Run yapf on all python files in the repo

Signed-off-by: Ravago Jones <ravagojones@gmail.com>
Change-Id: I221e04c3f517fab8535b22551553799e0fee7a80
diff --git a/y2020/vision/galactic_search_path.py b/y2020/vision/galactic_search_path.py
index 00b572a..11ec73d 100755
--- a/y2020/vision/galactic_search_path.py
+++ b/y2020/vision/galactic_search_path.py
@@ -8,6 +8,7 @@
 import numpy as np
 import os
 
+
 class Rect:
 
     # x1 and y1 are top left corner, x2 and y2 are bottom right
@@ -41,11 +42,14 @@
 
     @staticmethod
     def from_value(value):
-        return (Alliance.kRed if value == Alliance.kRed.value else Alliance.kBlue)
+        return (Alliance.kRed
+                if value == Alliance.kRed.value else Alliance.kBlue)
 
     @staticmethod
     def from_name(name):
-        return (Alliance.kRed if name == Alliance.kRed.name else Alliance.kBlue)
+        return (Alliance.kRed
+                if name == Alliance.kRed.name else Alliance.kBlue)
+
 
 class Letter(Enum):
     kA = 'A'
@@ -59,6 +63,7 @@
     def from_name(name):
         return (Letter.kA if name == Letter.kA.name else Letter.kB)
 
+
 class Path:
 
     def __init__(self, letter, alliance, rects):
@@ -72,15 +77,18 @@
     def to_dict(self):
         return {"alliance": self.alliance.name, "letter": self.letter.name}
 
+
 RECTS_JSON_PATH = "rects.json"
 
 AOS_SEND_PATH = "bazel-bin/aos/aos_send"
 
+
 def setup_if_pi():
     if os.path.isdir("/home/pi/bin"):
         AOS_SEND_PATH = "/home/pi/bin/aos_send.stripped"
         os.system("./starter_cmd stop camera_reader")
 
+
 setup_if_pi()
 
 # The minimum percentage of yellow for a region of a image to
@@ -89,12 +97,14 @@
 
 _paths = []
 
+
 def load_json():
     rects_dict = None
     with open(RECTS_JSON_PATH, 'r') as rects_json:
         rects_dict = json.load(rects_json)
     return rects_dict
 
+
 def _run_detection_loop():
     global img_fig, rects_dict
 
@@ -104,7 +114,9 @@
             rects = []
             for rect_list in rects_dict[letter][alliance]:
                 rects.append(Rect.from_list(rect_list))
-            _paths.append(Path(Letter.from_name(letter), Alliance.from_name(alliance), rects))
+            _paths.append(
+                Path(Letter.from_name(letter), Alliance.from_name(alliance),
+                     rects))
 
     plt.ion()
     img_fig = plt.figure()
@@ -113,6 +125,7 @@
     while running:
         _detect_path()
 
+
 def _detect_path():
     img = capture_img()
     img_fig.figimage(img)
@@ -138,7 +151,8 @@
                 current_path = path
                 num_current_paths += 1
         else:
-            glog.error("Error: len of pcts (%u) != len of rects: (%u)", len(pcts), len(rects))
+            glog.error("Error: len of pcts (%u) != len of rects: (%u)",
+                       len(pcts), len(rects))
 
     if num_current_paths != 1:
         if num_current_paths == 0:
@@ -147,24 +161,27 @@
         glog.warn("Expected 1 path but detected %u", num_current_paths)
         return
 
-
     path_dict = current_path.to_dict()
     glog.info("Path is %s", path_dict)
     os.system(AOS_SEND_PATH +
-              " /pi2/camera y2020.vision.GalacticSearchPath '" + json.dumps(path_dict) + "'")
+              " /pi2/camera y2020.vision.GalacticSearchPath '" +
+              json.dumps(path_dict) + "'")
+
 
 KERNEL = np.ones((5, 5), np.uint8)
 
+
 def _create_mask(img):
     hsv = cv.cvtColor(img, cv.COLOR_BGR2HSV)
-    lower_yellow = np.array([23, 100, 75], dtype = np.uint8)
-    higher_yellow = np.array([40, 255, 255], dtype = np.uint8)
+    lower_yellow = np.array([23, 100, 75], dtype=np.uint8)
+    higher_yellow = np.array([40, 255, 255], dtype=np.uint8)
     mask = cv.inRange(hsv, lower_yellow, higher_yellow)
-    mask = cv.erode(mask, KERNEL, iterations = 1)
-    mask = cv.dilate(mask, KERNEL, iterations = 3)
+    mask = cv.erode(mask, KERNEL, iterations=1)
+    mask = cv.dilate(mask, KERNEL, iterations=3)
 
     return mask
 
+
 # This function finds the percentage of yellow pixels in the rectangles
 # given that are regions of the given image. This allows us to determine
 # whether there is a ball in those rectangles
@@ -172,25 +189,30 @@
     pcts = np.zeros(len(rects))
     for i in range(len(rects)):
         rect = rects[i]
-        slice = mask[rect.y1 : rect.y2, rect.x1 : rect.x2]
+        slice = mask[rect.y1:rect.y2, rect.x1:rect.x2]
         yellow_px = np.count_nonzero(slice)
         pcts[i] = yellow_px / (slice.shape[0] * slice.shape[1])
 
     return pcts
 
+
 _video_stream = cv.VideoCapture(0)
 
+
 def capture_img():
     global _video_stream
     return _video_stream.read()[1]
 
+
 def release_stream():
     global _video_stream
     _video_stream.release()
 
+
 def main():
     _run_detection_loop()
     release_stream()
 
+
 if __name__ == "__main__":
     main()