test1 experiments. some optimizations

- added self.test1 for experimenting cleaner
- began steps to calculate map size
- optimize several functions by moving from mean to max

src/df_tools/dfwindow.py

@@ -1,4 +1,5 @@
 import time
+import timeit
 from pathlib import Path
 
 import cv2
@@ -8,6 +9,8 @@ from loguru import logger
 from .waytools import capActiveWindow, focusWindow, moveMouse
 from .waytools import sendKey as _sendKey
 
+# TODO: Consider type hinting images   from cv2.typing import MatLike
+
 
 class DFWINDOW:
     class TOOLS:
@@ -29,20 +32,20 @@ class DFWINDOW:
         ) -> tuple[int, int]:
             # Check the first (num_rows) rows at the top of the image,
             #   ignoring (ignore_cols) number of pixels at each end of teh line.
-            test_mean = np.mean(
+            test_max = np.max(
                 cv2.cvtColor(image_in[0:num_rows, ignore_cols:-ignore_cols], cv2.COLOR_BGR2GRAY),
                 axis=1,  # get the mean along the x-axis
             )
             # TODO: handle when 0 results return
             # Test the mean darkness, get the first row darker than 4
-            content_y = np.where(test_mean < mean_threshold)[0][0]
+            content_y = np.where(test_max < mean_threshold)[0][0]
 
             _ignore_rows = max(ignore_rows, content_y + 1)
-            test_mean = np.mean(
+            test_max = np.max(
                 cv2.cvtColor(image_in[_ignore_rows:-_ignore_rows, 0:num_cols], cv2.COLOR_BGR2GRAY),
                 axis=0,  # get the mean along the y-axis
             )
-            content_x = np.where(test_mean < mean_threshold)[0][0]
+            content_x = np.where(test_max < mean_threshold)[0][0]
 
             logger.debug(f"Content origin ({content_x}, {content_y})")
 
@@ -89,14 +92,14 @@ class DFWINDOW:
             return not np.any(thresh)
 
         @staticmethod
-        def firstNotBlackX(img):
-            first_x = np.where(np.mean(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), axis=0) > 15)[0][0]
-            return first_x
+        def firstNotBlackX(img) -> int:
+            first_x = np.where(np.max(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), axis=0) > 15)[0][0]
+            return int(first_x)
 
         @staticmethod
-        def firstNotBlackY(img):
-            first_y = np.where(np.mean(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), axis=1) > 15)[0][0]
-            return first_y
+        def firstNotBlackY(img) -> int:
+            first_y = np.where(np.max(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), axis=1) > 15)[0][0]
+            return int(first_y)
 
     bottom_to_ignore = 120
     sleep_after_mouse = 0.2
@@ -318,6 +321,9 @@ class DFWINDOW:
             logger.debug("Calibration error. Not at requested upper left of map")
             raise Exception("Calibration error. Not at requested upper left of map")
 
+        cal_left_border = self.TOOLS.firstNotBlackX(img)
+        cal_top_border = self.TOOLS.firstNotBlackY(img)
+
         # Test going to (max,max)
         self.setGridPos(self.maxGridX, self.maxGridY)
         time.sleep(self.sleep_after_panning)
@@ -330,7 +336,37 @@ class DFWINDOW:
             f"Grid calibration complete. Grid steps ({self._gridy_max + 1},{self._gridy_max + 1}), step sizes({self._step_size_x},{self._step_size_y})"
         )
 
+    def test1(self):
+        rawimg = cv2.imread("./test_img.png")
+        img = rawimg[100 : -self.bottom_to_ignore - 70, 65:-65]
+        tlb = self.TOOLS.firstNotBlackX(img)
+        ttb = self.TOOLS.firstNotBlackY(img)
+
+        tt_setup = r"gc.enable() ; import cv2 ; import numpy as np ; timg = cv2.imread('./test_img.png', cv2.IMREAD_UNCHANGED)"
+        tt1 = timeit.Timer(
+            "np.where(np.mean(cv2.cvtColor(timg, cv2.COLOR_BGR2GRAY), axis=0) > 15)[0][0]",
+            setup=tt_setup,
+        )
+        tt2 = timeit.Timer(
+            "np.where(np.max(cv2.cvtColor(timg, cv2.COLOR_BGR2GRAY), axis=0) > 25)[0][0]",
+            setup=tt_setup,
+        )
+        tt3 = timeit.Timer(
+            "np.where(np.max(cv2.cvtColor(timg, cv2.COLOR_BGRA2GRAY), axis=0) > 25)[0][0]",
+            setup=tt_setup,
+        )
+
+        num_tests = 80
+        r1 = tt1.timeit(number=num_tests)
+        r2 = tt2.timeit(number=num_tests)
+        r3 = tt3.timeit(number=num_tests)
+
+        logger.debug("Pause here for testing")
+
     def getPanoramaMap(self):
+        self.test1()
+        return
+
         self.calibrateGrid()
 
         # Test getting pieces and stitching