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app.py

@@ -21,6 +21,9 @@ from datetime import datetime
 from huggingface_hub import hf_hub_download
 hf_hub_download = partial(hf_hub_download, library_name="gligen_demo")
 
+import sys
+sys.tracebacklimit = 0
+
 
 def load_from_hf(repo_id, filename='diffusion_pytorch_model.bin', subfolder=None):
     cache_file = hf_hub_download(repo_id=repo_id, filename=filename, subfolder=subfolder)
@@ -294,7 +297,9 @@ def generate(task, language_instruction, grounding_texts, sketch_pad,
     grounding_texts = [x.strip() for x in grounding_texts.split(';')]
     # assert len(boxes) == len(grounding_texts)
     if len(boxes) != len(grounding_texts):
-        assert len(boxes) > len(grounding_texts)
+        if len(boxes) < len(grounding_texts):
+            raise ValueError("""The number of boxes should be equal to the number of grounding objects.
+Number of boxes drawn: {}, number of grounding tokens: {}""".format(len(boxes), len(grounding_texts)))
         grounding_texts = grounding_texts + [""] * (len(boxes) - len(grounding_texts))
 
     boxes = (np.asarray(boxes) / 512).tolist()
@@ -749,6 +754,6 @@ with Blocks(
         )
 
 main.queue(concurrency_count=1, api_open=False)
-main.launch(share=False, show_api=False)
+main.launch(share=False, show_api=False, show_error=True)