Update app.py

app.py

@@ -104,12 +104,6 @@ def get_model(ctx, model_path):
 
 # Download test image
 mx.test_utils.download('https://s3.amazonaws.com/onnx-model-zoo/duc/city1.png')
-# read image as rgb
-im = cv.imread('city1.png')[:, :, ::-1]
-# set output shape (same as input shape)
-result_shape = [im.shape[0],im.shape[1]]
-# set rgb mean of input image (used in mean subtraction)
-rgb_mean = cv.mean(im)
 
 
 # Download ONNX model
@@ -125,8 +119,15 @@ else:
 mod = get_model(ctx, 'ResNet101_DUC_HDC.onnx')
 
 def inference(im):
-  pre = preprocess(im)
-  conf,result_img,blended_img,raw = predict(pre)
-  return blended_img
+    # read image as rgb
+    im = cv.imread(im)[:, :, ::-1]
+    # set output shape (same as input shape)
+    result_shape = [im.shape[0],im.shape[1]]
+    # set rgb mean of input image (used in mean subtraction)
+    rgb_mean = cv.mean(im)
+    pre = preprocess(im)
+    conf,result_img,blended_img,raw = predict(pre)
+    return blended_img
 
-gr.Interface(inference,"image",gr.outputs.Image(type="pil")).launch()
+examples=[['city1.png']]
+gr.Interface(inference,gr.inputs.Image(type="filepath"),gr.outputs.Image(type="pil"),examples=examples).launch()