colors, argparse
This commit is contained in:
@@ -1,101 +1,94 @@
|
||||
# Documentation for `example/example_code.py`
|
||||
|
||||
## `remove_dirt(image)`
|
||||
This function removes small elements from an image using area closing morphological operation.
|
||||
### `remove_dirt(image)`
|
||||
The `remove_dirt` function removes small objects from the input image using area closing. Here is an example of how to use the `remove_dirt` function:
|
||||
|
||||
Example:
|
||||
```python
|
||||
import skimage.morphology as morphology
|
||||
|
||||
```
|
||||
# Import the required module
|
||||
from skimage import morphology
|
||||
# Load an image using some library (e.g. Pillow, OpenCV, etc.)
|
||||
image = ...
|
||||
|
||||
# Load the image
|
||||
image = skimage.io.imread('image.jpg')
|
||||
|
||||
# Apply the function to remove small elements from the image
|
||||
# Remove small objects from the image
|
||||
image = remove_dirt(image)
|
||||
|
||||
# Show the result
|
||||
skimage.io.imshow(image)
|
||||
```
|
||||
|
||||
## `calculate_area(countour)`
|
||||
This function calculates the area of a contour in an image.
|
||||
|
||||
Example:
|
||||
### `calculate_area(countour)`
|
||||
The `calculate_area` function calculates the area of a contour in an image using OpenCV. Here is an example of how to use the `calculate_area` function:
|
||||
|
||||
```
|
||||
# Import the required modules
|
||||
import cv2 as cv
|
||||
```python
|
||||
import numpy as np
|
||||
import cv2 as cv
|
||||
|
||||
# Load the image and find the contours
|
||||
image = cv.imread('image.jpg')
|
||||
contours, _ = cv.findContours(image, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)
|
||||
# Load an image using some library (e.g. Pillow, OpenCV, etc.)
|
||||
image = ...
|
||||
|
||||
# Iterate over the contours and calculate their areas
|
||||
# Find contours in the image using OpenCV
|
||||
contours = cv.findContours(image, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_NONE)
|
||||
|
||||
# Calculate the area of each contour
|
||||
for contour in contours:
|
||||
area = calculate_area(contour)
|
||||
print('Area of contour:', area)
|
||||
print(area)
|
||||
```
|
||||
|
||||
## `center_of_mass(X)`
|
||||
This function calculates the center of mass of a set of points.
|
||||
|
||||
Example:
|
||||
### `center_of_mass(X)`
|
||||
The `center_of_mass` function calculates the center of mass of a 2D shape defined by a set of points. Here is an example of how to use the `center_of_mass` function:
|
||||
|
||||
```
|
||||
```python
|
||||
import numpy as np
|
||||
|
||||
# Define a set of points
|
||||
X = np.array([[1,2], [3,4], [5,6]])
|
||||
# Define a set of points that define a shape
|
||||
X = np.array([[0,0], [0,1], [1,1], [1,0]])
|
||||
|
||||
# Calculate the center of mass of the points
|
||||
center = center_of_mass(X)
|
||||
# Calculate the center of mass of the shape
|
||||
com = center_of_mass(X)
|
||||
|
||||
# Print the result
|
||||
print('Center of mass:', center)
|
||||
# Print the center of mass
|
||||
print(com)
|
||||
```
|
||||
|
||||
The output will be `Center of mass: [3. 4.]`.
|
||||
In this example, the output would be `[0.5, 0.5]`, which is the center of the square defined by the points `X`.
|
||||
|
||||
## `center_of_mass(X)`
|
||||
This function calculates the center of mass of a set of points.
|
||||
|
||||
Example:
|
||||
### `center_of_mass(X)`
|
||||
The `center_of_mass` function calculates the center of mass of a 2D shape defined by a set of points. Here is an example of how to use the `center_of_mass` function:
|
||||
|
||||
```
|
||||
```python
|
||||
import numpy as np
|
||||
|
||||
# Define a set of points
|
||||
X = np.array([[1,2], [3,4], [5,6]])
|
||||
# Define a set of points that define a shape
|
||||
X = np.array([[0,0], [0,1], [1,1], [1,0]])
|
||||
|
||||
# Calculate the center of mass of the points
|
||||
center = center_of_mass(X)
|
||||
# Calculate the center of mass of the shape
|
||||
com = center_of_mass(X)
|
||||
|
||||
# Print the result
|
||||
print('Center of mass:', center)
|
||||
# Print the center of mass
|
||||
print(com)
|
||||
```
|
||||
|
||||
The output will be `Center of mass: [3. 4.]`.
|
||||
In this example, the output would be `[0.5, 0.5]`, which is the center of the square defined by the points `X`.
|
||||
|
||||
## `rg_ratio_normalize(imgarr)`
|
||||
This function normalizes the temperature values in an image array using the RG ratio and a pyrometry calibration formula.
|
||||
|
||||
Example:
|
||||
### `rg_ratio_normalize(imgarr)`
|
||||
The `rg_ratio_normalize` function applies a normalization function to the red and green channels of a 2D image, then applies a camera calibration formula to the resulting normalized values and returns the resulting image. Here is an example of how to use the `rg_ratio_normalize` function:
|
||||
|
||||
```
|
||||
# Import the required modules
|
||||
```python
|
||||
import numpy as np
|
||||
|
||||
# Load the image array
|
||||
imgarr = np.array(...)
|
||||
# Load an image using some library (e.g. Pillow, OpenCV, etc.)
|
||||
image = ...
|
||||
|
||||
# Normalize the temperature values in the image
|
||||
# Convert the image to a NumPy array
|
||||
imgarr = np.array(image)
|
||||
|
||||
# Apply the normalization and calibration to the image
|
||||
imgnew, tmin, tmax = rg_ratio_normalize(imgarr)
|
||||
|
||||
# Print the resulting minimum and maximum temperature values
|
||||
print('Minimum temperature:', tmin)
|
||||
print('Maximum temperature:', tmax)
|
||||
# Print the minimum and maximum temperature values in the image
|
||||
print(tmin, tmax)
|
||||
```
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user