Apply python black style 🎱

Author: Mamdasn

code-example/test_image_im2dhisteq.py

@@ -1,9 +1,9 @@
 from im2dhisteq import im2dhisteq
-import numpy as np 
+import numpy as np
 import cv2
 import os
 
-filename = 'assets/cloudy-day-500.jpg'
+filename = "assets/cloudy-day-500.jpg"
 
 name, ext = os.path.splitext(filename)
 image = cv2.imread(filename)
@@ -19,6 +19,5 @@
 image_hsv[:, :, 2] = image_v_heq.copy()
 image_heq = cv2.cvtColor(image_hsv, cv2.COLOR_HSV2BGR)
 
-cv2.imwrite(f'{name}-im2dhisteq{ext}', image_2dheq)
-cv2.imwrite(f'{name}-imhisteq{ext}', image_heq)
-
+cv2.imwrite(f"{name}-im2dhisteq{ext}", image_2dheq)
+cv2.imwrite(f"{name}-imhisteq{ext}", image_heq)

code-example/test_video_im2dhisteq.py

@@ -2,23 +2,25 @@
 import cv2
 from im2dhisteq import vid2dhisteq
 
-cap = cv2.VideoCapture('assets/Arctic-Convoy-With-Giant-Mack-Trucks.mp4')
+cap = cv2.VideoCapture("assets/Arctic-Convoy-With-Giant-Mack-Trucks.mp4")
 
 # video without sound
-video_out_name = 'assets/Arctic-Convoy-With-Giant-Mack-Trucks-imWeightedThresholdedheq.mp4'
+video_out_name = (
+    "assets/Arctic-Convoy-With-Giant-Mack-Trucks-imWeightedThresholdedheq.mp4"
+)
 
 i = 0
 j = 0
 length = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
 Wout_list = np.zeros((10))
-while(cap.isOpened()):
+while cap.isOpened():
     ret, frame = cap.read()
     if ret == False:
         break
-    print("\r", 100*i//length, "%", end='')
+    print("\r", 100 * i // length, "%", end="")
 
     frame_hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
-    frame_v   = frame_hsv[:, :, 2].copy()
+    frame_v = frame_hsv[:, :, 2].copy()
     image_heq, Wout = vid2dhisteq(frame_v, Wout_list=Wout_list)
     Wout_list[j] = Wout
     j += 1
@@ -28,19 +30,32 @@
     frame_eq = cv2.cvtColor(frame_hsv, cv2.COLOR_HSV2BGR)
 
     fps = cap.get(cv2.CAP_PROP_FPS)
-    frame = cv2.putText(frame, 'Original', (10, 20), cv2.FONT_HERSHEY_COMPLEX, 
-                   0.5, (255, 255, 255), 1, cv2.LINE_AA)
-    frame_eq = cv2.putText(frame_eq, 'Enhanced', (10, 20), cv2.FONT_HERSHEY_COMPLEX, 
-                   0.5, (255, 255, 255), 1, cv2.LINE_AA)
-    frame_frame_eq = np.concatenate(
-        ( frame, frame_eq ),
-        axis= 1
-        )
-    if i==0:
+    frame = cv2.putText(
+        frame,
+        "Original",
+        (10, 20),
+        cv2.FONT_HERSHEY_COMPLEX,
+        0.5,
+        (255, 255, 255),
+        1,
+        cv2.LINE_AA,
+    )
+    frame_eq = cv2.putText(
+        frame_eq,
+        "Enhanced",
+        (10, 20),
+        cv2.FONT_HERSHEY_COMPLEX,
+        0.5,
+        (255, 255, 255),
+        1,
+        cv2.LINE_AA,
+    )
+    frame_frame_eq = np.concatenate((frame, frame_eq), axis=1)
+    if i == 0:
         h, w, d = frame_frame_eq.shape
-        fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+        fourcc = cv2.VideoWriter_fourcc(*"mp4v")
         video_out = cv2.VideoWriter(video_out_name, fourcc, fps, (w, h))
     video_out.write(frame_frame_eq)
 
-    i+=1
+    i += 1
 cv2.destroyAllWindows()

src/im2dhisteq.py

@@ -1,18 +1,19 @@
 from im2dhist import im2dhist as im2dhist
 from im2dhist import imhist
-import numba 
+import numba
 import numpy as np
 
