update files

app.py

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+import gradio as gr
+
+import kornia as K
+from kornia.core import Tensor
+
+
+def load_img(file):
+    # load the image using the rust backend
+    img_bgr: Tensor = K.io.load_image(file.name, K.io.ImageLoadType.RGB32)
+    img_bgr = img_bgr[None, ...].float() / 255.0
+
+    img_rgb: Tensor = K.color.bgr_to_rgb(img_bgr)
+    img_gray = K.color.rgb_to_grayscale(img_rgb)
+
+    return img_gray
+
+
+def canny_edge_detector(file):
+    x_gray = load_img(file)
+    x_canny: Tensor = K.filters.canny(x_gray)[0]
+    img_out = 1.0 - x_canny.clamp(0.0, 1.0)
+    return K.utils.tensor_to_image(img_out)
+
+
+def sobel_edge_detector(file):
+    x_gray = load_img(file)
+    x_sobel: Tensor = K.filters.sobel(x_gray)
+    img_out = 1.0 - x_sobel
+    return K.utils.tensor_to_image(img_out)
+
+
+def simple_edge_detector(file, order=1, dir="x"):
+    x_gray = load_img(file)
+    grads: Tensor = K.filters.spatial_gradient(x_gray, order=2)  # BxCx2xHxW
+    grads_x = grads[:, :, 0]
+    grads_y = grads[:, :, 1]
+    if dir == "x":
+        img_out = 1.0 - grads_x.clamp(0.0, 1.0)
+    else:
+        img_out = 1.0 - grads_y.clamp(0.0, 1.0)
+    return K.utils.tensor_to_image(img_out)
+
+
+def laplacian_edge_detector(file, kernel_size=5):
+    x_gray = load_img(file)
+    x_canny: Tensor = K.filters.canny(x_gray)[0]
+    img_out = 1.0 - x_canny.clamp(0.0, 1.0)
+    return K.utils.tensor_to_image(img_out)
+
+
+examples = [
+    ["examples/doraemon.jpg"],
+]
+
+title = "Kornia Edge Detector"
+description = "<p style='text-align: center'>This is a Gradio demo for Kornia's Edge Detector.</p><p style='text-align: center'>To use it, simply upload your image, or click one of the examples to load them, and use the sliders to enhance! Read more at the links at the bottom.</p>"
+article = "<p style='text-align: center'><a href='https://kornia.readthedocs.io/en/latest/' target='_blank'>Kornia Docs</a> | <a href='https://github.com/kornia/kornia' target='_blank'>Kornia Github Repo</a> | <a href='https://kornia-tutorials.readthedocs.io/en/latest/image_enhancement.html' target='_blank'>Kornia Enhancements Tutorial</a></p>"
+
+
+def change_kernel(choice):
+    if choice == "Laplacian":
+        return gr.update(visible=True)
+    else:
+        return gr.update(visible=False)
+
+
+def change_order(choice):
+    if choice == "simple":
+        return gr.update(visible=True)
+    else:
+        return gr.update(visible=False)
+
+
+def change_button(choice):
+    if choice == "simple":
+        return gr.Button("Detect").click(
+            canny_edge_detector, inputs=image_input, outputs=image_output
+        )
+    elif choice == "sobel":
+        return gr.Button("Detect").click(
+            sobel_edge_detector, inputs=image_input, outputs=image_output
+        )
+    elif choice == "laplacian":
+        return gr.Button("Detect").click(
+            laplacian_edge_detector, inputs=image_input, outputs=image_output
+        )
+    else:
+        return gr.Button("Detect").click(
+            simple_edge_detector, inputs=image_input, outputs=image_output
+        )
+
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        image_input = gr.Image()
+        image_output = gr.Image()
+        radio = gr.Radio(
+            ["canny", "simple", "sobel", "laplacian"],
+            label="Essay Length to Write?",
+        )
+        kernel = gr.Slider(
+            minimum=1,
+            maximum=6,
+            step=1,
+            default=5,
+            label="kernel_size",
+            visible=False,
+        )
+        order = gr.Slider(
+            minimum=1,
+            maximum=2,
+            step=1,
+            default=1,
+            label="Derivative order",
+            visible=False,
+        )
+        Button = gr.Button("Detect")
+
+        radio.change(fn=change_kernel, inputs=radio, outputs=kernel)
+        radio.change(fn=change_order, inputs=radio, outputs=order)
+        radio.change(fn=change_button, inputs=radio, outputs=Button)
+
+
+demo.launch()

requirements.txt

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+kornia
+kornia_rs
+opencv-python
+torch