Params verbosity

docs/Points.md

@@ -3,7 +3,7 @@
 Using [Jupyter Notebooks](jupyter.md) it is possible to interactively click to collect coordinates from an image, which can be used in various downstream applications. Left click on the image to collect a point. Right click removes the
 closest collected point.
 
-**plantcv.Points**(*img, figsize=(12, 6)*)
+**plantcv.Point**(*img, figsize=(12, 6)*)
 
 **returns** interactive image class
 
@@ -25,8 +25,8 @@ closest collected point.
 ```python
 from plantcv import plantcv as pcv
 
-# Create an instance of the Points class
-marker = pcv.Points(img=img, figsize=(12,6))
+# Create an instance of the Point class
+marker = pcv.Point(img=img, figsize=(12,6))
 
 # Click on the plotted image to collect coordinates
 

docs/params.md

@@ -50,7 +50,7 @@ the morphology sub-package. Default = 2.
 
 **saved_color_scale**: Using the `color_palette` function will save the color scale here for reuse in downstream functions. Set to `None` to remove. Default = `None`.
 
-**verbose**: Set the status of verboseness. When in "verbose" mode, the deprecation warning will always be printed once triggered. Default: `True`. Users can turn off deprecation warnings by setting `verbose=False`.
+**verbose**: Set the status of verboseness as an integer between 0 and 2. When in the most verbose mode (2), the deprecation warning will always be printed once triggered. Default: `1`. Users can turn off messages by setting `verbose=0` or opt for more messages/debug images with `verbose=2`.
 
 **unit**: Set the units of the size outputs. Users can scale size measurements by updating the `unit`, `px_height` and `px_width` Default: `pixels`
 

docs/sharpen.md

@@ -0,0 +1,44 @@
+## Sharpen
+
+Sharpens an image through the unmask-sharpening method. Applies a gaussian blur which is subtracted from an exaggerated version of the starting image.
+
+**plantcv.sharpen**(*img, ksize, amount=1, threshold=0, sigma_x=0, sigma_y=None, roi=None*)
+
+**returns** sharpened image
+
+- **Parameters:**
+    - img - RGB or grayscale image data
+    - ksize - Tuple of kernel dimensions, e.g. (5, 5). Must be odd integers.
+	- amount - Integer describing amount of sharpening, higher numbers will sharpen more.
+	- threshold - Integer cutoff on low contrast, contrasts lower than this will be removed.
+    - sigma_x - standard deviation in X direction; if 0 (default), calculated from kernel size
+    - sigma_y - standard deviation in Y direction; if sigma_Y is None (default), sigma_Y is taken to equal sigma_X
+	- roi - Optional rectangular ROI as returned by [`pcv.roi.rectangle`](roi_rectangle.md) within which to apply this function. (default = None, which uses the entire image)
+- **Context:**
+    - Used to reduce blur in an image
+
+**Original image**
+
+![Screenshot](img/documentation_images/threshold_2channels/VIS_TV_z500_h2_g0_e100_163042_0_m.png)
+
+**Sharpening Image**
+
+```python
+
+# Apply sharpening within an ROI to show differences
+roi = pcv.roi.rectangle(img, 200, 0, 335, 200)
+sharp1 = pcv.sharpen(img, (5, 5), amount=1, roi=roi)
+
+# Higher amount of sharpening will look more dramatic
+sharp5 = pcv.sharpen(img, (5, 5), amount = 5, roi=roi)
+```
+
+**Sharpen (ksize = (5,5), amount=1, roi=roi)**
+
+![sharp1](img/documentation_images/sharpen/sharp1.png)
+
+**Sharpen (ksize = (5,5), amount=5, roi=roi)**
+
+![sharp5](img/documentation_images/sharpen/sharp5.png)
+
+**Source Code:** [Here](https://github.com/danforthcenter/plantcv/blob/main/plantcv/plantcv/sharpen.py)

docs/updating.md

@@ -1065,6 +1065,10 @@ pages for more details on the input and output variable types.