+
 @numba.njit()
 def im2dhisteq(image, w_neighboring=6):
     V = image.copy()
     [h, w] = V.shape
     V_hist = imhist(V)
     H_in = im2dhist(V, w_neighboring=w_neighboring)
-    CDFx = np.cumsum(np.sum(H_in, axis=0)) # Kx1
+    CDFx = np.cumsum(np.sum(H_in, axis=0))  # Kx1
 
     # normalizes CDFx
-    CDFxn = (255*CDFx/CDFx[-1])
+    CDFxn = 255 * CDFx / CDFx[-1]
 
     PDFxn = np.zeros_like(CDFxn)
     PDFxn[0] = CDFxn[0]
@@ -22,10 +23,11 @@ def im2dhisteq(image, w_neighboring=6):
     X_transform[np.where(V_hist > 0)] = PDFxn.copy()
     CDFxn_transform = np.cumsum(X_transform)
 
-
     bins = np.arange(256)
     # use linear interpolation of cdf to find new pixel values
-    image_equalized = np.floor(np.interp(V.flatten(), bins, CDFxn_transform).reshape(h, w)).astype(np.uint8)
+    image_equalized = np.floor(
+        np.interp(V.flatten(), bins, CDFxn_transform).reshape(h, w)
+    ).astype(np.uint8)
 
     return image_equalized
 
@@ -38,24 +40,24 @@ def vid2dhisteq(image, w_neighboring=6, Wout_list=np.zeros((10), dtype=np.uint16
 
     H_in = im2dhist(V, w_neighboring=6)
 
-    CDFx = np.cumsum(np.sum(H_in, axis=0)) # Kx1
+    CDFx = np.cumsum(np.sum(H_in, axis=0))  # Kx1
 
     # normalizes CDFx
-    CDFxn = (CDFx/CDFx[-1])
+    CDFxn = CDFx / CDFx[-1]
 
     PDFxn = np.zeros_like(CDFxn)
     PDFxn[0] = CDFxn[0]
     PDFxn[1:] = np.diff(CDFxn)
 
-    X_transform = np.zeros((256), dtype=np.float64) 
+    X_transform = np.zeros((256), dtype=np.float64)
     X_transform[V_hist > 0] = PDFxn.copy()
     CDFxn_transform = np.cumsum(X_transform).astype(np.float64)
 
     Win = H_in.shape[0]
-    Gmax = 1.5 # 1.5 .. 2
-    Wout = min(255, Gmax*Win)
-    if np.where(Wout_list>0)[0].size==Wout_list.size:
-        Wout = (np.sum(Wout_list)+Wout) / (1+Wout_list.size)
+    Gmax = 1.5  # 1.5 .. 2
+    Wout = min(255, Gmax * Win)
+    if np.where(Wout_list > 0)[0].size == Wout_list.size:
+        Wout = (np.sum(Wout_list) + Wout) / (1 + Wout_list.size)
 
     F = V.ravel().astype(np.uint16)
     Ftilde = Wout * CDFxn_transform[F]

tests/test_im2dhisteq.py

@@ -2,16 +2,18 @@
 import numpy as np
 import cv2
 
+
 def test_im2dhisteq_with_param():
-    image_name = '../assets/Plane.jpg'
+    image_name = "../assets/Plane.jpg"
     image = cv2.imread(image_name)
     # convert rgb image to gray
     gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-    
+
     gray_image_2DHisteq = im2dhisteq(gray_image, w_neighboring=6)
-    
 
-    #np.save(f'{image_name}-2D-Histogram-Equalized', gray_image_2DHisteq)
-    gray_image_2DHisteq_cmpr = np.load(f'{image_name}-2D-Histogram-Equalized.npy')
+    # np.save(f'{image_name}-2D-Histogram-Equalized', gray_image_2DHisteq)
+    gray_image_2DHisteq_cmpr = np.load(f"{image_name}-2D-Histogram-Equalized.npy")
     assert np.all(gray_image_2DHisteq == gray_image_2DHisteq_cmpr)
-#test_im2dhisteq_with_param()
+
+
+# test_im2dhisteq_with_param()