added

app.py

@@ -2,7 +2,9 @@ import gluoncv
 import mxnet as mx
 from gluoncv.utils.viz import get_color_pallete
 import gradio as gr
-
+import numpy as np
+import PIL as Image
+from gluoncv.data.transforms.presets.segmentation import test_transform
 
 # using cpu
 ctx = mx.cpu(0)
@@ -13,6 +15,12 @@ FILE_NAME = "result.png"
 model = gluoncv.model_zoo.get_model("psp_resnet101_ade", pretrained=True)
 
 def segmentation(img):
+    img = Image.open(img)
+    img.load()
+    img = np.asarray(img, dtype="int32")
+    img = mx.ndarray.array(img)
+    ctx = mx.cpu(0)
+    img = test_transform(img, ctx)
     output = model.predict(img)
     predict = mx.nd.squeeze(mx.nd.argmax(output, 1)).asnumpy()
     mask = get_color_pallete(predict, "ade20k")

requirements.txt

@@ -3,4 +3,5 @@ gluoncv==0.10.5
 matplotlib>=3.5.3
 opencv-python>=4.6.0
 gradio
-numpy==1.23.1
+numpy==1.23.1
+pillow