From 0b7f80ed0566bdcf254fb7a09da25d9735a8c431 Mon Sep 17 00:00:00 2001
From: end-4 <97237370+end-4@users.noreply.github.com>
Date: Sun, 8 Jun 2025 02:10:01 +0200
Subject: [PATCH] script for least busy region of image

---
 .config/matugen/scripts/least_busy_region.py | 253 +++++++++++++++++++
 scriptdata/requirements.in                   |   1 +
 scriptdata/requirements.txt                  |   8 +-
 3 files changed, 259 insertions(+), 3 deletions(-)
 create mode 100755 .config/matugen/scripts/least_busy_region.py

diff --git a/.config/matugen/scripts/least_busy_region.py b/.config/matugen/scripts/least_busy_region.py
new file mode 100755
index 000000000..68e08ca12
--- /dev/null
+++ b/.config/matugen/scripts/least_busy_region.py
@@ -0,0 +1,253 @@
+#!/usr/bin/env -S\_/bin/sh\_-c\_"source\_\$(eval\_echo\_\$ILLOGICAL_IMPULSE_VIRTUAL_ENV)/bin/activate&&exec\_python\_-E\_"\$0"\_"\$@""
+# Disclaimer: This script is vibe-coded.
+
+import os
+os.environ["OPENCV_LOG_LEVEL"] = "SILENT"
+import cv2
+import numpy as np
+import argparse
+import json
+
+def find_least_busy_region(image_path, region_width=300, region_height=200, screen_width=None, screen_height=None, verbose=False, stride=2, screen_mode="fill"):
+    img = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
+    if img is None:
+        raise FileNotFoundError(f"Image not found: {image_path}")
+    orig_h, orig_w = img.shape
+    scale = 1.0
+    if screen_width is not None and screen_height is not None:
+        scale_w = screen_width / orig_w
+        scale_h = screen_height / orig_h
+        if screen_mode == "fill":
+            scale = max(scale_w, scale_h)
+        else:
+            scale = min(scale_w, scale_h)
+        new_w = int(orig_w * scale)
+        new_h = int(orig_h * scale)
+        if verbose:
+            print(f"Scaling image from {orig_w}x{orig_h} to {new_w}x{new_h} (scale: {scale:.3f}, mode: {screen_mode})")
+        img = cv2.resize(img, (new_w, new_h), interpolation=cv2.INTER_LANCZOS4)
+    else:
+        if verbose:
+            print(f"Using original image size: {orig_w}x{orig_h}")
+    arr = img.astype(np.float64)
+    h, w = arr.shape
+    # Use OpenCV's integral for fast computation
+    integral = cv2.integral(arr, sdepth=cv2.CV_64F)[1:,1:]
+    integral_sq = cv2.integral(arr**2, sdepth=cv2.CV_64F)[1:,1:]
+    def region_sum(ii, x1, y1, x2, y2):
+        total = ii[y2, x2]
+        if x1 > 0:
+            total -= ii[y2, x1-1]
+        if y1 > 0:
+            total -= ii[y1-1, x2]
+        if x1 > 0 and y1 > 0:
+            total += ii[y1-1, x1-1]
+        return total
+    min_var = None
+    min_coords = (0, 0)
+    area = region_width * region_height
+    for y in range(0, h - region_height + 1, stride):
+        for x in range(0, w - region_width + 1, stride):
+            x1, y1 = x, y
+            x2, y2 = x + region_width - 1, y + region_height - 1
+            s = region_sum(integral, x1, y1, x2, y2)
+            s2 = region_sum(integral_sq, x1, y1, x2, y2)
+            mean = s / area
+            var = (s2 / area) - (mean ** 2)
+            if (min_var is None) or (var < min_var):
+                min_var = var
+                min_coords = (x, y)
+    return min_coords, min_var
+
+def find_largest_region(image_path, screen_width=None, screen_height=None, verbose=False, stride=2, screen_mode="fill", threshold=100.0, aspect_ratio=1.0):
+    img = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
+    if img is None:
+        raise FileNotFoundError(f"Image not found: {image_path}")
+    orig_h, orig_w = img.shape
+    scale = 1.0
+    if screen_width is not None and screen_height is not None:
+        scale_w = screen_width / orig_w
+        scale_h = screen_height / orig_h
+        if screen_mode == "fill":
+            scale = max(scale_w, scale_h)
+        else:
+            scale = min(scale_w, scale_h)
+        new_w = int(orig_w * scale)
+        new_h = int(orig_h * scale)
+        if verbose:
+            print(f"Scaling image from {orig_w}x{orig_h} to {new_w}x{new_h} (scale: {scale:.3f}, mode: {screen_mode})")
+        img = cv2.resize(img, (new_w, new_h), interpolation=cv2.INTER_LANCZOS4)
+    else:
+        if verbose:
+            print(f"Using original image size: {orig_w}x{orig_h}")
+    arr = img.astype(np.float64)
