clean up folder

tools/patch_generation/patch_generation.py

@@ -0,0 +1,53 @@
+#%%
+import numpy as np
+import cv2
+
+def generate_color_pattern(h, w, d, r):
+    # Initialize the pattern with zeros
+    pattern = np.zeros((h, w, 3))
+
+    # Calculate the number of patches in each dimension
+    num_patches_x = h // d
+    num_patches_y = w // d
+
+    # Maximum number of attempts to find a suitable color
+    max_attempts = 1000
+
+    # Iterate over the patches
+    for i in range(num_patches_x):
+        for j in range(num_patches_y):
+            # Get the neighbors
+            neighbors = []
+            if i > 0:
+                neighbors.append(pattern[(i-1)*d:i*d, j*d:(j+1)*d])
+            if j > 0:
+                neighbors.append(pattern[i*d:(i+1)*d, (j-1)*d:j*d])
+
+            # Generate a new color
+            for attempt in range(max_attempts):
+                new_color = np.random.rand(3)
+                if all(np.min((new_color - neighbor.mean(axis=(0, 1)))**2) >= r for neighbor in neighbors):
+                    break
+            if attempt == max_attempts - 1:
+                print(f"Warning: Could not find a suitable color for patch ({i}, {j}) after {max_attempts} attempts")
+
+            # Apply the new color to the patch
+            pattern[i*d:(i+1)*d, j*d:(j+1)*d] = new_color
+
+            print('Patch ({}, {})'.format(i, j))
+
+    return pattern
+
+# Test the function
+pattern = generate_color_pattern(162, 162, 3, 0.75)
+
+# Convert the pattern to a format suitable for display with OpenCV
+pattern_display = (pattern * 255).astype(np.uint8)
+
+# # Display the pattern
+# cv2.imshow('Pattern', pattern_display)
+# cv2.waitKey(0)
+# cv2.destroyAllWindows()
+
+# #%%
+cv2.imwrite('color_pattern.png', pattern_display)