Merged PR 548: fix relative links from local Jekyll

fix relative links from local Jekyll

Gemfile

@@ -3,5 +3,6 @@ source 'https://rubygems.org'
 gem 'jekyll'
 gem 'jekyll-paginate'
 gem 'jekyll-sass-converter'
+gem 'jekyll-relative-links'
 gem 'kramdown'
 gem 'rouge'

_config.yml

@@ -9,6 +9,8 @@ author:
 #  url:        https://github.com/Microsoft/ELL 
 
 # Gems
+plugins:
+  - jekyll-relative-links
 
 destination: ./_site
 plugins_dir:     ./_plugins
@@ -17,6 +19,9 @@ data_dir: ./_data
 
 source: docs
 
+relative_links:
+  enabled:     true
+  collections: false
 
 # Handling Reading
 safe:         false
@@ -76,3 +81,5 @@ kramdown:
 
 sass:
     sass_dir: _sass
+
+

docs/_config.yml

@@ -9,6 +9,8 @@ author:
 #  url:        https://github.com/Microsoft/ELL 
 
 # Gems
+plugins:
+  - jekyll-relative-links
 
 destination: ./_site
 plugins_dir:     ./_plugins
@@ -17,6 +19,9 @@ data_dir: ./_data
 
 source: docs
 
+relative_links:
+  enabled:     true
+  collections: false
 
 # Handling Reading
 safe:         false

docs/css/syntax.scss

@@ -3,8 +3,6 @@
 # only Main files contain this front matter, not partials.
 ---
 
-// This file is generated by rougify for the selected theme (DO NOT EDIT)
-
 .highlight table td { padding: 5px; }
 .highlight table pre { margin: 0; }
 .highlight, .highlight .w {
@@ -80,8 +78,8 @@
 .highlight .nf {
   color: #5F0281;  
 }
-.highlight .na {
-  color: #268bd2;
+.highlight .na, .highlight .nb {
+  color: #0000ff;
 }
 .highlight .m, .highlight .mf, .highlight .mh, .highlight .mi, .highlight .il, .highlight .mo, .highlight .mb, .highlight .mx {
   color: #a31515;

tools/utilities/pitest/drivetest.py

@@ -174,7 +174,7 @@ def find_files_with_extension(self, path, extension):
     def get_bash_files(self):
         # copy demo files needed to run the test
         self.copy_files( [ os.path.join(self.ell_root, "tools/utilities/pitest/coffeemug.jpg"),
-                           os.path.join(self.ell_root, "docs/tutorials/shared/demo.py"),
+                           os.path.join(self.ell_root, "tools/utilities/pythonlibs/demo.py"),
                            os.path.join(self.ell_root, "tools/utilities/pythonlibs/demoHelper.py") ], self.output_dir) 
         self.configure_runtest(self.output_dir)
 

tools/utilities/pythonlibs/demo.py

@@ -0,0 +1,74 @@
+####################################################################################################
+##
+##  Project:  Embedded Learning Library (ELL)
+##  File:     demo.py
+##  Authors:  Chris Lovett
+##
+##  Requires: Python 3.x
+##
+####################################################################################################
+
+import sys
+import os
+import numpy as np
+import cv2
+import demoHelper as d
+
+# note: to run this in headless mode on a Linux machine run the following from your terminal window
+# export DISPLAY=:0
+# then add the '-save' argument to get tagged frames to be saved to disk.
+
+def main(args):
+    helper = d.DemoHelper()
+    helper.parse_arguments(args,
+            "Runs the given ELL model passing images from camera or static image file\n"
+            "Either the ELL model file, or the compiled model's Python module must be given,\n"
+            "using the --model or --compiledModel options respectively.\n"
+            "Example:\n"
+            "   python demo.py categories.txt --compiledModel tutorial1/pi3/model1\n"
+            "   python demo.py categories.txt --model model1.ell\n"
+            "This shows opencv window with image classified by the model using given labels")
+
+    # Initialize image source
+    helper.init_image_source()
+
+    lastPrediction = ""
+
+    while (not helper.done()):
+        # Grab next frame
+        frame = helper.get_next_frame()
+
+        # Prepare the image to send to the model.
+        # This involves scaling to the required input dimension and re-ordering from BGR to RGB
+        data = helper.prepare_image_for_predictor(frame)
+
+        # Get the model to classify the image, by returning a list of probabilities for the classes it can detect
+        predictions = helper.predict(data)
+
+        # Get the (at most) top 5 predictions that meet our threshold. This is returned as a list of tuples,
+        # each with the text label and the prediction score.
+        top5 = helper.get_top_n_predictions(predictions, 5)
+
+        # Turn the top5 into a text string to display
+        text = ", ".join(["(" + str(int(element[1]*100)) + "%) " + helper.get_label(element[0]) for element in top5])
+
+        save = False
+        if (text != lastPrediction):
+            print(text)
+            save = True
+            lastPrediction = text
+
+        # Draw the text on the frame
+        frameToShow = frame
+        helper.draw_label(frameToShow, text)
+        helper.draw_fps(frameToShow)
+
+        # Show the new frame
+        helper.show_image(frameToShow, save)
+
+    helper.report_times()
+
+if __name__ == "__main__":
+    args = sys.argv
+    args.pop(0) # when an args list is passed to parse_args, the first argument (program name) needs to be dropped
+    main(args)