a

app.py

@@ -17,11 +17,9 @@ model.eval()
 
 def generate(image):
 
-    #inputs = processor(images=image, return_tensors="pt", max_patches=1024).to(device)
-    #generated_ids = model.generate(flattened_patches=inputs.flattened_patches, attention_mask=inputs.attention_mask, max_length=600)
-    #generated_caption = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
-    
-    generated_caption = "{'mark': 'bar', 'encoding': {'x': {'field': '', 'type': 'ordinal'}, 'y': {'field': '', 'type': 'quantitative'}}, 'data': {'values': [{'x': 0, 'y': 5.6}, {'x': 1, 'y': 6.7}, {'x': 2, 'y': 5.0}, {'x': 3, 'y': 18.7}]}}"
+    inputs = processor(images=image, return_tensors="pt", max_patches=1024).to(device)
+    generated_ids = model.generate(flattened_patches=inputs.flattened_patches, attention_mask=inputs.attention_mask, max_length=600)
+    generated_caption = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
 
     # Generate the Vega image
     vega = string_to_vega(generated_caption)