added

app.py

@@ -9,27 +9,19 @@ from gluoncv.data.transforms.presets.segmentation import test_transform
 # using cpu
 ctx = mx.cpu(0)
 
-
-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")
+
+def segmentation(image):
+    img = Image.fromarray(image)
     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")
-    # mask.save("result.png")
-    # mmask = mpimg.imread("result.png")
-    # plt.imshow(mmask)
-    # plt.savefig("result.png")
     return mask
 
+
 image_in = gr.Image()
 image_out = gr.components.Image()
 
@@ -38,4 +30,4 @@ Iface = gr.Interface(
     inputs=image_in,
     outputs=image_out,
     title="Sementic Segmentation - MXNet",
-).launch()
+).launch()