v2

app.py

@@ -42,14 +42,14 @@ from transformers import AutoProcessor
 from datasets import Features, Sequence, ClassLabel, Value, Array2D, Array3D
 from datasets import load_dataset # this dataset uses the new Image feature :) 
 
-from transformers import LayoutLMv3Processor, LayoutLMv3ForTokenClassification
+from transformers import LayoutLMv3Processor,LayoutLMv3ForTokenClassification, AutoProcessor ,AutoModelForTokenClassification
 
 #import cv2
 from PIL import Image, ImageDraw, ImageFont
 
 processor = LayoutLMv3Processor.from_pretrained("microsoft/layoutlmv3-base",apply_ocr = True)
 
-model = LayoutLMv3ForTokenClassification.from_pretrained("microsoft/layoutlmv3-base")
+model = LayoutLMv3ForTokenClassification.from_pretrained("nielsr/layoutlmv3-finetuned-funsd")
 
 dataset = load_dataset("nielsr/funsd-layoutlmv3")
 
@@ -93,7 +93,7 @@ if isinstance(features[label_column_name].feature, ClassLabel):
     id2label = {k: v for k,v in enumerate(label_list)}
     label2id = {v: k for k,v in enumerate(label_list)}
 else:
-    label_list = get_label_list(dataset["train"][label_column_name])
+    label_list = get_label_list(dataset["test"][label_column_name])
     id2label = {k: v for k,v in enumerate(label_list)}
     label2id = {v: k for k,v in enumerate(label_list)}
 num_labels = len(label_list)