+    h, w = arr.shape
+    # Use OpenCV's integral for fast computation
+    integral = cv2.integral(arr, sdepth=cv2.CV_64F)[1:,1:]
+    integral_sq = cv2.integral(arr**2, sdepth=cv2.CV_64F)[1:,1:]
+    def region_sum(ii, x1, y1, x2, y2):
+        total = ii[y2, x2]
+        if x1 > 0:
+            total -= ii[y2, x1-1]
+        if y1 > 0:
+            total -= ii[y1-1, x2]
+        if x1 > 0 and y1 > 0:
+            total += ii[y1-1, x1-1]
+        return total
+    min_size = 10
+    max_size = min(h, int(w / aspect_ratio)) if aspect_ratio >= 1.0 else min(int(h * aspect_ratio), w)
+    best = None
+    best_size = min_size
+    while min_size <= max_size:
+        mid = (min_size + max_size) // 2
+        if aspect_ratio >= 1.0:
+            region_h = mid
+            region_w = int(mid * aspect_ratio)
+        else:
+            region_w = mid
+            region_h = int(mid / aspect_ratio)
+        if region_w > w or region_h > h:
+            max_size = mid - 1
+            continue
+        found = False
+        for y in range(0, h - region_h + 1, stride):
+            for x in range(0, w - region_w + 1, stride):
+                x1, y1 = x, y
+                x2, y2 = x + region_w - 1, y + region_h - 1
+                s = region_sum(integral, x1, y1, x2, y2)
+                s2 = region_sum(integral_sq, x1, y1, x2, y2)
+                area = region_w * region_h
+                mean = s / area
+                var = (s2 / area) - (mean ** 2)
+                if var <= threshold:
+                    found = True
+                    best = (x, y, region_w, region_h, var)
+                    break
+            if found:
+                break
+        if found:
+            best_size = mid
+            min_size = mid + 1
+        else:
+            max_size = mid - 1
+    if best:
+        x, y, region_w, region_h, var = best
+        center_x = x + region_w // 2
+        center_y = y + region_h // 2
+        return (center_x, center_y), (region_w, region_h), var
+    else:
+        return None, (0, 0), None
+
+def draw_region(image_path, coords, region_width=300, region_height=200, output_path='output.png', screen_width=None, screen_height=None, screen_mode="fill"):
+    img = cv2.imread(image_path)
+    if img is None:
+        raise FileNotFoundError(f"Image not found: {image_path}")
+    orig_h, orig_w = img.shape[:2]
+    if screen_width is not None and screen_height is not None:
+        scale_w = screen_width / orig_w
+        scale_h = screen_height / orig_h
+        if screen_mode == "fill":
+            scale = max(scale_w, scale_h)
+        else:
+            scale = min(scale_w, scale_h)
+        new_w = int(orig_w * scale)
+        new_h = int(orig_h * scale)
+        img = cv2.resize(img, (new_w, new_h), interpolation=cv2.INTER_LANCZOS4)
+    x, y = coords
+    cv2.rectangle(img, (x, y), (x+region_width-1, y+region_height-1), (0,0,255), 3)
+    cv2.imwrite(output_path, img)
+    print(f"Saved output image with rectangle at {output_path}")
+
+def draw_largest_region(image_path, center, size, output_path='output.png', screen_width=None, screen_height=None, screen_mode="fill"):
+    img = cv2.imread(image_path)
+    if img is None:
+        raise FileNotFoundError(f"Image not found: {image_path}")
+    orig_h, orig_w = img.shape[:2]
+    if screen_width is not None and screen_height is not None:
+        scale_w = screen_width / orig_w
+        scale_h = screen_height / orig_h
+        if screen_mode == "fill":
+            scale = max(scale_w, scale_h)
+        else:
+            scale = min(scale_w, scale_h)
+        new_w = int(orig_w * scale)
+        new_h = int(orig_h * scale)
+        img = cv2.resize(img, (new_w, new_h), interpolation=cv2.INTER_LANCZOS4)
+    cx, cy = center
+    region_w, region_h = size
+    x1 = cx - region_w // 2
+    y1 = cy - region_h // 2
+    x2 = cx + region_w // 2 - 1
+    y2 = cy + region_h // 2 - 1
+    cv2.rectangle(img, (x1, y1), (x2, y2), (255,0,0), 3)
+    cv2.imwrite(output_path, img)
+    print(f"Saved output image with largest region at {output_path}")
+
+def main():
+    parser = argparse.ArgumentParser(description="Find least busy region in an image and output a JSON. Made for determining a suitable position for a wallpaper widget.")
