move files

src/editor/histogram_transfer/regrain.py

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+from scipy.ndimage import zoom
+import numpy as np
+
+
+NBITS = [4, 16, 32, 64, 64, 64]
+
+
+def regrain(img_arr_in, img_arr_col, smoothness: float = 1):
+    """keep gradient of img_arr_in and color of img_arr_col."""
+
+    img_arr_in = img_arr_in / 255.0
+    img_arr_col = img_arr_col / 255.0
+    img_arr_out = np.array(img_arr_in)
+    img_arr_out = _regrain_rec(
+        img_arr_out, img_arr_in, img_arr_col, NBITS, 0, smoothness
+    )
+    img_arr_out[img_arr_out < 0] = 0
+    img_arr_out[img_arr_out > 1] = 1
+    img_arr_out = (255.0 * img_arr_out).astype("uint8")
+    return img_arr_out
+
+
+def _regrain_rec(img_arr_out, img_arr_in, img_arr_col, nbits, level, smoothness):
+    [h, w, _] = img_arr_in.shape
+    h2 = (h + 1) // 2
+    w2 = (w + 1) // 2
+    if len(nbits) > 1 and h2 > 20 and w2 > 20:
+        resize_arr_in = _resize_image(img_arr_in, w2, h2)
+        resize_arr_col = _resize_image(img_arr_col, w2, h2)
+        resize_arr_out = _resize_image(img_arr_out, w2, h2)
+        resize_arr_out = _regrain_rec(
+            resize_arr_out,
+            resize_arr_in,
+            resize_arr_col,
+            nbits[1:],
+            level + 1,
+            smoothness,
+        )
+        img_arr_out = _resize_image(resize_arr_out, w, h)
+    img_arr_out = _solve(
+        img_arr_out, img_arr_in, img_arr_col, nbits[0], level, smoothness
+    )
+    return img_arr_out
+
+
+def _solve(img_arr_out, img_arr_in, img_arr_col, nbit, level, smoothness):
+    [width, height, c] = img_arr_in.shape
+    first_pad_0 = lambda arr: np.concatenate((arr[:1, :], arr[:-1, :]), axis=0)
+    first_pad_1 = lambda arr: np.concatenate((arr[:, :1], arr[:, :-1]), axis=1)
+    last_pad_0 = lambda arr: np.concatenate((arr[1:, :], arr[-1:, :]), axis=0)
+    last_pad_1 = lambda arr: np.concatenate((arr[:, 1:], arr[:, -1:]), axis=1)
+
+    delta_x = last_pad_1(img_arr_in) - first_pad_1(img_arr_in)
+    delta_y = last_pad_0(img_arr_in) - first_pad_0(img_arr_in)
+    delta = np.sqrt((delta_x**2 + delta_y**2).sum(axis=2, keepdims=True))
+
+    psi = 256 * delta / 5
+    psi[psi > 1] = 1
+    phi = 30 * 2 ** (-level) / (1 + 10 * delta / smoothness)
+
+    phi1 = (last_pad_1(phi) + phi) / 2
+    phi2 = (last_pad_0(phi) + phi) / 2
+    phi3 = (first_pad_1(phi) + phi) / 2
+    phi4 = (first_pad_0(phi) + phi) / 2
+
+    rho = 1 / 5.0
+    for i in range(nbit):
+        den = psi + phi1 + phi2 + phi3 + phi4
+        num = (
+            np.tile(psi, [1, 1, c]) * img_arr_col
+            + np.tile(phi1, [1, 1, c])
+            * (last_pad_1(img_arr_out) - last_pad_1(img_arr_in) + img_arr_in)
+            + np.tile(phi2, [1, 1, c])
+            * (last_pad_0(img_arr_out) - last_pad_0(img_arr_in) + img_arr_in)
+            + np.tile(phi3, [1, 1, c])
+            * (first_pad_1(img_arr_out) - first_pad_1(img_arr_in) + img_arr_in)
+            + np.tile(phi4, [1, 1, c])
+            * (first_pad_0(img_arr_out) - first_pad_0(img_arr_in) + img_arr_in)
+        )
+        img_arr_out = (
+            num / np.tile(den + 1e-6, [1, 1, c]) * (1 - rho) + rho * img_arr_out
+        )
+    return img_arr_out
+
+
+def _resize_image(data, target_width, target_height):
+    return zoom(data, (target_height / data.shape[0], target_width / data.shape[1], 1))