main

app.py

@@ -29,6 +29,12 @@ image_path = 'images/00000.jpg'
 # tile_size_meters = 128
 model = Demo(experiment_or_path=experiment_or_path, num_rotations=128, device='cpu')
 
+# def build_examples(root,num):
+#     images=os.listdir(root)
+#     info = []
+#     for i in range(len(images)):
+
+#     pass
 def demo_localize(image,long,lat,tile_size_meters):
     # inp = Image.fromarray(inp.astype('uint8'), 'RGB')
     # inp = transforms.ToTensor()(inp).unsqueeze(0)
@@ -78,15 +84,23 @@ def demo_localize(image,long,lat,tile_size_meters):
 # model = torch.hub.load('pytorch/vision:v0.6.0', 'resnet18', pretrained=True).eval()
 #标题
 title = "MapLocNet"
+title="<h1 align="center"><ins>MapLocNet</ins><br>UAV Vision-based Geo-Localization<br>Using Vectorized Maps</h1>"
 #标题下的描述，支持md格式
-description = "UAV Vision-based Geo-Localization Using Vectorized Maps"
+description = "OrienterNet finds the position and orientation of UAV image using OpenStreetMap. Click on one of the provided examples or upload your own UAV image!"
 
 # outputs = gr.outputs.Label(num_top_classes=3)
-outputs = gr.Plot()
+# outputs = gr.Plot()
+
+examples=[
+    ['images/00000.jpg',-122.435941445631,37.75704325989902,128],
+['images/00011.jpg',-122.4115887,37.76847628,128],
+['images/00022.jpg',-122.4421809,37.77668392,128],
+['images/00033.jpg',-122.4384978,37.76426403,128],
+]
 interface = gr.Interface(fn=demo_localize,
-                         inputs=["image",
-                                 gr.Number(label="Prior location-longitude)"),
-                                 gr.Number(label="Prior location-longitude)"),
+                         inputs=["UAV image",
+                                 gr.Number(label="The center longitude of the map"),
+                                 gr.Number(label="The central latitude of the map"),
                                  gr.Radio([64, 128, 256], label="Search radius (meters)", info="vectorized map size"),
                                  # gr.inputs.RadioGroup(label="Search radius (meters)",["English", "French", "Spanish"]),
                                  # gr.Slider(64, 512,label='Search radius (meters)')
@@ -94,5 +108,5 @@ interface = gr.Interface(fn=demo_localize,
                          outputs=["plot","plot","text"],
                          title=title,
                          description=description,
-                         examples=[['images/00000.jpg',-122.435941445631,37.75704325989902,128]])
+                         examples=examples)
 interface.launch()