Update release notes for R5.0.1. (#115)

Author: jrobble

docs/docs/Release-Notes.md

@@ -8,6 +8,12 @@
 - <span style="color:red">TODO: This new component detects objects in images and videos by making use of an [NVIDIA TensorRT Inference Server](https://docs.nvidia.com/deeplearning/sdk/tensorrt-inference-server-guide/docs/) (TRTIS), and calculates features that can later be used by other systems to recognize the same object in other media. We provide support for running the server as a separate service during a Docker deployment, but an external server instance can be used instead. By default, the ip_irv2_coco model is supported and will optionally classify detected objects using [COCO labels](https://github.com/openmpf/openmpf-components/blob/master/cpp/trtisdetection/plugin-files/models/ip_irv2_coco.labels). Additionally, features can be generated for whole frames, automatically-detected object regions, and user-specified regions. Refer to the [README](https://github.com/openmpf/openmpf-components/blob/master/cpp/trtisdetection/README.md).</span>
 -->
 
+# OpenMPF 5.0.1: July 2020
+
+<h2>Updates</h2>
+
+- Updated Tessseract component with `MAX_PIXELS` setting to prevent processing large images.
+
 # OpenMPF 5.0.0: June 2020
 
 <h2>Documentation</h2>

docs/site/Release-Notes/index.html

@@ -64,6 +64,9 @@
 
             <ul>
 
+                <li class="toctree-l3"><a href="#openmpf-501-july-2020">OpenMPF 5.0.1: July 2020</a></li>
+                
+            
                 <li class="toctree-l3"><a href="#openmpf-500-june-2020">OpenMPF 5.0.0: June 2020</a></li>
 
 
@@ -318,6 +321,12 @@ <h2 style="color:red">TensorRT Inference Server (TRTIS) Object Detection Compone
 - <span style="color:red">TODO: This new component detects objects in images and videos by making use of an [NVIDIA TensorRT Inference Server](https://docs.nvidia.com/deeplearning/sdk/tensorrt-inference-server-guide/docs/) (TRTIS), and calculates features that can later be used by other systems to recognize the same object in other media. We provide support for running the server as a separate service during a Docker deployment, but an external server instance can be used instead. By default, the ip_irv2_coco model is supported and will optionally classify detected objects using [COCO labels](https://github.com/openmpf/openmpf-components/blob/master/cpp/trtisdetection/plugin-files/models/ip_irv2_coco.labels). Additionally, features can be generated for whole frames, automatically-detected object regions, and user-specified regions. Refer to the [README](https://github.com/openmpf/openmpf-components/blob/master/cpp/trtisdetection/README.md).</span>
 -->
 
+<h1 id="openmpf-501-july-2020">OpenMPF 5.0.1: July 2020</h1>
+<h2>Updates</h2>
+
+<ul>
+<li>Updated Tessseract component with <code>MAX_PIXELS</code> setting to prevent processing large images.</li>
+</ul>
 <h1 id="openmpf-500-june-2020">OpenMPF 5.0.0: June 2020</h1>
 <h2>Documentation</h2>
 

docs/site/index.html

@@ -398,5 +398,5 @@ <h1 id="overview">Overview</h1>
 
 <!--
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-Build Date UTC : 2020-07-03 18:38:48
+Build Date UTC : 2020-07-03 18:54:28
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