added: basic app

app.py

@@ -0,0 +1,14 @@
+import gradio as gr
+
+from model import inverse_pic
+
+demo = gr.Interface(
+    inverse_pic,
+    gr.Image(show_label=True, label="Input Image"),
+    "image",
+    title="Image Transposer",
+    description="Transpose Image",
+)
+
+if __name__ == "__main__":
+    demo.launch()

model.py

@@ -0,0 +1,8 @@
+import cv2
+import numpy as np
+
+
+def inverse_pic(input_img):
+    # print(type(input_img))
+    input_img = cv2.cvtColor(input_img, cv2.COLOR_BGR2RGB)
+    return np.flip(input_img)

requirements.txt

@@ -5,4 +5,5 @@ grad-cam
 pillow
 numpy
 pytorch_lightning
-cv2
+cv2
+gradio