@@ -51,7 +51,7 @@ image_np = np.array(input_image)
5151image_GrayScale = image_np[:, :, 0 ] * 0.299 + image_np[:, :, 1 ] * 0.587 + image_np[:, :, 2 ] * 0.114
5252```
5353
54- Setting Hyperparameters and applying Pad frame for input image.
54+ Setting Hyperparameters and applying ** Pad frame** for input image.
5555<br />Consider following part of the code:
5656
5757``` py
@@ -82,7 +82,7 @@ filter_2 = np.array([[0, 1, 0], [1, -4, 1], [0, 1, 0]])
8282filter_3 = np.array([[- 1 , - 1 , - 1 ], [- 1 , 8 , - 1 ], [- 1 , - 1 , - 1 ]])
8383```
8484
85- Creating function to delete negative values from resulted image.
85+ Creating function to ** delete negative values** from resulted image, also known as ** ReLU function ** .
8686<br />Consider following part of the code:
8787
8888``` py
@@ -97,7 +97,7 @@ def relu(array):
9797 return result
9898```
9999
100- Creating function to delete values that are more than 255.
100+ Creating function to ** delete values that are more than 255** .
101101<br />Consider following part of the code:
102102
103103``` py
@@ -115,7 +115,7 @@ def image_pixels(array):
115115 return result
116116```
117117
118- Implementing filtering for ** Edge Detection** also known as ** Convolution Operation** .
118+ Implementing filtering for ** Edge Detection** , also known as ** Convolution Operation** .
119119<br />Consider following part of the code:
120120
121121``` py
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