Modify : Code and Evaluation Result

README.md

@@ -20,13 +20,10 @@ Model predict the data table of text form in the image.
 이미지를 모델에 입력하면 모델은 이미지로부터 표 형태의 데이터 테이블을 예측합니다.    
 
 ```python
-from transformers import Pix2StructForConditionalGeneration, Pix2StructImageProcessor, AutoTokenizer, Pix2StructProcessor
+from transformers import Pix2StructForConditionalGeneration, AutoProcessor
 from PIL import Image
 
-image_processor = Pix2StructImageProcessor()
-tokenizer = AutoTokenizer.from_pretrained("brainventures/deplot_kr")
-processor = Pix2StructProcessor(image_processor=image_processor, tokenizer=tokenizer)
-
+processor = AutoProcessor.from_pretrained("brainventures/deplot_kr")
 model = Pix2StructForConditionalGeneration.from_pretrained("brainventures/deplot_kr")
 
 image_path = "IMAGE_PATH"
@@ -76,8 +73,10 @@ This model achieves the following results:
 
 |metrics name | % |
 |:---|---:|
-| RNSS (Relative Number Set Similarity)| 99.5483 |
-| RMS F1 (Relative Mapping Similarity)| 16.6401 |
+| RNSS (Relative Number Set Similarity)| 98.1615 |
+|RMS (Relative Mapping Similarity) Precision | 83.1615 |
+|RMS Recall | 26.3549 |
+| RMS F1 Score | 31.5633 |
 
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