update: gradio version to 3.41.2

app.py

@@ -7,6 +7,7 @@ from common.utils import (
     change_estimate_geom,
     run_matching,
     gen_examples,
+    GRADIO_VERSION,
     DEFAULT_RANSAC_METHOD,
     DEFAULT_SETTING_GEOMETRY,
     DEFAULT_RANSAC_REPROJ_THRESHOLD,
@@ -20,7 +21,7 @@ from common.utils import (
 DESCRIPTION = """
 # Image Matching WebUI
 This Space demonstrates [Image Matching WebUI](https://github.com/Vincentqyw/image-matching-webui) by vincent qin. Feel free to play with it, or duplicate to run image matching without a queue!
-<br/><br/>
+<br/>
 🔎 For more details about supported local features and matchers, please refer to https://github.com/Vincentqyw/image-matching-webui
 
 🚀 All algorithms run on CPU for inference, causing slow speeds and high latency. For faster inference, please download the [source code](https://github.com/Vincentqyw/image-matching-webui) for local deployment.
@@ -39,11 +40,20 @@ def ui_change_imagebox(choice):
     Returns:
         dict: A dictionary containing the updated value, sources, and type for the image box.
     """
-    return {
+    ret_dict = {
         "value": None,  # The updated value of the image box
-        "source": choice,  # The list of image sources to be displayed
         "__type__": "update",  # The type of update for the image box
     }
+    if GRADIO_VERSION > "3":
+        return {
+            **ret_dict,
+            "sources": choice,  # The list of image sources to be displayed
+        }
+    else:
+        return {
+            **ret_dict,
+            "source": choice,  # The list of image sources to be displayed
+        }
 
 
 def ui_reset_state(*args):
@@ -113,7 +123,11 @@ def run(server_name="0.0.0.0", server_port=7860):
                         interactive=True,
                     )
                     match_image_src = gr.Radio(
-                        ["upload", "webcam", "canvas"],
+                        (
+                            ["upload", "webcam", "clipboard"]
+                            if GRADIO_VERSION > "3"
+                            else ["upload", "webcam", "canvas"]
+                        ),
                         label="Image Source",
                         value="upload",
                     )
@@ -122,14 +136,14 @@ def run(server_name="0.0.0.0", server_port=7860):
                         label="Image 0",
                         type="numpy",
                         image_mode="RGB",
-                        height=300,
+                        height=300 if GRADIO_VERSION > "3" else None,
                         interactive=True,
                     )
                     input_image1 = gr.Image(
                         label="Image 1",
                         type="numpy",
                         image_mode="RGB",
-                        height=300,
+                        height=300 if GRADIO_VERSION > "3" else None,
                         interactive=True,
                     )
 

common/utils.py

@@ -25,7 +25,7 @@ DEFAULT_RANSAC_MAX_ITER = 10000
 DEFAULT_MIN_NUM_MATCHES = 4
 DEFAULT_MATCHING_THRESHOLD = 0.2
 DEFAULT_SETTING_GEOMETRY = "Homography"
-
+GRADIO_VERSION = gr.__version__.split('.')[0]
 
 def get_model(match_conf):
     Model = dynamic_load(matchers, match_conf["model"]["name"])
@@ -38,7 +38,6 @@ def get_feature_model(conf):
     model = Model(conf["model"]).eval().to(device)
     return model
 
-
 def gen_examples():
     random.seed(1)
     example_matchers = [

env-docker.txt

@@ -1,8 +1,8 @@
 e2cnn==0.2.3
 einops==0.6.1
 gdown==4.7.1
-gradio==4.25.0
-gradio_client==0.15.0
+gradio==3.41.2
+gradio_client==0.5.0
 h5py==3.9.0
 imageio==2.31.1
 Jinja2==3.1.2

pre-requirements.txt

@@ -6,5 +6,5 @@ pytorch-lightning>=1.4.2
 omegaconf>=2.1.1
 einops>=0.3.0
 kornia>=0.6
-gradio==3.50.2
-gradio_client==0.6.1
+gradio==3.41.2
+gradio_client==0.5.0