Initial commit.

.idea/workspace.xml

@@ -2,6 +2,7 @@
 <project version="4">
   <component name="ChangeListManager">
     <list default="true" id="5dd22f22-8223-4d55-99f9-57d1e00622d7" name="Default Changelist" comment="Initial commit.">
+      <change beforePath="$PROJECT_DIR$/.idea/workspace.xml" beforeDir="false" afterPath="$PROJECT_DIR$/.idea/workspace.xml" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/app.py" beforeDir="false" afterPath="$PROJECT_DIR$/app.py" afterDir="false" />
     </list>
     <option name="SHOW_DIALOG" value="false" />
@@ -50,7 +51,7 @@
       <option name="number" value="Default" />
       <option name="presentableId" value="Default" />
       <updated>1647350746642</updated>
-      <workItem from="1647350750956" duration="6323000" />
+      <workItem from="1647350750956" duration="6572000" />
     </task>
     <task id="LOCAL-00001" summary="Initial commit.">
       <created>1647352693910</created>
@@ -164,7 +165,14 @@
       <option name="project" value="LOCAL" />
       <updated>1647357087405</updated>
     </task>
-    <option name="localTasksCounter" value="17" />
+    <task id="LOCAL-00017" summary="Initial commit.">
+      <created>1647357185506</created>
+      <option name="number" value="00017" />
+      <option name="presentableId" value="LOCAL-00017" />
+      <option name="project" value="LOCAL" />
+      <updated>1647357185506</updated>
+    </task>
+    <option name="localTasksCounter" value="18" />
     <servers />
   </component>
   <component name="TypeScriptGeneratedFilesManager">

app.py

@@ -1,3 +1,5 @@
+import os
+
 import gradio as gr
 import numpy as np
 import requests
@@ -46,6 +48,13 @@ def download_file_from_google_drive(destination=WEIGHTS):
     save_response_content(response, destination)
 
 
+def download_weights():
+    if not os.path.exists(WEIGHTS):
+        url = 'https://drive.google.com/file/d/1v6_d2KHzRROsjb_cgxU7jvmnGVDXeBia/view?usp=sharing'
+        import urllib.request
+        urllib.request.urlretrieve(url, WEIGHTS)
+
+
 def segment_segmenter(image, model, window_size, window_stride, encoder_features=False, decoder_features=False,
                       no_upsample=False, batch_size=2):
     seg_pred = utils.inference(