+    parser.add_argument("image_path", help="Path to the input image")
+    parser.add_argument("--width", type=int, default=500, help="Region width")
+    parser.add_argument("--height", type=int, default=250, help="Region height")
+    parser.add_argument("-v", "--visual-output", action="store_true", help="Output image with rectangle")
+    parser.add_argument("--screen-width", type=int, default=1920, help="Screen width for wallpaper scaling")
+    parser.add_argument("--screen-height", type=int, default=1080, help="Screen height for wallpaper scaling")
+    parser.add_argument("--stride", type=int, default=4, help="Step size for sliding window (higher is faster, less precise)")
+    parser.add_argument("--screen-mode", choices=["fill", "fit"], default="fill", help="Wallpaper scaling mode: 'fill' (default) or 'fit'")
+    parser.add_argument("--verbose", action="store_true", help="Print verbose output")
+    parser.add_argument("-l", "--largest-region", action="store_true", help="Find the largest region under the variance threshold and output its center")
+    parser.add_argument("-t", "--variance-threshold", type=float, default=1000.0, help="Variance threshold for largest region mode")
+    parser.add_argument("--aspect-ratio", type=float, default=1.0, help="Aspect ratio (width/height) for largest region mode")
+    args = parser.parse_args()
+
+    if args.largest_region:
+        center, size, var = find_largest_region(
+            args.image_path,
+            screen_width=args.screen_width,
+            screen_height=args.screen_height,
+            verbose=args.verbose,
+            stride=args.stride,
+            screen_mode=args.screen_mode,
+            threshold=args.variance_threshold,
+            aspect_ratio=args.aspect_ratio
+        )
+        if center:
+            if args.visual_output:
+                draw_largest_region(args.image_path, center, size, screen_width=args.screen_width, screen_height=args.screen_height, screen_mode=args.screen_mode)
+            # Output JSON
+            print(json.dumps({
+                "center_x": center[0],
+                "center_y": center[1],
+                "width": size[0],
+                "height": size[1],
+                "variance": var
+            }))
+        else:
+            print(json.dumps({"error": "No region found under the threshold."}))
+        return
+
+    coords, variance = find_least_busy_region(
+        args.image_path,
+        region_width=args.width,
+        region_height=args.height,
+        screen_width=args.screen_width,
+        screen_height=args.screen_height,
+        verbose=args.verbose,
+        stride=args.stride,
+        screen_mode=args.screen_mode
+    )
+    if args.visual_output:
+        draw_region(args.image_path, coords, region_width=args.width, region_height=args.height, screen_width=args.screen_width, screen_height=args.screen_height, screen_mode=args.screen_mode)
+    # Output JSON with center point
+    center_x = coords[0] + args.width // 2
+    center_y = coords[1] + args.height // 2
+    print(json.dumps({
+        "center_x": center_x,
+        "center_y": center_y,
+        "width": args.width,
+        "height": args.height,
+        "variance": variance
+    }))
+
+if __name__ == "__main__":
+    main()
+
diff --git a/scriptdata/requirements.in b/scriptdata/requirements.in
index 0b4ac323e..f312b7f15 100644
--- a/scriptdata/requirements.in
+++ b/scriptdata/requirements.in
@@ -8,3 +8,4 @@ materialyoucolor
 libsass
 material-color-utilities
 setproctitle
+opencv-python
diff --git a/scriptdata/requirements.txt b/scriptdata/requirements.txt
index 802304132..a710f483a 100644
--- a/scriptdata/requirements.txt
+++ b/scriptdata/requirements.txt
@@ -11,7 +11,11 @@ material-color-utilities==0.2.1
 materialyoucolor==2.0.10
     # via -r scriptdata/requirements.in
 numpy==2.2.2
-    # via material-color-utilities
+    # via
+    #   material-color-utilities
+    #   opencv-python
+opencv-python==4.11.0.86
+    # via -r scriptdata/requirements.in
 packaging==24.2
     # via
     #   build
@@ -26,8 +30,6 @@ pycparser==2.22
     # via cffi
 pyproject-hooks==1.2.0
     # via build
-# pywal==3.3.0
-    # via -r scriptdata/requirements.in
 pywayland==0.4.18
     # via -r scriptdata/requirements.in
 setproctitle==1.3.4