Fixes and a few additional helper functions

- corrected the return type of a few functions to int
- Add DFWINDOW.TOOLS.getImageDiff to get how diff 2 images are
- Added complimentary lastNotBlack(X/Y)
- Increase blindly chosen preset "bottom_to_ignore". Wasnt enough when full screen.
- Fixed the sign/polarity of step sizes
- First attempt at calculating the size of the map. Probably wrong. Will replace when writing the map maker
- removed cv2.Stitcher stuff. Not what I needed
- Added some test_ functions for experimenting. Ignore.

.gitignore

@@ -231,3 +231,4 @@ Thumbs.db
 # experiment garbage
 
 *.png
+src/calib_info.json

src/df_tools/dfwindow.py

@@ -1,3 +1,4 @@
+import json
 import time
 import timeit
 from pathlib import Path
@@ -49,7 +50,7 @@ class DFWINDOW:
 
             logger.debug(f"Content origin ({content_x}, {content_y})")
 
-            return (content_x, content_y)
+            return (int(content_x), int(content_y))
 
         @staticmethod
         def isRightBorder(img, num_columns=20, border_threshold: int = 10) -> bool:
@@ -61,6 +62,20 @@ class DFWINDOW:
             # Are all pixels in the strip "black"
             return not np.any(thresh)
 
+        @staticmethod
+        def getImageDiff(image1, image2, conversion=cv2.COLOR_BGR2GRAY) -> float:
+            # Diff size, very dif img
+            if image1.shape != image2.shape:
+                return float("inf")
+            grey1 = cv2.cvtColor(image1, conversion)
+            grey2 = cv2.cvtColor(image2, conversion)
+
+            # Apparently this is the Mean Squared Error (MES). Thanks Gemini (LLM)
+            err = np.sum((grey1.astype("float") - grey2.astype("float")) ** 2)
+            err /= float(grey1.shape[0] * grey1.shape[0])
+
+            return float(err)
+
         @staticmethod
         def isLeftBorder(img, num_columns=20, border_threshold: int = 10) -> bool:
             # grab a greyscale strip to look at
@@ -93,19 +108,29 @@ class DFWINDOW:
 
         @staticmethod
         def firstNotBlackX(img) -> int:
-            first_x = np.where(np.max(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), axis=0) > 15)[0][0]
+            first_x = np.where(np.max(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), axis=0) > 5)[0][0]
+            return int(first_x)
+
+        @staticmethod
+        def lastNotBlackX(img) -> int:
+            first_x = np.where(np.max(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), axis=0) > 5)[0][-1]
             return int(first_x)
 
         @staticmethod
         def firstNotBlackY(img) -> int:
-            first_y = np.where(np.max(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), axis=1) > 15)[0][0]
+            first_y = np.where(np.max(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), axis=1) > 5)[0][0]
             return int(first_y)
 
-    bottom_to_ignore = 120
+        @staticmethod
-    sleep_after_mouse = 0.2
+        def lastNotBlackY(img) -> int:
-    sleep_after_key = 0.08
+            first_y = np.where(np.max(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), axis=1) > 5)[0][-1]
-    sleep_after_focus = 0.3
+            return int(first_y)
-    sleep_after_panning = 0.3
+
+    bottom_to_ignore = 160
+    sleep_after_mouse = 0.2  # 2
+    sleep_after_key = 0.08  # 08
+    sleep_after_focus = 0.2  # 3
+    sleep_after_panning = 0.2  # 3
     query_for_window = "dwarfort"
 
     def __init__(self) -> None:
@@ -227,8 +252,8 @@ class DFWINDOW:
         self.sendKeys("a", 30)
         img = self.capWindow()
         self._content_left, self._content_top = self.TOOLS.find_content_origin(img)
-        self._content_right = img.shape[1] - self._content_left
+        self._content_right = int(img.shape[1] - self._content_left)
-        self._content_bottom = img.shape[0] - self.bottom_to_ignore
+        self._content_bottom = int(img.shape[0] - self.bottom_to_ignore)
         img = img[self._content_top : self._content_bottom, self._content_left : self._content_right]  # pyright: ignore[reportOptionalSubscript]
         logger.debug(f"Content width {self.contentWidth}. Content height {self.contentHeight}.")
 
@@ -242,8 +267,8 @@ class DFWINDOW:
         img = self.capContent()
         mx2 = self.TOOLS.firstNotBlackX(img)
         my2 = self.TOOLS.firstNotBlackY(img)
-        self._step_size_x = mx2 - mx1
+        self._step_size_x = mx1 - mx2
-        self._step_size_y = my2 - my1
+        self._step_size_y = my1 - my2
         logger.info(f"Step sizes calculated: x={self._step_size_x} and y={self._step_size_y}")
         self.sendKeys("w")
         self.sendKeys("a")
@@ -306,13 +331,6 @@ class DFWINDOW:
         self._gridx = steps_right
         self._gridy = steps_down
 
