feat: core hashers

src/arcaea_offline_ocr/core/hashers/__init__.py

@@ -0,0 +1,3 @@
+from .index import average, dct, difference
+
+__all__ = ["average", "dct", "difference"]

src/arcaea_offline_ocr/core/hashers/_common.py

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+import cv2
+
+from arcaea_offline_ocr.types import Mat
+
+
+def _resize_image(src: Mat, dsize: ...) -> Mat:
+    return cv2.resize(src, dsize, fx=0, fy=0, interpolation=cv2.INTER_AREA)

src/arcaea_offline_ocr/core/hashers/index.py

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+import cv2
+import numpy as np
+
+from arcaea_offline_ocr.types import Mat
+
+from ._common import _resize_image
+
+
+def average(img_gray: Mat, hash_size: int) -> Mat:
+    img_resized = _resize_image(img_gray, (hash_size, hash_size))
+    diff = img_resized > img_resized.mean()
+    return diff.flatten()
+
+
+def difference(img_gray: Mat, hash_size: int) -> Mat:
+    img_size = (hash_size + 1, hash_size)
+    img_resized = _resize_image(img_gray, img_size)
+
+    previous = img_resized[:, :-1]
+    current = img_resized[:, 1:]
+    diff = previous > current
+    return diff.flatten()
+
+
+def dct(img_gray: Mat, hash_size: int = 16, high_freq_factor: int = 4) -> Mat:
+    # TODO: consistency?
+    img_size_base = hash_size * high_freq_factor
+    img_size = (img_size_base, img_size_base)
+
+    img_resized = _resize_image(img_gray, img_size)
+    img_resized = img_resized.astype(np.float32)
+    dct_mat = cv2.dct(img_resized)
+
+    hash_mat = dct_mat[:hash_size, :hash_size]
+    return hash_mat > hash_mat.mean()