nvm

app.py

@@ -19,14 +19,13 @@ ds = dataset["train"]
 
 
 def query(image, top_k=4):
-    inputs = feature_extractor(image.convert("RGB"), return_tensors="pt")
+    inputs = feature_extractor(image, return_tensors="pt")
     model_output = model(**inputs)
     embedding = model_output.pooler_output.detach()
     results = index.query(embedding, k=top_k)
     inx = results[0][0].tolist()
     logits = results[1][0].tolist()
     images = ds.select(inx)["image"]
-
     captions = ds.select(inx)["label"]
     images_with_captions = [(i, c) for i, c in zip(images, captions)]
     labels_with_probs = dict(zip(captions, logits))