ver. 0.15.10

Author: AnonymousCKNN

npy/files/io.py

@@ -38,6 +38,11 @@ def load_txt(fpath):
         return f.read()
 
 
+def load_txtlines(fpath):
+    with open(fpath, 'r') as f:
+        return [l.strip() for l in f.readlines()]
+
+
 def load_video(fpath):
     vidcap = cv2.VideoCapture(fpath)
 

npy/image/__init__.py

@@ -4,3 +4,4 @@
 from .modify import *
 from .miscs import *
 from . import augment
+from .bbox import *

npy/image/bbox.py

@@ -0,0 +1,56 @@
+import math
+
+__all__ = ['pad_bbox', 'square_bbox']
+
+
+def pad_bbox(xyxy, padding_ratio, H, W):
+    x1, y1, x2, y2 = xyxy
+    y1, y2, x1, x2 = int(y1), int(y2), int(x1), int(x2)
+
+    if padding_ratio != 0:
+        bbox_H = y2 - y1
+        bbox_W = x2 - x1
+
+        bbox_Hc = (y2 + y1) / 2
+        bbox_Wc = (x2 + x1) / 2
+
+        bbox_H2 = bbox_H * (1 + padding_ratio) / 2
+        bbox_W2 = bbox_W * (1 + padding_ratio) / 2
+        y1 = bbox_Hc - bbox_H2
+        y2 = bbox_Hc + bbox_H2
+        x1 = bbox_Wc - bbox_W2
+        x2 = bbox_Wc + bbox_W2
+
+        y1, y2, x1, x2 = int(y1), int(y2), int(x1), int(x2)
+        y1 = max(0, y1)
+        x1 = max(0, x1)
+
+        x2 = min(W, x2)
+        y2 = min(H, y2)
+    return x1, y1, x2, y2
+
+
+def square_bbox(xyxy, H, W):
+    x1, y1, x2, y2 = xyxy
+    h, w = y2 - y1, x2 - x1
+    if h > w:
+        c = int(math.ceil((x1 + x2) / 2))
+        x1 = c - h // 2
+        x2 = c + h - h // 2
+        if x1 < 0:
+            x2 -= x1
+            x1 -= x1
+        elif x2 > W:
+            x1 -= (x2 - W)
+            x2 -= (x2 - W)
+    elif w > h:
+        c = int(math.ceil((y1 + y2) / 2))
+        y1 = c - w // 2
+        y2 = c + w - w // 2
+        if y1 < 0:
+            y2 -= y1
+            y1 -= y1
+        elif y2 > H:
+            y1 -= (y2 - H)
+            y2 -= (y2 - H)
+    return x1, y1, x2, y2

npy/utils/utils_primitive/utils_dict.py

@@ -4,7 +4,7 @@
 __all__ = ['keys_d_of_l_of_num', 'keys_d_of_num',
            'append_d_of_l', 'inv_d', 'replace_keys', 'drop_keys',
            'filter_d_of_l_of_num', 'filter_d_of_num', 'filter_keys', 'filter_empty',
-           'dict_eq', 'l_of_dict_eq', 'add_d_of_l'
+           'dict_eq', 'l_of_dict_eq', 'add_d_of_l', 'merge_l_of_d'
            ]
 
 
@@ -62,6 +62,18 @@ def append_d_of_l(d_of_l: dict, d: dict):
     return d_of_l
 
 
+def merge_l_of_d(l_of_d: list) -> dict:
+    if len(l_of_d) == 0:
+        return {}
+
+    keys = list(l_of_d[0].keys())
+    ret = {k: [] for k in keys}
+    for d in l_of_d:
+        for k in keys:
+            ret[k].append(d[k])
+    return ret
+
+
 def add_d_of_l(d_of_l: dict, d_of_l2: dict, reverse=False):
     if d_of_l is None:
         return d_of_l2

npy/utils/utils_primitive/utils_list.py

@@ -2,7 +2,7 @@
 from collections.abc import Iterable
 
 
-__all__ = ['take', 'isarray', 'isnum', 'shuffled']
+__all__ = ['take', 'isarray', 'isnum', 'shuffled', 'normalize_l']
 
 
 def take(l, inds_or_ind):
@@ -28,3 +28,15 @@ def shuffled(x, y=None):
         return take(x, inds)
     else:
         return take(x, inds), take(y, inds)
+
+
+def normalize_l(arr):
+    only_values = arr[~np.isinf(arr)]
+    if len(only_values) == 0:
+        return arr
+    vmax = np.max(only_values)
+    vmin = np.min(only_values)
+    dur = vmax - vmin
+    if dur == 0:
+        dur = 1
+    return (arr - vmin) / dur

setup.py

@@ -10,7 +10,7 @@
 
 setup(name='nuclear-python',
 
-      version='0.15.9',
+      version='0.15.10',
 
       url='https://github.com/nuclearboy95/nuclear-python',