Merge pull request #1339 from danforthcenter/acute-update-docs

update docs

docs/homology_acute.md

@@ -17,6 +17,9 @@ useful in parsing homolog_pts in downstream analyses
 
 chain       = raw angle scores for entire contour, used to visualize landmark clusters
 
+verbose     = supplemental file which stores coordinates, distance from
+landmark cluster edges, and angle score for entire contour.  Used in troubleshooting.
+
 - **Parameters:**
     - img - The original image, used for plotting purposes
     - mask - Binary mask used to generate contour array (necessary for ptvals)

docs/tutorials.md

@@ -203,7 +203,7 @@
 <!--Color correction Tutorial-->
 <div class="card" style="display:block">
     <a target="_blank" href="" onclick="location.href=this.href.replace('tutorials', 'tutorials/transform_color_correction_tutorial');return false;">
-        <img src="https://github.com/danforthcenter/plantcv-binder/blob/master/notebooks/color_correction_tutorial/color_correction_tutorial_card.png?raw=true" alt="Color correction tutorial" width="600" height="auto">
+        <img src="https://github.com/danforthcenter/plantcv-tutorial-color-correction/blob/main/tutorial_card.png?raw=true" alt="Color correction tutorial" width="600" height="auto">
     </a>
     <div class="card-title">
         <h6>Color Correction Tutorial</h6>
@@ -226,36 +226,23 @@
     </div>
 </div>
 
-<!--Threshold tools Tutorial-->
+<!--Segmentation Tutorials-->
 <div class="card" style="display:block">
     <a target="_blank" href="" onclick="location.href=this.href.replace('tutorials', 'tutorials/threshold_tutorial');return false;">
-        <img src="https://github.com/danforthcenter/plantcv-binder/blob/master/notebooks/threshold_tutorial/threshold_tutorial_card.png?raw=true" alt="Thresholding tutorial" width="600" height="auto">
+        <img src="https://github.com/danforthcenter/plantcv-tutorial-threshold/blob/main/tutorial_card.png?raw=true" alt="Segmentation tutorials" width="600" height="auto">
     </a>
     <div class="card-title">
         <h6>Thresholding Tutorial</h6>
     </div>
     <div class="card-tags">
-        <span><strong>Tags</strong>: plant shoot, single plant, side-view, RGB, threshold methods</span>
-    </div>
-</div>
-
-<!--Updated Threshold Tools Tutorial-->
-<div class="card" style="display:block">
-    <a target="_blank" href="" onclick="location.href=this.href.replace('tutorials', 'tutorials/threshold_tools_tutorial');return false;">
-        <img src="https://github.com/danforthcenter/plantcv-binder/blob/master/notebooks/new_mask_tutorial/mask_tutorial_card.jpg?raw=true" alt="Thresholding tools tutorial" width="600" height="auto">
-    </a>
-    <div class="card-title">
-        <h6>Tools for Thresholding Plant Data</h6>
-    </div>
-    <div class="card-tags">
-        <span><strong>Tags</strong>: plant shoot, single plant, side-view, RGB, threshold methods, binary mask</span>
+        <span><strong>Tags</strong>: plant shoot, single plant, side-view, RGB, threshold methods, seed, background subtraction, naive bayes, machine learning, segmentation</span>
     </div>
 </div>
 
 <!--ROI Tutorial-->
 <div class="card" style="display:block">
     <a target="_blank" href="" onclick="location.href=this.href.replace('tutorials', 'tutorials/roi_tutorial');return false;">
-        <img src="https://github.com/danforthcenter/plantcv-binder/blob/master/notebooks/roi_tutorial/roi_tutorial_card.png?raw=true" alt="ROI tutorial" width="600" height="auto">
+        <img src="https://github.com/danforthcenter/plantcv-tutorial-roi/blob/main/tutorial_card.png?raw=true" alt="ROI tutorial" width="600" height="auto">
     </a>
     <div class="card-title">
         <h6>Region of Interest Tutorial</h6>

docs/tutorials/homology_tutorial.md

@@ -1,5 +1,5 @@
 ## Tutorial: De novo homology assessment from landmark data
 
-[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/danforthcenter/plantcv-homology-tutorials/HEAD?filepath=index.ipynb) Check out the interactive tutorial! 
+[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/danforthcenter/plantcv-homology-tutorials/HEAD?labpath=index.ipynb) Check out the interactive tutorial! 
 
 <iframe src="https://nbviewer.jupyter.org/github/danforthcenter/plantcv-homology-tutorials/blob/main/index.ipynb" width="100%" height="1500px"></iframe>

docs/tutorials/roi_tutorial.md

@@ -1,5 +1,19 @@
 ## Tutorial: Region of Interest Tutorial
 
-[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/danforthcenter/plantcv-binder.git/master?filepath=notebooks/roi_tutorial/roi_package.ipynb) Check out our interactive ROI tutorial! 
+[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/danforthcenter/plantcv-tutorial-roi/HEAD?labpath=table_of_contents.ipynb) Check out our interactive ROI tutorials! 
 
