Resolution set via env support

README.md

@@ -54,11 +54,6 @@ in building an autonomous formula. The project is proof of concept of cones dete
 the currently developed perception system. The positions of the cones seen through the camera are then
 used by the car’s autonomous system to drive.
 
-<!-- CAMERA PERCEPTION -->
-## Camera perception
-
-[Cones detection](https://github.com/lukaszmichalskii/camera-perception/blob/master/docs/yolo/autocross.mp4) model in version 2.0 during PWR Racing Team car test on autocross event
-
 <!-- BACKLOG -->
 ## Backlog
 

src/camera_perception/camera.py

@@ -6,7 +6,8 @@ class CameraError(Exception):
 
 
 class Camera:
- def __init__(self, video):
+ def __init__(self, video, resolution):
+ self.frame_width, self.frame_height = resolution
  self.lens = cv2.VideoCapture(video)
 
  def get_frame(self):
@@ -17,6 +18,7 @@ def get_frame(self):
  ret, frame = self.lens.read()
  if not ret:
  break
+ frame = cv2.resize(frame, (self.frame_width, self.frame_height))
  yield frame
 
  def turn_off(self):

src/camera_perception/common.py

@@ -1,3 +1,4 @@
+import re
 from platform import platform
 
 import torch
@@ -17,6 +18,12 @@ def processing_unit() -> str:
  return "CUDA" if torch.cuda.is_available() else "CPU"
 
 
+def get_resolution(resolution_env):
+ regex = r"\d+"
+ resolution = re.findall(regex, resolution_env)
+ return int(resolution[0]), int(resolution[1])
+
+
 class Environment:
  """
  Class for storing user specific configuration overwritten using environmental variables
@@ -26,14 +33,19 @@ def __init__(self, env):
  self.os = get_current_os()
  self.conf = float(env.get("CONFIDENCE", 0.7))
  self.processing_unit = processing_unit()
+ self.resolution = get_resolution(env.get("RESOLUTION", "1280x720"))
 
  @staticmethod
  def from_env(env):
  return Environment(env)
 
  def to_info_string(self):
- return "os: {}, processing unit: {}, detections confidence: {}%".format(
- self.os, self.processing_unit, self.conf * 100
+ return "os: {}, processing unit: {}, detections confidence: {}%, resolution: {}x{}".format(
+ self.os,
+ self.processing_unit,
+ self.conf * 100,
+ self.resolution[0],
+ self.resolution[1],
  )
 
  def cuda_to_info_string(self):

src/camera_perception/main.py

@@ -25,6 +25,8 @@ def get_help_epilog():
 Environment variables:
  CONFIDENCE : Model detection confidence threshold
  Default: 0.7
+ RESOLUTION : Frame or image resolution, for better performance consider smaller resolutions
+ Default: 1280x720
  
 Usage:
  Run system with video:
@@ -86,7 +88,7 @@ def label():
  return 4
 
  font = cv2.FONT_HERSHEY_DUPLEX
- camera_lens = Camera(args.video)
+ camera_lens = Camera(args.video, environment.resolution)
  cones_detector = ConesDetector()
  try:
  for frame in camera_lens.get_frame():