Update documentation

_sources/lib/Vision.rst.txt

@@ -0,0 +1,102 @@
+.. _lib_vision:
+
+Vision
+=====
+
+This module provides an interface for grabbing an rtmp stream and using the images to do some processing in opencv.
+
+How do I use this module?
+
+1. Get frames from the raspberry pi camera
+2. -- here comes your own processing --
+3. Publish the processed frames on an http server
+4. You can view the http stream of your processed images in a web browser
+
+Opencv Stream
+*************
+
+Because of the rtmp stream needing to buffer some frames and waiting for P-Frames, importing this module might take up
+to 5 Seconds.
+
+.. autoclass:: compLib.Vision.__Streaming
+   :members:
+
+Examples
+*********
+
+Using the Vision Module
+---------------------
+
+.. code-block:: python
+
+    import cv2
+    from compLib import Vision
+
+    # get newest opencv frame from camera
+    frame = Vision.Streaming.get_frame()
+
+    # do some processing with the frame.....
+
+    # publish frame to streaming server
+    Vision.Streaming.publish_frame(frame)
+
+Connect the raspberry pi to your internet and view the stream at: "http://your_raspi_ip:9898/". This should display
+your raspberry pi camera. Note: the stream will lag a little bit BUT the processing of the image will be done in
+realtime.
+
+The output on the website should show whatever your raspberry pi cam records:
+
+.. image:: images/opencv_http_stream.png
+  :width: 680
+  :alt: Processed frames from opencv
+
+
+Chessboard Detection
+------------------------------------------
+
+In this example we process the captured stream of images and want to detect chessboards. Run this example and
+point your raspberry pi camera to a chessboard and it should be detected.
+
+For testing you can point it at this image:
+
+.. image:: images/chessboard.jpg
+  :width: 680
+  :alt: Chessboard for opencv processing
+
+.. code-block:: python
+
+    import cv2
+    from compLib import Vision
+
+    # get newest opencv frame from camera
+    frame = Vision.Streaming.get_frame()
+
+    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
+
+    # convert image to grayscale image
+    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+
+    # find the chessboard corners
+    ret, corners = cv2.findChessboardCorners(gray, (6, 9), None)
+
+    # draw detected chessboard position onto the image
+    cv2.drawChessboardCorners(frame,  (6, 9), corners, ret)
+
+    # publish frame to streaming server
+    Vision.Streaming.publish_frame(frame)
+
+Connect the raspberry pi to your internet and view the stream at: "http://your_raspi_ip:9898/".
+
+The output image should look like this:
+
+.. image:: images/chessboard_detected.jpg
+  :width: 680
+  :alt: Processed frames from opencv
+
+Here is a screenshot of the stream website while viewing the chessboard in this documentation.
+
+.. image:: images/opencv_processed.png
+  :width: 680
+  :alt: Processed frames from opencv
+
+