Add application file

app.py

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+import gradio as gr
+import kornia as K
+import numpy as np
+import kornia.geometry as KG
+import torch
+import cv2
+
+def geometry_transform(images: list,
+                       translation: float,
+                       scale: float,
+                       angle: float) -> np.ndarray:
+
+    file_names: list = [f.name for f in images]
+    image_list: list = [K.io.load_image(f, K.io.ImageLoadType(0)).float().unsqueeze(0)/255 for f in file_names]
+    image_batch: torch.Tensor = torch.cat(image_list, 0)
+    center: torch.Tensor = torch.tensor([x.shape[1:] for x in image_batch])/2
+    translation = torch.tensor(translation).repeat(len(image_list), 2)
+    scale = torch.tensor(scale).repeat(len(image_list), 2)
+    angle = torch.tensor(angle).repeat(len(image_list))
+    affine_matrix: torch.Tensor = KG.get_affine_matrix2d(translation, center, scale, angle)
+
+    transformed: torch.Tensor = KG.transform.warp_affine(image_batch, affine_matrix[:, :2], dsize=image_batch.shape[2:])
+    np_images: list = [K.tensor_to_image(f*255).astype(np.uint8) for f in transformed]
+    final_images: np.ndarray = cv2.hconcat(np_images)
+
+    return final_images
+
+def main():
+
+    title = """
+    <h1 align="center">
+    Geometry Image Transforms with Kornia!
+    </h1>
+    """
+
+    with gr.Blocks() as demo:
+        gr.Markdown(title)
+
+        with gr.Row():
+            images_input = gr.Files()
+            with gr.Column():
+                translation = gr.Number(label= "Translation")
+                scale = gr.Number(label = "Scale", value= 1.0)
+                angle = gr.Number(label = "Angle")
+        
+        button = gr.Button('Transform')
+        result = gr.Image()
+
+        button.click(
+            geometry_transform,
+            inputs=[images_input,translation, scale, angle],
+            outputs=result
+        )
+    demo.launch()
+
+
+if __name__ == '__main__':
+    main()