 * post v3.0dev2: sr_img = **plantcv.scharr_filter**(*gray_img, dx, dy, scale*)
 * post v4.9: sr_img = **plantcv.scharr_filter**(*gray_img, dx, dy, scale, roi=None*)
 
+#### plantcv.sharpen
+* pre v5.0: NA
+* post v5.0: **plantcv.sharpen**(*img, ksize, amount=1, threshold=0, sigma_x=0, sigma_y=None, roi=None*)
+
 #### plantcv.shift_img
 
 * pre v3.0dev2: device, adjusted_img = **plantcv.shift_img**(*img, device, number, side="right", debug=None*)

mkdocs.yml

@@ -160,6 +160,7 @@ nav:
         - 'Filter a mask by ROI (quickly)': roi_quick_filter.md
         - 'Convert ROI to Mask': roi2mask.md
       - 'Segment Image Series': segment_image_series.md
+      - 'Sharpen Image': sharpen.md
       - 'Shift Image': shift.md
       - 'Spatial Clustering': spatial_clustering.md
       - 'Spectral Index': spectral_index.md

plantcv/plantcv/__init__.py

@@ -8,13 +8,12 @@
 from plantcv.plantcv.classes import Outputs
 from plantcv.plantcv.classes import Spectral_data
 from plantcv.plantcv.classes import PSII_data
-from plantcv.plantcv.classes import Points
+from plantcv.plantcv.classes import Point
 from plantcv.plantcv.classes import Objects
 
 # Initialize an instance of the Params and Outputs class with default values
 # params and outputs are available when plantcv is imported
-params = Params()
-outputs = Outputs()
+from plantcv.plantcv._globals import params, outputs
 
 from plantcv.plantcv.deprecation_warning import deprecation_warning
 from plantcv.plantcv.warn import warn
@@ -63,6 +62,7 @@
 from plantcv.plantcv.canny_edge_detect import canny_edge_detect
 from plantcv.plantcv.opening import opening
 from plantcv.plantcv.closing import closing
+from plantcv.plantcv.sharpen import sharpen
 from plantcv.plantcv import roi
 from plantcv.plantcv import threshold
 from plantcv.plantcv import visualize
@@ -91,8 +91,10 @@
     "Outputs",
     "Spectral_data",
     'PSII_data',
-    'Points',
+    'Point',
     "Objects",
+    "params",
+    "outputs",
     "deprecation_warning",
     "warn",
     "print_image",
@@ -139,6 +141,7 @@
     "canny_edge_detect",
     "opening",
     "closing",
+    "sharpen",
     "roi",
     "threshold",
     "visualize",

plantcv/plantcv/_debug.py

@@ -1,28 +1,32 @@
 # Debugging module
-from plantcv.plantcv import params
+from plantcv.plantcv._globals import params
 from plantcv.plantcv import print_image
 from plantcv.plantcv import plot_image
 
 
-def _debug(visual, filename=None, **kwargs):
-    """
-    Save or display a visual for debugging.
+def _debug(visual, filename=None, verbosity_level=0, **kwargs):
+    """Save or display a visual for debugging.
 
-    Inputs:
-    visual   - An image or plot to display for debugging
-    filename - An optional filename to save the visual to (default: None)
-    kwargs - key-value arguments to xarray.plot method
+    Parameters
+    ----------
+    visual          = numpy.ndarray, An image or plot to display for debugging
+    filename        = str, An optional filename to save the visual to (default: None)
+    verbosity level = int, threshold for params.verbose to make debug image.
+                          Defaults to 0, which essentially ignores params.verbose
+    kwargs          = dict, key-value arguments to xarray.plot method
 
-    :param visual: numpy.ndarray
-    :param filename: str
-    :param kwargs: dict
+    Returns
+    -------
+    No returns
     """
-    # Auto-increment the device counter
-    params.device += 1
+    # if verbose from params is at least to the verbosity level, make debug images
+    if params.verbose >= verbosity_level:
+        # Auto-increment the device counter
+        params.device += 1
 
-    if params.debug == "print":
-        # If debug is print, save the image to a file
-        print_image(img=visual, filename=filename, **kwargs)
-    elif params.debug == "plot":
-        # If debug is plot, print to the plotting device
-        plot_image(img=visual, **kwargs)
+        if params.debug == "print":
+            # If debug is print, save the image to a file
+            print_image(img=visual, filename=filename, **kwargs)
+        elif params.debug == "plot":
+            # If debug is plot, print to the plotting device
+            plot_image(img=visual, **kwargs)

