Fix Space runtime: pin numpy<2, upgrade gradio, return list outputs, bind server & share on Spaces

app.py

@@ -1,5 +1,10 @@
+import os
 from gradio_two_stage_app import build_interface
 
 if __name__ == "__main__":
     demo = build_interface()
-    demo.launch()
+    # On Spaces, localhost may not be accessible; serve on 0.0.0.0 and enable share
+    if os.environ.get("SPACE_ID"):
+        demo.queue().launch(server_name="0.0.0.0", server_port=int(os.environ.get("PORT", 7860)), share=True)
+    else:
+        demo.launch()

gradio_two_stage_app.py

@@ -45,7 +45,7 @@ def _as_table_rows(labels, probs):
 
 def predict(image: Image.Image):
     if image is None:
-        return gr.update(value="No image provided."), None, None
+        return gr.update(value="No image provided."), [], []
     try:
         cascade = get_cascade()
         tmp_path = '___temp_input.png'
@@ -53,7 +53,7 @@ def predict(image: Image.Image):
         result = cascade.predict(tmp_path)
         os.remove(tmp_path)
     except Exception as e:
-        return f"Error during inference: {e}", None, None
+        return f"Error during inference: {e}", [], []
 
     binary_part = result.get('binary', {})
     multi_part = result.get('multiclass', {})
@@ -77,7 +77,7 @@ def predict(image: Image.Image):
     bin_probs = binary_part.get('probs', []) or []
     bin_rows = _as_table_rows(getattr(get_cascade(), 'bin_id2label', {}), bin_probs)
 
-    multi_rows = None
+    multi_rows = []
     if 'multiclass' in result:
         m_probs = multi_part.get('probs', []) or []
         multi_rows = _as_table_rows(getattr(get_cascade(), 'multi_id2label', {}), m_probs)

requirements.txt

@@ -1,7 +1,8 @@
-gradio==4.44.0
+gradio==4.44.1
 transformers==4.44.2
 huggingface_hub==0.24.5
 torch==2.2.1
 torchvision==0.17.1
 safetensors==0.4.3
 Pillow==10.3.0
+numpy<2