-<iframe src="https://nbviewer.jupyter.org/github/danforthcenter/plantcv-binder/blob/master/notebooks/roi_tutorial/roi_package.ipynb" width="100%" height="1500px"></iframe>
+## Table of Contents for ROI tutorials
+1. [Rectangle ROI](#rectangle)
+2. [Multi ROI](#rectangle)
+3. [Automatic Grid ROIs](#rectangle)
+4. [Circle ROI](#circle)
+5. [Custom Polygon ROI](#custom)
+
+### Rectangle/Mutli/Auto_Grid Region of Interest <a name="rectangle"></a>
+<iframe src="https://nbviewer.jupyter.org/github/danforthcenter/plantcv-tutorial-roi/blob/main/notebooks/roi-rectangle-tutorial.ipynb" width="100%" height="1500px"></iframe>
+
+## Circle Region of Interest <a name="circle"></a>
+<iframe src="https://nbviewer.jupyter.org/github/danforthcenter/plantcv-tutorial-roi/blob/main/notebooks/roi-circle-tutorial.ipynb" width="100%" height="1500px"></iframe>
+
+## Custom Polygon Region of Interest <a name="custom"></a>
+<iframe src="https://nbviewer.jupyter.org/github/danforthcenter/plantcv-tutorial-roi/blob/main/notebooks/custom-roi-tutorial.ipynb" width="100%" height="1500px"></iframe>

docs/tutorials/sorghum_morphology_tutorial.md

@@ -1,6 +1,6 @@
 ## Tutorial: Sorghum Shape and Morphology Analysis
 
 
-[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/danforthcenter/plantcv-binder.git/master?filepath=notebooks/new_side_view_morphology_tutorial/morphology_analysis_side_view_workflow.ipynb) Check out our interactive sorghum shape and morphology tutorial! 
+[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/danforthcenter/plantcv-binder.git/master?labpath=notebooks/new_side_view_morphology_tutorial/morphology_analysis_side_view_workflow.ipynb) Check out our interactive sorghum shape and morphology tutorial! 
 
 <iframe src="https://nbviewer.jupyter.org/github/danforthcenter/plantcv-binder/blob/master/notebooks/new_side_view_morphology_tutorial/morphology_analysis_side_view_workflow.ipynb" width="100%" height="1500px"></iframe>

docs/tutorials/threshold_tutorial.md

@@ -1,5 +1,29 @@
-## Tutorial: Thresholding Tutorial
+## Tutorial: Segmentation Tutorial
 
-[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/danforthcenter/plantcv-binder.git/master?filepath=notebooks/threshold_tutorial/threshold.ipynb) Check out our interactive thresholding tutorial! 
+[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/danforthcenter/plantcv-tutorial-threshold/HEAD?labpath=index.ipynb) Check out our interactive thresholding tutorial! 
 
-<iframe src="https://nbviewer.jupyter.org/github/danforthcenter/plantcv-binder/blob/master/notebooks/threshold_tutorial/threshold.ipynb" width="100%" height="1500px"></iframe>
+## Table of Contents for segmentation tutorials
+1. [Thresholding](#thresholding)
+2. [Edge Detection](#edges)
+3. [Supervised Machine Learning](#naivebayes)
+4. [Unsupervied Machine Learning](#kmeans)
+5. [Background Subtraction](#background)
+6. [Dual Thresholding](#dual)
+
+### Thresholding <a name="thresholding"></a>
+<iframe src="https://nbviewer.jupyter.org/github/danforthcenter/plantcv-tutorial-threshold/blob/main/modules/01.thresholding.ipynb" width="100%" height="1500px"></iframe>
+
+### Edge Detection <a name="edges"></a>
+<iframe src="https://nbviewer.jupyter.org/github/danforthcenter/plantcv-tutorial-threshold/blob/main/modules/02.edge-detection.ipynb" width="100%" height="1500px"></iframe>
+
+### Supervised Machine Learning <a name="naivebayes"></a>
+<iframe src="https://nbviewer.jupyter.org/github/danforthcenter/plantcv-tutorial-threshold/blob/main/modules/03.supervised-machine-learning.ipynb" width="100%" height="1500px"></iframe>
+
+### Unsupervised Machine Learning <a name="kmeans"></a>
+<iframe src="https://nbviewer.jupyter.org/github/danforthcenter/plantcv-tutorial-threshold/blob/main/modules/04.unsupervised-machine-learning.ipynb" width="100%" height="1500px"></iframe>
+
+### Background Subtraction <a name="background"></a>
+<iframe src="https://nbviewer.jupyter.org/github/danforthcenter/plantcv-tutorial-threshold/blob/main/modules/05.background-subtraction.ipynb" width="100%" height="1500px"></iframe>
+
+### Dual Thresholding <a name="dual"></a>
+<iframe src="https://nbviewer.jupyter.org/github/danforthcenter/plantcv-tutorial-threshold/blob/main/modules/06.2d-thresholding.ipynb" width="100%" height="1500px"></iframe>

