deploy: d2cabdd

Author: sahehb

pull/134/index.json

@@ -145,7 +145,7 @@
     minimumHeight = 300
     initCommand   = resetApplication
     Category {
-        // Vertical Layout and 4 Boxes with Horizontal Layout
+        // Vertical Layout and four Boxes with Horizontal Layout
         Vertical {
             Box Source {
                 layout = Horizontal

pull/134/tutorials/summary/summary8/index.html

@@ -91,7 +91,7 @@
 </span></span><span style=display:flex><span>    <span style=color:#75715e># Step 1: Get input image</span>
 </span></span><span style=display:flex><span>    image <span style=color:#f92672>=</span> ctx<span style=color:#f92672>.</span>field(<span style=color:#e6db74>&#34;inputImage&#34;</span>)<span style=color:#f92672>.</span>image()
 </span></span><span style=display:flex><span>    imageArray <span style=color:#f92672>=</span> image<span style=color:#f92672>.</span>getTile((<span style=color:#ae81ff>0</span>, <span style=color:#ae81ff>0</span>, <span style=color:#ae81ff>0</span>, <span style=color:#ae81ff>0</span>, <span style=color:#ae81ff>0</span>, <span style=color:#ae81ff>0</span>), image<span style=color:#f92672>.</span>imageExtent())
-</span></span><span style=display:flex><span>    inputImage <span style=color:#f92672>=</span> imageArray[<span style=color:#ae81ff>0</span>,<span style=color:#ae81ff>0</span>,<span style=color:#ae81ff>0</span>,:,:,:]<span style=color:#f92672>.</span>astype(<span style=color:#e6db74>&#34;float&#34;</span>)
+</span></span><span style=display:flex><span>    inputImage <span style=color:#f92672>=</span> imageArray[<span style=color:#ae81ff>0</span>, <span style=color:#ae81ff>0</span>, <span style=color:#ae81ff>0</span>, :, :, :]<span style=color:#f92672>.</span>astype(<span style=color:#e6db74>&#34;float&#34;</span>)
 </span></span><span style=display:flex><span>    
 </span></span><span style=display:flex><span>    <span style=color:#75715e># Step 2: Normalize input image</span>
 </span></span><span style=display:flex><span>    values <span style=color:#f92672>=</span> inputImage[inputImage <span style=color:#f92672>&gt;</span> inputImage<span style=color:#f92672>.</span>mean()]

pull/134/tutorials/thirdparty/pytorch/pytorchexample2/index.html

@@ -106,13 +106,13 @@
 </span></span><span style=display:flex><span>    gray <span style=color:#f92672>=</span> cv2<span style=color:#f92672>.</span>cvtColor(img, cv2<span style=color:#f92672>.</span>COLOR_BGR2GRAY)
 </span></span><span style=display:flex><span>    faces <span style=color:#f92672>=</span> face_cascade<span style=color:#f92672>.</span>detectMultiScale(gray, <span style=color:#ae81ff>1.1</span>, <span style=color:#ae81ff>4</span>)
 </span></span><span style=display:flex><span>    <span style=color:#66d9ef>for</span> (x, y, w, h) <span style=color:#f92672>in</span> faces:
-</span></span><span style=display:flex><span>        cv2<span style=color:#f92672>.</span>rectangle(img, (x, y), (x<span style=color:#f92672>+</span>w, y<span style=color:#f92672>+</span>h), (<span style=color:#ae81ff>255</span>, <span style=color:#ae81ff>0</span>, <span style=color:#ae81ff>0</span>), <span style=color:#ae81ff>2</span>)
+</span></span><span style=display:flex><span>        cv2<span style=color:#f92672>.</span>rectangle(img, (x, y), (x <span style=color:#f92672>+</span> w, y <span style=color:#f92672>+</span> h), (<span style=color:#ae81ff>255</span>, <span style=color:#ae81ff>0</span>, <span style=color:#ae81ff>0</span>), <span style=color:#ae81ff>2</span>)
 </span></span><span style=display:flex><span>    <span style=color:#75715e># Display the output</span>
 </span></span><span style=display:flex><span>    cv2<span style=color:#f92672>.</span>imshow(<span style=color:#e6db74>&#39;img&#39;</span>, img)
 </span></span><span style=display:flex><span>
 </span></span><span style=display:flex><span><span style=color:#75715e># Update image in interface</span>
 </span></span><span style=display:flex><span><span style=color:#66d9ef>def</span> <span style=color:#a6e22e>updateImage</span>(image):
-</span></span><span style=display:flex><span>    _interfaces[<span style=color:#ae81ff>0</span>]<span style=color:#f92672>.</span>setImage(OpenCVUtils<span style=color:#f92672>.</span>convertImageToML(image), minMaxValues <span style=color:#f92672>=</span> [<span style=color:#ae81ff>0</span>,<span style=color:#ae81ff>255</span>])
+</span></span><span style=display:flex><span>    _interfaces[<span style=color:#ae81ff>0</span>]<span style=color:#f92672>.</span>setImage(OpenCVUtils<span style=color:#f92672>.</span>convertImageToML(image), minMaxValues <span style=color:#f92672>=</span> [<span style=color:#ae81ff>0</span>, <span style=color:#ae81ff>255</span>])
 </span></span><span style=display:flex><span>
 </span></span><span style=display:flex><span><span style=color:#75715e># Start capturing webcam</span>
 </span></span><span style=display:flex><span><span style=color:#66d9ef>def</span> <span style=color:#a6e22e>startCapture</span>():
@@ -167,7 +167,7 @@
 </span></span><span style=display:flex><span>    <span style=color:#75715e># Step 1: Get image from webcam capture</span>
 </span></span><span style=display:flex><span>    stopCapture()
 </span></span><span style=display:flex><span>    inImage <span style=color:#f92672>=</span> ctx<span style=color:#f92672>.</span>field(<span style=color:#e6db74>&#34;PythonImage.output0&#34;</span>)<span style=color:#f92672>.</span>image()
-</span></span><span style=display:flex><span>    img <span style=color:#f92672>=</span> inImage<span style=color:#f92672>.</span>getTile((<span style=color:#ae81ff>0</span>,<span style=color:#ae81ff>0</span>,<span style=color:#ae81ff>0</span>,<span style=color:#ae81ff>0</span>,<span style=color:#ae81ff>0</span>,<span style=color:#ae81ff>0</span>), inImage<span style=color:#f92672>.</span>imageExtent())[<span style=color:#ae81ff>0</span>,<span style=color:#ae81ff>0</span>,:,<span style=color:#ae81ff>0</span>,:,:]
+</span></span><span style=display:flex><span>    img <span style=color:#f92672>=</span> inImage<span style=color:#f92672>.</span>getTile((<span style=color:#ae81ff>0</span>, <span style=color:#ae81ff>0</span>, <span style=color:#ae81ff>0</span>, <span style=color:#ae81ff>0</span>, <span style=color:#ae81ff>0</span>, <span style=color:#ae81ff>0</span>), inImage<span style=color:#f92672>.</span>imageExtent())[<span style=color:#ae81ff>0</span>, <span style=color:#ae81ff>0</span>, :, <span style=color:#ae81ff>0</span>, :, :]
 </span></span><span style=display:flex><span>      
 </span></span><span style=display:flex><span>    <span style=color:#75715e># Step 2: Convert image into torch tensor</span>
 </span></span><span style=display:flex><span>    img <span style=color:#f92672>=</span> torch<span style=color:#f92672>.</span>Tensor(img)<span style=color:#f92672>.</span>type(torch<span style=color:#f92672>.</span>uint8)