plantcv/plantcv/_globals.py

@@ -0,0 +1,7 @@
+# define singletons
+
+from plantcv.plantcv.classes import Params
+from plantcv.plantcv.classes import Outputs
+
+params = Params()
+outputs = Outputs()

plantcv/plantcv/_helpers.py

@@ -2,7 +2,7 @@
 import numpy as np
 from skimage import morphology
 from plantcv.plantcv import fatal_error, warn
-from plantcv.plantcv import params
+from plantcv.plantcv._globals import params
 import pandas as pd
 
 

plantcv/plantcv/analyze/bound_horizontal.py

@@ -4,8 +4,7 @@
 import numpy as np
 from plantcv.plantcv._debug import _debug
 from plantcv.plantcv._helpers import _iterate_analysis, _grayscale_to_rgb, _scale_size
-from plantcv.plantcv import params
-from plantcv.plantcv import outputs
+from plantcv.plantcv._globals import params, outputs
 
 
 def _get_boundary_values(bound_mask, total_area, axis=0):

plantcv/plantcv/analyze/bound_vertical.py

@@ -4,7 +4,7 @@
 from plantcv.plantcv._debug import _debug
 from plantcv.plantcv._helpers import _iterate_analysis, _grayscale_to_rgb, _scale_size
 from plantcv.plantcv.analyze.bound_horizontal import _get_boundary_values, _boundary_img_annotation
-from plantcv.plantcv import params
+from plantcv.plantcv._globals import params
 from plantcv.plantcv import outputs
 
 

plantcv/plantcv/analyze/color.py

@@ -4,7 +4,7 @@
 import numpy as np
 from scipy import stats
 from plantcv.plantcv import fatal_error
-from plantcv.plantcv import params
+from plantcv.plantcv._globals import params
 from plantcv.plantcv._debug import _debug
 from plantcv.plantcv import outputs
 from plantcv.plantcv.visualize import histogram

plantcv/plantcv/analyze/size.py

@@ -5,7 +5,7 @@
 from scipy.spatial.distance import euclidean
 from plantcv.plantcv._helpers import _iterate_analysis, _cv2_findcontours, _object_composition, _grayscale_to_rgb, _scale_size
 from plantcv.plantcv import outputs, within_frame
-from plantcv.plantcv import params
+from plantcv.plantcv._globals import params
 from plantcv.plantcv._debug import _debug
 
 

plantcv/plantcv/apply_mask.py

@@ -3,7 +3,7 @@
 import os
 import cv2
 import numpy as np
-from plantcv.plantcv import params
+from plantcv.plantcv._globals import params
 from plantcv.plantcv._debug import _debug
 from plantcv.plantcv import fatal_error
 from plantcv.plantcv.transform import rescale

plantcv/plantcv/background_subtraction.py

@@ -6,7 +6,7 @@
 import numpy as np
 from plantcv.plantcv._debug import _debug
 from plantcv.plantcv import fatal_error, warn
-from plantcv.plantcv import params
+from plantcv.plantcv._globals import params
 
 
 def background_subtraction(background_image, foreground_image):

plantcv/plantcv/canny_edge_detect.py

@@ -2,7 +2,7 @@
 
 from plantcv.plantcv._debug import _debug
 from plantcv.plantcv._helpers import _dilate
-from plantcv.plantcv import params
+from plantcv.plantcv._globals import params
 from plantcv.plantcv import fatal_error
 from skimage import feature
 import numpy as np

plantcv/plantcv/classes.py

@@ -4,8 +4,8 @@
 import json
 import numpy as np
 import datetime
-from plantcv.plantcv import __version__ as ver
-from plantcv.plantcv import fatal_error
+from importlib.metadata import version
+from plantcv.plantcv.fatal_error import fatal_error
 from plantcv.plantcv.annotate.points import _find_closest_pt
 import matplotlib.pyplot as plt
 from math import floor
@@ -19,46 +19,29 @@ class Params:
     def __init__(self, device=0, debug=None, debug_outdir=".", line_thickness=5,
                  line_color=(255, 0, 255), dpi=100, text_size=0.55,
                  text_thickness=2, marker_size=60, color_scale="gist_rainbow", color_sequence="sequential",
-                 sample_label="default", saved_color_scale=None, verbose=True, unit="pixels", px_height=1, px_width=1):
+                 sample_label="default", saved_color_scale=None, verbose=1, unit="pixels", px_height=1, px_width=1):
         """Initialize parameters.
 
-        Keyword arguments/parameters:
-        device            = Device number. Used to count steps in the pipeline. (default: 0)
-        debug             = None, print, or plot. Print = save to file, Plot = print to screen. (default: None)
-        debug_outdir      = Debug images output directory. (default: .)
