added example images (#1)

- added example images (4ff38a191f6ac24c37c96e02db5ade5ceb4e75b2)

app.py

@@ -1,6 +1,12 @@
 from transformers import ViTFeatureExtractor, BertTokenizer, VisionEncoderDecoderModel, AutoTokenizer, AutoFeatureExtractor
 import gradio as gr
 
+title="Multilingual OCR (currently recognises: English and Chinese)"
+description="mOCR(multilingual-OCR) is a Vision-Encoder-Decoder model which uses pre-trained facebook's vit-mae-large as the encoder and xlm-roberta-base as the decoder. It has been trained on IAM, SROIE 2019 and TRDG(synthetic) datasets (amounting to approx 1.4 Million samples) for English and Chinese text-recognition."
+examples =[["demo_image/img1.png"], ["demo_image/img2.jpeg"], ["demo_image/img3.jpeg"], ["demo_image/img4.png"], ["demo_image/img5.jpeg"], ["demo_image/img6.jpeg"]]
+
+
+
 model=VisionEncoderDecoderModel.from_pretrained("priyank-m/mOCR")
 tokenizer =  AutoTokenizer.from_pretrained("xlm-roberta-base")
 feature_extractor = AutoFeatureExtractor.from_pretrained("facebook/vit-mae-large")
@@ -13,5 +19,5 @@ def run_ocr(image):
   return generated_text
     
          
-demo = gr.Interface(fn=run_ocr, inputs="image", outputs="text")
+demo = gr.Interface(fn=run_ocr, inputs="image", outputs="text", title=title, description=description, article=article, examples=examples)
 demo.launch()