vk4_driver is a tool used to extract data from Keyence profilometry vk4 format data files and provide useful output formats for analysis (csv, tiff, jpeg, png).
The vk4_driver is meant to be used as command line script by running the vk4_driver.py file with approprate arguments. However, it can also be used as a module providing a flexible set of tools to process data from vk4 files.
In order to execute the vk4_driver the NumPy and PIL packages need to be installed
First, install numpy:
$ pip install numpyNext, install PIL:
$ pip install PILTo install, download the 4 source files:
VkContainer.pyvk4extract.pyvk4out.pyvk4_driver.py
First, the module vk4_driver can be used as a script with the following args:
$ python3 vk4_driver.py -i<vk4 filename> -t<type of output> -l<layers of data>
-o<optional output filename> -v<optional verbose logging>The input filename must be a valid vk4 file, including the extension .vk4
Options for the output file type argument:
csv(comma separated values)hcsv(comma separated values with metadata header)jpeg(image)png(image)tiff(image) NOTE: Only tiff type output creates valid image files for light and height data.
Options for data layers:
RGB(color peak data)LRGB(color + light data) NOTE: Any combination of L, R, G, B can be used for output (R, RB, LG, LRGB, etc.)H(height data)L(light data) NOTE: L alone refers strictly to light data, L in combination with RGB is color + light data
For the argument
To extract RGB data from the file 'example.vk4' and output that data to the file 'example_output' (filename extensions are supplied by the script) in jpeg image format:
$ python3 vk4_driver -iexample.vk4 -tjpeg -lRGB -oexample_output To extract height data from 'example.vk4' and output that data to a csv formatted output file with the default filename:
$ python3 vk4_driver -iexample.vk4 -tcsv -lH Currently vk4extract.py can be used as a module to extract particular data from a vk4 file for the user to manipualte or analyze as they see fit. In order to extract any data from the vk4 file, you must first call the extract_offsets() function which returns a dictionary in which the values are the byte offsets to the data corresponding to their keys.
Particular keys for dictionaries created from vk4extract functions can be found in the project documentation file vk4layout.pdf
| Primary Offset Key | Data Layer |
|---|---|
| 'meas_conds' | Measurement conditions and metadata |
| 'color_peak' | RGB color data |
| 'color_light' | RGB + light color data |
| 'light' | Light intensity data |
| 'height' | Height data |
| 'string_data' | Metadata refering to file title and microscope lens |
| Secondary Offset Key | Data Layer |
|---|---|
| 'clr_peak_thumb' | RGB thumbnail data |
| 'clr_thumb' | RGB + light thumbnail data |
| 'light_thumb' | Light thumbnail data |
| 'height_thumb' | Height thumbnail data |
| 'assembly_info' | Microscope Assembly metadata |
| 'line_measure' | --- |
| 'line_thickness' | --- |
| 'reserved' | --- |
NOTE: the values for the last three keys have been zero in all vk4 files I have worked with, indicating there is no data stored for that information, and I am unsure as to what data they might refer to in the case that the offset table in the vk4 file had non-zero values for those offsets
Once you have the offsets for the vk4 files it is just a matter of reading the binary data at those offsets, and the vk4extract module provides functions to extract layers of data from the primary offsets and convert them from binary, namely:
| Function name | Parameters |
|---|---|
extract_measurement_conditions |
offset dict, open vk4 file object |
extract_color_data |
offset dict, color type, open vk4 file object |
extract_img_data |
offset dict, data type, open vk4 file object |
extract_string_data |
offset dict, open vk4 file object |
NOTE: Color type refers to the strings 'peak' (for RGB data) and 'light' (for RGB + light data). Data type refers to the strings 'height' (for height data) and 'light' (for light intensity data)
Each of these functions returns a dictionary containing the data pertaining to a specific layer of data (RGB, RGB + light, Height, etc.) within the vk4 file.
Measurement Conditions Each key in this dict refers to an associated piece of metadata for the microscope or for the file itself. For a list of key names refer to the 'VK4layout.ods' file.
Color Data Each key in this dict typically refers to an associated piece of metadata concerning the data layer in question, except the key 'data' whose value is a Numpy array the same length as the image size (length * width) where each index is a list of three 1 byte integers representing the RGB color channels at each pixel of the image.
Image Data Each key in this dict typically refers to an associated piece of metadata concerning the data layer in question, except the key 'palette' whose value is a Numpy array of length 768 (= 256 * 3) containing 8 bit integers, and 'data' whose value is a Numpy array the same length as the image size where each index is the unscaled light or height data for each pixel of the image
String Data Each key in this dict typically refers to either the title of the image, or the name of the microscope lens
NOTE: each of the above dictionaries will also have a 'name' key whose value is determined by the data layer in question, e.g. when calling extract_img_data(offset_dict, 'height', vk4_in_file) the key 'name' will have the value 'Height'
Create a png image file from RGB data:
import numpy as np
from PIL import Image
import vk4extract
with open('example.vk4', 'rb') as in_file:
offsets = vk4extract.extract_offsets(in_file)
rgb_dict = vk4extract.extract_color_data(offsets, 'peak', in_file)
rgb_data = rgb_dict['data']
height = rgb_dict['height']
width = rgb_dict['width']
rgb_matrix = np.reshape(rgb_data, (height, width, 3))
image = Image.fromarray(rgb_matrix, 'RGB')
image.save('example_image.png', 'PNG')Create a csv text file from Light data:
import csv
import numpy as np
import vk4extract
with open('example.vk4', 'rb') as in_file:
offsets = vk4extract.extract_offsets(in_file)
light_dict = vk4extract.extract_img_data(offsets, 'light', in_file)
light_data = light_dict['data']
height = light_dict['height']
width = light_dict['width']
light_matrix = np.reshape(light_data, (height, width))
with open('example_light.csv', 'w', newline='') as out_file:
writer = csv.writer(out_file, delimiter=',')
for row in light_matrix:
writer.writerow(row)