update the tactile graphics

app.py

@@ -0,0 +1,70 @@
+import gradio as gr
+
+import kornia as K
+from kornia.core import Tensor
+
+def edge_detection(filepath, detector): 
+
+    img: Tensor = K.io.load_image(filepath, K.io.ImageLoadType.RGB32)    
+    img = img[None]
+
+    x_gray = K.color.rgb_to_grayscale(img)
+    
+
+    if detector == '1st order derivates in x':
+        grads: Tensor = K.filters.spatial_gradient(x_gray, order=1) 
+        grads_x = grads[:, :, 0]
+        grads_y = grads[:, :, 1]
+        
+        output = K.utils.tensor_to_image(1. - grads_x.clamp(0., 1.))
+    
+    elif detector == '1st order derivates in y':
+        grads: Tensor = K.filters.spatial_gradient(x_gray, order=1)
+        grads_x = grads[:, :, 0]
+        grads_y = grads[:, :, 1]
+        
+        output = K.utils.tensor_to_image(1. - grads_y.clamp(0., 1.))
+        
+    elif detector == '2nd order derivatives in x':
+        grads: Tensor = K.filters.spatial_gradient(x_gray, order=2) 
+        grads_x = grads[:, :, 0]
+        grads_y = grads[:, :, 1]
+        
+        output = K.utils.tensor_to_image(1. - grads_x.clamp(0., 1.))
+        
+    elif detector == '2nd order derivatives in y':
+        grads: Tensor = K.filters.spatial_gradient(x_gray, order=2)
+        grads_x = grads[:, :, 0]
+        grads_y = grads[:, :, 1]
+        
+        output = K.utils.tensor_to_image(1. - grads_y.clamp(0., 1.))
+        
+    elif detector == 'Sobel':
+        x_sobel: Tensor = K.filters.sobel(x_gray)
+        output = K.utils.tensor_to_image(1. - x_sobel)
+
+    elif detector == 'Laplacian':
+        x_laplacian: Tensor = K.filters.laplacian(x_gray, kernel_size=5)
+        output = K.utils.tensor_to_image(1. - x_laplacian.clamp(0., 1.))
+
+    else:
+        x_canny: Tensor = K.filters.canny(x_gray)[0]
+        output = K.utils.tensor_to_image(1. - x_canny.clamp(0., 1.0))
+
+    return output
+    
+title = "Tactile Graphic Generator"
+description = "<p style='text-align: center'>To use it, simply upload your image. Press Enter, them click on the tactile graphic to download.</p>"
+
+iface = gr.Interface(edge_detection, 
+            [
+            	gr.Image(type="filepath"),
+	            gr.Dropdown(choices=["1st order derivates in x", "1st order derivates in y", "2nd order derivatives in x", "2nd order derivatives in y", "Sobel", "Laplacian", "Canny"])
+            ],
+            "image",
+            title=title,
+            description=description,
+            
+)
+
+iface.launch()

requirements.txt

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+kornia
+kornia_rs
+opencv-python
+torch