docs/tutorials/transform_color_correction_tutorial.md

@@ -1,5 +1,5 @@
 ## Tutorial: Color Correction Workflow
 
-[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/danforthcenter/plantcv-binder.git/master?filepath=notebooks/color_correction_tutorial/color_correct_tutorial.ipynb) Check out our interactive color correction tutorial! 
+[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/danforthcenter/plantcv-tutorial-color-correction.git/main?labath=index.ipynb) Check out our interactive color correction tutorial! 
 
-<iframe src="https://nbviewer.jupyter.org/github/danforthcenter/plantcv-binder/blob/master/notebooks/color_correction_tutorial/color_correct_tutorial.ipynb" width="100%" height="1500px"></iframe>
+<iframe src="https://nbviewer.jupyter.org/github/danforthcenter/plantcv-tutorial-color-correction/blob/main/index.ipynb" width="100%" height="1500px"></iframe>

plantcv/plantcv/homology/acute.py

@@ -36,7 +36,12 @@ def acute(img, mask, win, threshold):
     :param mask: numpy.ndarray
     :param win: int
     :param threshold: int
-    :return homolog_pts:
+    :return homolog_pts: numpy.ndarray
+    :return start_pts: numpy.ndarray
+    :return stop_pts: numpy.ndarray
+    :return ptvals: list
+    :return chain: lsit
+    :return verbose_out: list
     """
     # Find contours
     contours, hierarchy = _cv2_findcontours(bin_img=mask)
@@ -80,12 +85,6 @@ def acute(img, mask, win, threshold):
         p23 = np.sqrt((pt_a[0][0]-pt_b[0][0])*(pt_a[0][0]-pt_b[0][0])+(pt_a[0][1]-pt_b[0][1])*(pt_a[0][1]-pt_b[0][1]))
         dot = (p12*p12 + p13*p13 - p23*p23)/(2*p12*p13)
 
-        # Used a random number generator to test if either of these cases were possible but neither is possible
-        # if dot > 1:              # If float exceeds 1 prevent arcos error and force to equal 1
-        #     dot = 1
-        # elif dot < -1:           # If float exceeds -1 prevent arcos error and force to equal -1
-        #     dot = -1
-
         ang = math.degrees(math.acos(dot))
         # print(str(k)+'  '+str(dot)+'  '+str(ang))
         chain.append(ang)
@@ -96,10 +95,6 @@ def acute(img, mask, win, threshold):
         if float(link) <= threshold:
             index.append(c)         # Append positions of acute links to index
 
-    # acute_pos = obj[index]            # Extract all island points blindly
-    #
-    # float(len(acute_pos)) / float(len(obj))  # Proportion of informative positions
-
     if len(index) != 0:
 
         isle = []
@@ -160,31 +155,6 @@ def acute(img, mask, win, threshold):
             else:
                 ptvals.append('NaN')        # If no values can be retrieved (small/collapsed contours)
                 vals = []
-
-            # Identify pixel coordinate to use as pseudolandmark for island
-            # if len(isle[x]) == 1:           # If landmark is a single point (store position)
-            #    if debug == True:
-            #        print('route A')
-            #    pt = isle[x][0]
-            #    max_dist.append([isle[x][0], '-', chain[isle[x][0]]])
-            #    # print pt
-            # elif len(isle[x]) == 2:         # If landmark is a pair of points (store more acute position)
-            #    if debug == True:
-            #        print('route B')
-            #    pt_a = chain[isle[x][0]]
-            #    pt_b = chain[isle[x][1]]
-            #    print(pt_a, pt_b)
-            #    if pt_a == pt_b:
-            #        pt = isle[x][0]             # Store point A if both are equally acute
-            #        max_dist.append([isle[x][0], '-', chain[isle[x][0]]])
-            #    elif pt_a < pt_b:
-            #        pt = isle[x][0]             # Store point A if more acute
-            #        max_dist.append([isle[x][0], '-', chain[isle[x][0]]])
-            #    elif pt_a > pt_b:
-            #        pt = isle[x][1]             # Store point B if more acute
-            #        max_dist.append([isle[x][1], '-', chain[isle[x][1]]])
-            #     print pt
-
             if len(island) >= 3:               # If landmark is multiple points (distance scan for position)
                 if params.debug is not None:
                     print('route C')