Linting

test/cv_helper.py

@@ -1,40 +1,35 @@
-import itertools
-from typing import Tuple, List, Dict
-import zipfile
-import io
-import json
-import dataclasses
+"""Contains function to manually test the visual detection of a board"""
 
 import numpy as np
 import cv2
 
-from .context import shenzhen_solitaire
 from shenzhen_solitaire.cv import adjustment
-from shenzhen_solitaire.cv import card_finder
 from shenzhen_solitaire.cv import board_parser
 from shenzhen_solitaire import board
 from shenzhen_solitaire.cv.configuration import Configuration
 
 
 def generate() -> None:
-    with open("Solitaire.png", 'rb') as fd:
-        img_str = fd.read()
+    """Generate a configuration"""
+    with open("Solitaire.png", 'rb') as png_file:
+        img_str = png_file.read()
     nparr = np.frombuffer(img_str, np.uint8)
     image = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
 
-    a = Configuration.generate(image)
-    a.save('test_config.zip')
+    generated_config = Configuration.generate(image)
+    generated_config.save('test_config.zip')
 
 def parse() -> board.Board:
-    with open("Solitaire2.png", 'rb') as fd:
-        img_str = fd.read()
+    """Parse a configuration"""
+    with open("Solitaire2.png", 'rb') as png_file:
+        img_str = png_file.read()
     nparr = np.frombuffer(img_str, np.uint8)
     image = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
     image = cv2.resize(image, (1000, 629))
 
-    a = Configuration.load('test_config.zip')
-    a.field_adjustment = adjustment.adjust_field(image)
-    return board_parser.parse_board(image, a)
+    loaded_config = Configuration.load('test_config.zip')
+    loaded_config.field_adjustment = adjustment.adjust_field(image)
+    return board_parser.parse_board(image, loaded_config)
 
 
 if __name__ == "__main__":