examples

app.py

@@ -49,15 +49,27 @@ fiber_demo = GLIPDemo(
     show_mask_heatmaps=False
 )
 
+athetics_params = {
+    "skip_name": False, # whether we overlay the phrase over the box
+    "override_color": (255, 255, 255), # box color, default is white
+    "text_size": 1.0,
+    "text_pixel": 3,
+    "box_alpha": 1.0,
+    "box_pixel": 5,
+    "text_offset_original": 8, # distance between text and box
+}
+
 def predict(image, text, ground_tokens=""):
     ground_tokens = None if ground_tokens.strip() == "" else ground_tokens.strip().split(";")
-    result, _ = glip_demo.run_on_web_image(deepcopy(image[:, :, [2, 1, 0]]), text, 0.5, ground_tokens)
-    fiber_result, _ = fiber_demo.run_on_web_image(deepcopy(image[:, :, [2, 1, 0]]), text, 0.5, ground_tokens)
+    result, _ = glip_demo.run_on_web_image(deepcopy(image[:, :, [2, 1, 0]]), text, 0.5, ground_tokens, **athetics_params)
+    fiber_result, _ = fiber_demo.run_on_web_image(deepcopy(image[:, :, [2, 1, 0]]), text, 0.5, ground_tokens, **athetics_params)
     return result[:, :, [2, 1, 0]], fiber_result[:, :, [2, 1, 0]]
 
 
 image = gr.inputs.Image()
 
+
+
 gr.Interface(
     description="Object Recognition with DesCo (https://github.com/liunian-harold-li/DesCo)",
     fn=predict,
@@ -73,12 +85,8 @@ gr.Interface(
         ),
     ],
     examples=[
-        ["./coco_000000281759.jpg", "A green umbrella. A pink striped umbrella. A plain white umbrella.", ""],
-        ["./coco_000000281759.jpg", "a flowery top. A blue dress. An orange shirt .", ""],
-        ["./coco_000000281759.jpg", "a car . An electricity box .", ""],
         ["./1.jpg", "a train besides sidewalk", "train;sidewalk"],
+        ["./2.jpg", "Bumblebee, yellow with black accents.", "Bumblebee"],
     ],
     article=Path("docs/intro.md").read_text()
 ).launch()
-# ).launch(server_name="0.0.0.0", server_port=7000, share=True)
-