[example] Add circle-packing example (#6870)

This PR adds a new example.


![Figure_1](https://user-images.githubusercontent.com/23307174/206941350-03f6b7f6-9d6c-44a3-9f29-ea44aff229a9.png)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

.gitignore

@@ -58,6 +58,7 @@ __pycache__
 !docs/**/*.jpg
 !docs/**/*.png
 !tests/python/expected/*.png
+!python/taichi/examples/algorithm/circle-packing/*.png
 *.egg-info
 .tlang_cache
 /taichi/common/version.h

python/taichi/examples/algorithm/circle-packing/circle_packing_image.py

@@ -0,0 +1,133 @@
+"""
+Given an input image, redraw it with circle packings.
+"""
+try:
+    import cairocffi as cairo
+    import cv2
+except:
+    raise ImportError(
+        "This example depends on opencv and cairocffi, please run 'pip install opencv-python cairocffi' to install."
+    )
+
+import os
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+import taichi as ti
+
+ti.init(arch=ti.cpu)
+
+_internal_scale = 5  # internally we need a large image to paint
+
+
+@ti.dataclass
+class Circle:
+    x: int
+    y: int
+    r: int
+
+
+circles = Circle.field()  # pylint: disable=no-member
+ti.root.dynamic(ti.i, 100000, chunk_size=64).place(circles)
+
+
+def load_image(imgfile):
+    image = cv2.imread(imgfile)
+    h, w = image.shape[:2]
+    image = cv2.resize(image,
+                       (int(_internal_scale * w), int(_internal_scale * h)),
+                       interpolation=cv2.INTER_AREA)
+    return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+
+
+def get_dist_transform_image(image):
+    canny = cv2.Canny(image, 100, 200)
+    edges_inv = 255 - canny
+    dist_image = cv2.distanceTransform(edges_inv, cv2.DIST_L2, 0)
+    return dist_image
+
+
+@ti.kernel
+def add_new_circles(filled: ti.types.ndarray(), dist_image: ti.types.ndarray(),
+                    min_radius: int, max_radius: int) -> int:
+    H, W = dist_image.shape[0], dist_image.shape[1]
+    ti.loop_config(serialize=True)
+    for x in range(min_radius, W - min_radius):
+        for y in range(min_radius, H - min_radius):
+            valid = True
+            if dist_image[y, x] > min_radius:
+                r = int((dist_image[y, x] + 1) / 2)
+                r = ti.min(r, max_radius)
+                if not filled[y, x] and r <= x < W - r and r <= y < H - r:
+                    for ii in range(x - r, x + r + 1):
+                        for jj in range(y - r, y + r + 1):
+                            if (ii - x)**2 + (jj - y)**2 < (r + 1)**2:
+                                if filled[jj, ii]:
+                                    valid = False
+                                    break
+                        if not valid:
+                            break
+
+                    if valid:
+                        circles.append(Circle(x, y, r))
+                        for ii in range(x - r, x + r + 1):
+                            for jj in range(y - r, y + r + 1):
+                                if (ii - x)**2 + (jj - y)**2 < (r + 1)**2:
+                                    filled[jj, ii] = 1
+
+    return circles.length()
+
+
+def plot_cirlces(image, ctx, n):
+    for i in range(n):
+        c = circles[i]
+        fc = image[c.y, c.x] / 255
+        if all(fc < 0.1):
+            ec = (0.5, 0.5, 0.5)
+        else:
+            ec = (0, 0, 0)
+        ctx.arc(c.x, c.y, c.r, 0, 2 * np.pi)
+        ctx.set_source_rgb(*fc)
+        ctx.fill_preserve()
+        ctx.set_source_rgba(*ec)
+        ctx.stroke()
+
+
+def process(imgfile, scale):
+    image = load_image(imgfile)
+    dist_image = get_dist_transform_image(image)
+    image = cv2.GaussianBlur(image, (5, 5), 0)
+    H, W = image.shape[:2]
+    surface = cairo.ImageSurface(cairo.FORMAT_RGB24, W, H)
+    ctx = cairo.Context(surface)
+    ctx.set_source_rgb(0, 0, 0)
+    ctx.paint()
+
+    filled = np.zeros([H, W], dtype=np.int32)
+    R = [150, 120, 100, 80, 50, 30, 25, 20, 15, 10, 7, 5, 3, 2]
+    for i in range(1, len(R)):
+        n = add_new_circles(filled, dist_image, R[i], R[i - 1])
+
+    ctx.set_line_width(1)
+    plot_cirlces(image, ctx, n)
+    data = surface.get_data()
+    result = np.frombuffer(data, dtype=np.uint8).reshape(H, W, 4)
+    w = int(W / _internal_scale * scale)
+    h = int(H / _internal_scale * scale)
+    result = cv2.resize(result, (w, h), interpolation=cv2.INTER_CUBIC)
+    plt.tight_layout()
+    plt.axis('off')
+    plt.imshow(result)
+    plt.show()
+
+
+def main(imgfile=None, scale=2):
+    if imgfile is None:
+        imgfile = os.path.join(os.path.dirname(os.path.realpath(__file__)),
+                               'taichi_logo.png')
+    process(imgfile, scale)
+
+
+if __name__ == '__main__':
+    main()

requirements_dev.txt

@@ -17,3 +17,5 @@ pre-commit
 scikit-build
 numpy
 ninja; platform_system != 'Windows'
+cairocffi
+opencv-python