label name

app.py

@@ -54,9 +54,8 @@ def detect(model, processor, image: Image.Image, prompts: list, threshold: float
     )
     result = results[0]
     annotations = []
-    for box, score, label in zip(result["boxes"], result["scores"], result["labels"]):
+    for box, score, label_name in zip(result["boxes"], result["scores"], result["text_labels"]):
         if score >= threshold:
-            label_name = prompts[label]
             xmin, ymin, xmax, ymax = [int(x) for x in box.tolist()]
             annotations.append(((xmin, ymin, xmax, ymax), f"{label_name} {score:.2f}"))
     elapsed_ms = (time.perf_counter() - t0) * 1000