Prepare for pre-release

src/driver_station.py

@@ -2,6 +2,8 @@
 import numpy as np
 import cv2
 
+# WIP Feature, not currently used.
+
 # data_dict holds both images and the camera that took them
 def get_driver_frame(data_dict):
     # Just get the cameras marked as driver
@@ -11,12 +13,11 @@ def get_driver_frame(data_dict):
     if drivers:
         # Arrange the images into one collage
         collage = create_collage(drivers)
+        collage = cv2.resize(collage, (50,50))
     else:
         # Just give back a blank image
         # TODO: Descriptive image
         collage = np.zeros(shape=[512,512,3], dtype=np.uint8)
-
-    cv2.imshow("collage", collage)
     return collage
 
 

src/main.py

@@ -105,10 +105,6 @@ def main():
     }
     api = ShuffleLogAPI(messenger_params, environment['tags'], cameras['cameras'])
 
-    # Initialize Flask camera stream
-    port = 5802
-    stream = Streamer(port, False)
-    stream.start_streaming()
 
     # Main loop, run all the time like limelight
     while True:
@@ -118,8 +114,6 @@ def main():
 
         position, matrices = solver.solve(detection_poses)
 
-        # print(position)
-
         if not args.no_gui:
             for i, image in enumerate(data):
                 cv2.imshow(str(i), image['image'])
@@ -129,9 +123,6 @@ def main():
         if position is None: position = [0, 0, 0]
         table.putNumberArray('position', position)
 
-        # Send the camera feed to driver station
-        stream.update_frame(get_driver_frame(data))
-
         # Read incoming API messages
         api.read()