base code for pytorch distributed, add cyclegan

tool/img2skeleton.py

@@ -0,0 +1,41 @@
+from pathlib import Path
+import fire
+import cv2
+import numpy as np
+from tqdm import tqdm
+
+
+def xDoG(img, sigma, k_sigma, p, epsilon, phi):
+    sigma_large = sigma * k_sigma
+    sharped_img = (1 + p) * cv2.GaussianBlur(img, (0, 0), sigma) - p * cv2.GaussianBlur(img, (0, 0), sigma_large)
+    img = np.multiply(img, sharped_img)
+
+    t = np.zeros(img.shape)
+    t[img >= epsilon] = 1.0
+    img_dark_indices = img < epsilon
+    t[img_dark_indices] = 1.0 + np.tanh(phi * (img[img_dark_indices] - epsilon))
+
+    return t * 256
+
+
+def transform_single(origin, to, anime: bool = True):
+    img = cv2.imread(str(origin), cv2.IMREAD_GRAYSCALE)
+    if anime:
+        r = xDoG(img / 256, 0.3, 4.5, 19, 0.01, 10 ^ 8 * 2)
+    else:
+        r = xDoG(img / 256, 0.7, 5, 20, 0.02, 10 ^ 8 * 2)
+    cv2.imwrite(str(to), r)
+
+
+def transform(origin, to, anime=True):
+    origin = Path(origin)
+    to = Path(to)
+    if origin.is_dir() and to.is_dir():
+        for f in tqdm(origin.glob("*")):
+            transform_single(f, to / f.name, anime)
+    elif origin.is_file():
+        transform_single(origin, to, anime)
+
+
+if __name__ == '__main__':
+    fire.Fire(transform)