-        # TODO: Use seek tests to calculate mapsize in pixels
-        #   at (0,0) save left_edge_offset and top_edge_offset
-        #   at (max,max) save right_edge_offset and bottom_edge_offset
-        #   width = (contentWidth - l_e_o) + (gridyx_max * _step_size_x) - abs(r_e_o)
-        #   | <==|====|====|==>  |
-        #   (max*size) is too far, so we subract the ofset/border from the right map edge
-
         # Test going to 0,0
         self.setGridPos(0, 0)
         time.sleep(self.sleep_after_panning)
@@ -332,17 +350,46 @@ class DFWINDOW:
             logger.debug("Calibration error. Not at requested lower right of map")
             raise Exception("Calibration error. Not at requested lower right of map")
 
+        cal_right_border = self.TOOLS.lastNotBlackX(img)
+        cal_bottom_border = self.TOOLS.lastNotBlackY(img)
+
+        # TODO: Use seek tests to calculate mapsize in pixels
+        #   at (0,0) save left_edge_offset and top_edge_offset
+        #   at (max,max) save right_edge_offset and bottom_edge_offset
+        #   width = (contentWidth - l_e_o) + (gridyx_max * _step_size_x) - abs(r_e_o)
+        #   | <==|====|====|==>  |
+        #   (max*size) is too far, so we subract the ofset/border from the right map edge
+
+        self._map_width = (
+            (img.shape[1] - cal_left_border)  # Grid x = 0
+            + ((self._gridx_max - 1) * self._step_size_x)  # All the middle
+            + cal_right_border  # grid x = max
+        )
+
+        self._map_height = (
+            (img.shape[0] - cal_top_border)  # Grid x = 0
+            + ((self._gridy_max - 1) * self._step_size_y)  # All the middle
+            + cal_right_border  # grid x = max
+        )
+
+        self.setGridPos(0, 0)
+
+        logger.debug(f"Map dimensions calculated as {self._map_width} x {self._map_height}")
+
         logger.info(
             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")
+        # rawimg = cv2.imread("./test_img.png")
+        rawimg = cv2.imread("grid_base_3.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)"
+        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,
@@ -363,30 +410,57 @@ class DFWINDOW:
 
         logger.debug("Pause here for testing")
 
+    def test_saveGrids(self):
+        savedir = Path()
+        savefile_base = "cached_grid"
+        savefile_ext = "png"
+        for x in range(0, self._gridx_max + 1):
+            for y in range(0, self._gridy_max):
+                self.setGridPos(x, y)
+                time.sleep(self.sleep_after_panning)
+                img = self.capContent()
+                savefilename = savedir.joinpath(f"{savefile_base}_{x}_{y}.{savefile_ext}")
+                cv2.imwrite(str(savefilename.resolve()), img)
+        calib_info = {
+            "gridx": int(self._gridx),
+            "gridy": int(self._gridy),
+            "gridx_max": int(self._gridx_max),
+            "gridy_max": int(self._gridy_max),
+            "step_size_x": int(self._step_size_x),
+            "step_size_y": int(self._step_size_y),
+            "content_top": int(self._content_top),
+            "content_bottom": int(self._content_bottom),
+            "content_left": int(self._content_left),
+            "content_right": int(self._content_right),
+            "map_height": int(self._map_height),
+            "map_width": int(self._map_width),
+        }
+        with open("./calib_info.json", "w") as fh:
+            json.dump(calib_info, fh)
+
+    def test_loadCalib(self):
+        with open("./calib_info.json") as fh:
+            calib_info = json.load(fh)
+
+        self._gridx = calib_info["gridx"]
+        self._gridy = calib_info["gridy"]
+        self._gridx_max = calib_info["gridx_max"]
+        self._gridy_max = calib_info["gridy_max"]
+        self._step_size_x = calib_info["step_size_x"]
+        self._step_size_y = calib_info["step_size_y"]
+        self._content_top = calib_info["content_top"]
+        self._content_bottom = calib_info["content_bottom"]
+        self._content_left = calib_info["content_left"]
+        self._content_right = calib_info["content_right"]
+        self._map_height = calib_info["map_height"]
+        self._map_width = calib_info["map_width"]
+
     def getPanoramaMap(self):
-        self.test1()
+        # self.test1()
-        return
+        # return
 
         self.calibrateGrid()
-
+        # self.test_saveGrids()
-        # Test getting pieces and stitching
+        # self.test_loadCalib()
-        stitcher = cv2.Stitcher.create(cv2.STITCHER_SCANS)
-        stitcher.setPanoConfidenceThresh(0.1)  # Dont be confident
-
-        imgs_in_row = []
-
-        # Get a row
-        self.setGridPos(0, 0)
-        time.sleep(self.sleep_after_panning)
-        for x in range(0, self.maxGridX + 1, 3):
-            self.setGridPos(x, self.curGridY)
-            time.sleep(self.sleep_after_panning)
-            img = self.capContent()
-            if img.shape[2] == 4:
-                img = cv2.cvtColor(img, cv2.COLOR_BGRA2BGR)
-            imgs_in_row.append(img)
-
-        status, strip = stitcher.stitch(imgs_in_row)
-        logger.debug(f"{len(imgs_in_row)} images. {status=}  {strip=} {status == cv2.Stitcher_OK}")
 
         return None