.

pyvidplayer2/post_processing.py

@@ -0,0 +1,33 @@
+import cv2
+import numpy
+
+
+class PostProcessing:
+    def none(data: numpy.ndarray) -> numpy.ndarray:
+        return data 
+    
+    def blur(data: numpy.ndarray) -> numpy.ndarray:
+        return cv2.blur(data, (5, 5))
+    
+    def sharpen(data: numpy.ndarray) -> numpy.ndarray:
+        return cv2.filter2D(data, -1, numpy.array([[-1,-1,-1], [-1,9,-1], [-1,-1,-1]]))
+    
+    def greyscale(data: numpy.ndarray) -> numpy.ndarray:
+        return numpy.stack((cv2.cvtColor(data, cv2.COLOR_BGR2GRAY),) * 3, axis=-1)
+    
+    def noise(data: numpy.ndarray) -> numpy.ndarray:
+        noise = numpy.zeros(data.shape, dtype=numpy.uint8)
+        cv2.randn(noise, (0,) * 3, (20,) * 3)
+        return data + noise
+    
+    def letterbox(data: numpy.ndarray) -> numpy.ndarray:
+        background = numpy.zeros((*data.shape[:2], 3), dtype=numpy.uint8)
+
+        x1, y1 = 0, int(data.shape[0] * 0.1) #topleft crop
+        x2, y2 = data.shape[1], int(data.shape[0] * 0.9) #bottomright crop
+        data = data[y1:y2, x1:x2] # crops image
+        background[y1:y1 + data.shape[0], x1:x1 + data.shape[1]] = data # draws image onto background
+        return background
+    
+    def cel_shading(data: numpy.ndarray) -> numpy.ndarray:
+        return cv2.subtract(data, cv2.blur(cv2.merge((cv2.Canny(data, 150, 200),) * 3), (2, 2)))