Added working example to readme.

master
Rostislav Lán 2 years ago
parent 7e45cf4a5b
commit d68471e1a9

@ -15,50 +15,88 @@ Before cloning repository, you need these to succesfully use the application.
* python version 3.10 is a requirement might work on earlier python 3 versions
```sh
apt install python3.10
sudo apt install python3.10
```
* python graphical modules
* virtualenv for virtual enviroment creation
```sh
pip install numpy==1.23.3 matplotlib==3.5.3 opencv-python=4.7.0.72
stl==0.0.3 scikit-image==0.19.3
pip install virtualenv
```
# Installation
Installation is relatively fast and easy.
1. Go to a suitable installation folder, for example Documents.
```sh
cd /home/username/Documents
```
1. Clone the repository
2. Clone the repository to a suitable directory, for example
```sh
git clone ssh://git@strade.fit.vutbr.cz:3022/xlanro00/BP_DP-xlanro00.git
```
2. Prepare an image file containing fingerprint
3. Go inside cloned directory
```sh
cd BP_DP-xlanro00
```
v
4. Create and enter the virtual enviroment.
```sh
virtualenv .venv && source .venv/bin/activate
```
3. Run the application
5. Install required python modules from requirements.txt.
```sh
pip install -r requirements.txt
```
6. Run the application, as an example there is a file in res/examples called Palec_P4.tif. This is shown in the section below.
# Filtering images
Once all the requirements are installed, the program is ready to use. There are two ways to enter filters:
Once all the requirements are installed, the program is ready to use. There are two ways to enter the filters:
* manually from command line, list filter names and parameters
1. manually list filter names and parameters from command line
```sh
python src/main.py res/test_fp.png res/test_fp_cpy.png 100 denoise_tv_chambolle iterations=1 weight=0.1 median ksize=3
python3 src/main.py res/examples/Palec_P4.tif res/examples/Palec_P4.png 600 denoise_tv_chambolle iterations=1 weight=0.2 median ksize=5
```
* manually from preset saved in a json config file, that can be used to create new presets
2. from preset saved in a json config file, that can be used to tune and modify existing presetrs, or create new ones
```sh
python src/main.py res/test_fp.png res/test_fp_cpy.png 100 --config config/config.json weak
python3 src/main.py res/examples/Palec_P4.tif res/examples/Palec_P4_from_preset.png 600 --config config/config.json git_example
```
# Configuration
# Configuration and presets
There is an option to input the filter series as a preset to json configuration file.
There is an option to input the filter series as a preset from json configuration file.
```diff
{
"weak": [
"preset": [
{
"name": "filter_name",
"parameter": value,
"parameter": value
},
{
"name": "filter_name",
"parameter": value
}
],
"preset": [
...
]
...
}
```
For example
```diff
{
"git_example": [
{
"name": "denoise_tv_chambolle",
"weight": 0.01,
@ -67,16 +105,59 @@ There is an option to input the filter series as a preset to json configuration
{
"name": "median",
"ksize": 3
},
],
"strong": [
...
}
]
...
}
```
All the filters used and their parameters will be described in documentation.
All the filters used and their parameters are described below.
## Available filters with parameters
-median blur
-ksize - kernel size (int)
-gaussian blur
-ksize - Gaussian kernel size (int)
-sigmaX - Kernel deviation in X direction (float)
-sigmaY - Kernel deviation in Y direction (float)
-bilateral blur
-d - ? (int)
-sigmaColor - ? (int)
-sigmaSpace - ? (int)
-denoise
-h - ? (int)
-tWS - template window size (int)
-sWs - search window size (int)
-denoise_bilateral
-sigmaColor - ? (int)
-sigmaSpace - ? (int)
-iterations - ? (int)
-denoise_tv_chambolle
-weight - ? (float)
-iterations - ? (int)
-sharpen
-kernel - ? (numpy.matrix)
-unsharp mask
-strength - ? (float)
-ksize - kernel size (int)
-unsharp mask scikit
-radius - ? (int)
-amount - ? (float)
-morph
-kernel - ? (numpy.matrix)
-iterations - ? (int)
-op - opencv MORPH operation (MORPH_OPEN, MORPH_CLOSE,
MORPH_DILATE, MORPH_ERODE)
-anchor - ? (tuple)
# Comparison
@ -99,25 +180,59 @@ It is possible to generate 3D printable stl model using `--stl` switch, which re
In base mode the output model will be a curved finger model, with optional parameters following the filename controlling its shape.
First optional parameter is papilar line height, second rate of curvature along x axis and the third is the rate of curvature along y axis.
* Example planar stl generation
* General form for curved stl generation
```sh
python3 src/main.py input_file output_file dpi --config config_file preset --stl height_line height_base curvature_x curvature_y
```
* Working example curved stl generation
```sh
python src/main.py res/test_fp.png res/test_fp_mod.png 508 --config config/config.json weak --stl res/test_fp.stl 2 2 4
python3 src/main.py res/examples/Palec_P4.tif res/examples/Palec_P4_from_preset.png 600 --config config/config.json git_example --stl 2 10 2 2
```
# Generating planar finger model
Using `-p` switch makes the generated model planar. This is not the main goal of the application.
Using `-p` switch makes the generated model planar.
Optional parameters are model base thickness and papilar lines height, they are set after stl file name.
* Example curved stl generation
* General form for planar stl generation
```sh
python3 src/main.py input_file output_file dpi --config config_file preset --stl height_line height_base -p
```
* Working example planar stl generation
```sh
python src/main.py res/test_fp.png res/test_fp_mod.png 508 --config config/config.json weak --stl res/test_fp.stl 10 2 -p
python3 src/main.py res/examples/Palec_P4.tif res/examples/Palec_P4_from_preset.png 600 --config config/config.json git_example --stl 2 10 -p
```
# Mapping to existing finger model
This section will be added later, (if implemented) mapping of fingerprint to a given finger model.
# Usage
usage: main.py [-h] [-m | --mirror | --no-mirror] [-p] input_file output_file dpi ([-c | --config config_file preset] | [filters ...]) [-s | --stl height_line height_base | --stl_file height_line curv_rate_x curv_rate_y]
Program for processing a 2D image into 3D fingerprint.
positional arguments:
input_file input file path
output_file output file path
dpi dpi of used scanner
filters list of filter names and their parameters in form [filter_name1 param1=value
param2=value filter_name2 param1=value...]
options:
-h, --help show this help message and exit
-m, --mirror, --no-mirror
switch to mirror input image
-s [STL_FILE ...], --stl_file [STL_FILE ...]
create stl model from processed image
-p, --planar, --no-planar
make stl shape planar instead of curved one
-c CONFIG CONFIG, --config CONFIG CONFIG
pair: name of the config file with presets, name of the preset
# Roadmap
- [x] Load and store image
@ -130,7 +245,7 @@ This section will be added later, (if implemented) mapping of fingerprint to a g
- [X] Add the option to modify filter parameters
- [X] Convert the processed image to stl lithophane
- [X] Add the option to curve the lithophane into the shape of a finger
- [ ] Add the option to map the lithophane on a given finger model
- [ ] Add the option to map the fingerprint onto a given finger model
- [X] Export final model ready for 3D print
#

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