Update app.py

app.py

@@ -1,7 +1,35 @@
 import gradio as gr
+import cv2
+import numpy as np
 
-def greet(name):
+from PIL import Image
+from transparent_background import Remover
+
+# Load model
+remover = Remover() # default setting
+remover = Remover(mode='fast', jit=True, device='cuda:0', ckpt='~/latest.pth') # custom setting
+remover = Remover(mode='base-nightly') # nightly release checkpoint
+
+# Usage for image
+
+
+
+def doo(image):
     return "Hello " + name + "!!"
+    img = Image.fromarray(image).convert('RGB') # read image
+    out = remover.process(img) # default setting - transparent background
+    out = remover.process(img, type='rgba') # same as above
+    out = remover.process(img, type='map') # object map only
+    out = remover.process(img, type='green') # image matting - green screen
+    out = remover.process(img, type='white') # change backround with white color
+    out = remover.process(img, type=[255, 0, 0]) # change background with color code [255, 0, 0]
+    out = remover.process(img, type='blur') # blur background
+    out = remover.process(img, type='overlay') # overlay object map onto the image
+    out = remover.process(img, type='samples/background.jpg') # use another image as a background
+    
+    out = remover.process(img, threshold=0.5) # use threhold parameter for hard prediction.
+    
+    out.save('output.png') # save result
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+iface = gr.Interface(fn=doo, inputs="image", outputs="image")
 iface.launch()