-        line_thickness    = Width of line drawings. (default: 5)
-        line_color        = Color of line annotations (default = (255, 0, 255))
-        dpi               = Figure plotting resolution, dots per inch. (default: 100)
-        text_size         = Size of plotting text. (default: 0.55)
-        text_thickness    = Thickness of plotting text. (default: 2)
-        marker_size       = Size of plotting markers (default: 60)
-        color_scale       = Name of plotting color scale (matplotlib colormap). (default: gist_rainbow)
-        color_sequence    = Build color scales in "sequential" or "random" order. (default: sequential)
-        sample_label      = Sample name prefix. Used in analyze functions. (default: "default")
-        saved_color_scale = Saved color scale that will be applied next time color_palette is called. (default: None)
-        verbose           = Whether or not in verbose mode. (default: True)
-        unit              = Units of size trait outputs. (default: "pixels")
-        px_height         = Size scaling information about pixel height (default: 1)
-        px_width          = Size scaling information about pixel width (default: 1)
-
-
-        :param device: int
-        :param debug: str
-        :param debug_outdir: str
-        :param line_thickness: numeric
-        :param dpi: int
-        :param text_size: float
-        :param text_thickness: int
-        :param marker_size: int
-        :param color_scale: str
-        :param color_sequence: str
-        :param sample_label: str
-        :param saved_color_scale: list
-        :param verbose: bool
-        :param unit: str
-        :param px_height: float
-        :param px_width: float
-
+        Parameters
+        ----------
+        device            = int, Device number. Used to count steps in the pipeline. (default: 0)
+        debug             = str or None. Print = save to file, Plot = print to screen. (default: None)
+        debug_outdir      = str, Debug images output directory. (default: .)
+        line_thickness    = numeric, Width of line drawings. (default: 5)
+        line_color        = tuple, Color of line annotations (default = (255, 0, 255))
+        dpi               = numeric, Figure plotting resolution, dots per inch. (default: 100)
+        text_size         = float, Size of plotting text. (default: 0.55)
+        text_thickness    = int, Thickness of plotting text. (default: 2)
+        marker_size       = int, Size of plotting markers (default: 60)
+        color_scale       = str, Name of plotting color scale (matplotlib colormap). (default: gist_rainbow)
+        color_sequence    = str, Build color scales in "sequential" or "random" order. (default: sequential)
+        sample_label      = str, Sample name prefix. Used in analyze functions. (default: "default")
+        saved_color_scale = list or None, Saved color scale that will be applied next time color_palette is called.
+                            (default: None)
+        verbose           = Int, 0:2 representing verbosity level. 0 is least verbose, 2 is most verbose (default 1)
+        unit              = str, Units of size trait outputs. (default: "pixels")
+        px_height         = float, Size scaling information about pixel height (default: 1)
+        px_width          = float, Size scaling information about pixel width (default: 1)
         """
         self.device = device
         self.debug = debug
@@ -180,7 +163,7 @@ def save_results(self, filename, outformat="json"):
         # Add current date & time to metadata in UTC format
         run_datetime = datetime.datetime.now().strftime("%Y-%m-%dT%H:%M:%S.%fZ")
         self.add_metadata(term="run_date", datatype=str, value=run_datetime)
-        self.add_metadata(term="plantcv_version", datatype=str, value=ver)
+        self.add_metadata(term="plantcv_version", datatype=str, value=version("plantcv"))
 
         if outformat.upper() == "JSON":
             if os.path.isfile(filename):
@@ -377,7 +360,7 @@ def add_data(self, protocol):
         self.__dict__[protocol.name] = protocol
 
 
-class Points:
+class Point:
     """Point annotation/collection class to use in Jupyter notebooks. It allows the user to
     interactively click to collect coordinates from an image. Left click collects the point and
     right click removes the closest collected point

plantcv/plantcv/closing.py

@@ -1,5 +1,5 @@
 import os
-from plantcv.plantcv import params
+from plantcv.plantcv._globals import params
 from plantcv.plantcv._debug import _debug
 from plantcv.plantcv._helpers import _closing
 

plantcv/plantcv/color_palette.py

@@ -2,7 +2,7 @@
 
 from matplotlib import pyplot as plt
 import numpy as np
-from plantcv.plantcv import params
+from plantcv.plantcv._globals import params
 
 
 def color_palette(num, saved=False):

plantcv/plantcv/create_labels.py

@@ -4,7 +4,7 @@
 import numpy as np
 from skimage.measure import label
 from skimage.color import label2rgb
-from plantcv.plantcv import params
+from plantcv.plantcv._globals import params
 from plantcv.plantcv._debug import _debug
 from plantcv.plantcv._helpers import _roi_filter, _cv2_findcontours