixel format)
      if(eoim16.max()&gt;1.0):
          eoim16 = np.divide(eoim16,255)
          print(eoim16)
  
  val = []
  preprocessed_image_path = 'C:/Users/Owner/Desktop/Ubotica/IOD/cloud_detect/'
  formated_image_file = &quot;output_patch_fp&quot;
  f = open(preprocessed_image_path + &quot;/&quot; + formated_image_file + &quot;.txt&quot;, 'r')
  '''elem_counter = 0
  for elem in eoim16:
      for elem1 in elem:
          for col in elem1:
              #f.read(int(float(formated_image_file)))
              val = float(f.readline())'''
  for y in f.readlines()[0]:
      val.append(float(y))
  f.close()
  
  #print(val)
  #val = np.reshape(val, (3,512,512))
  val = np.ndarray(shape=(c, h, w))
  #res = val
  
  # calling the instance method using the object cloudDetector
  res = cloudDetector.infer(val)
  res = res[out_blob]
  </code></pre>
  <p>Any help will be much appreciated!</p>