Use our examples

app.py

@@ -11,10 +11,10 @@ model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-base-printed"
 model.config.eos_token_id = 2
 
 # load image examples
-urls = ['https://layoutlm.blob.core.windows.net/trocr/dataset/SROIE2019Task2Crop/train/X00016469612_1.jpg', 'https://layoutlm.blob.core.windows.net/trocr/dataset/SROIE2019Task2Crop/train/X51005255805_7.jpg', 'https://layoutlm.blob.core.windows.net/trocr/dataset/SROIE2019Task2Crop/train/X51005745214_6.jpg']
-for idx, url in enumerate(urls):
-  image = Image.open(requests.get(url, stream=True).raw)
-  image.save(f"image_{idx}.png")
+#urls = ['https://layoutlm.blob.core.windows.net/trocr/dataset/SROIE2019Task2Crop/train/X00016469612_1.jpg', 'https://layoutlm.blob.core.windows.net/trocr/dataset/SROIE2019Task2Crop/train/X51005255805_7.jpg', 'https://layoutlm.blob.core.windows.net/trocr/dataset/SROIE2019Task2Crop/train/X51005745214_6.jpg']
+#for idx, url in enumerate(urls):
+#  image = Image.open(requests.get(url, stream=True).raw)
+#  image.save(f"image_{idx}.png")
 
 def process_image(image):
     # prepare image
@@ -31,7 +31,9 @@ def process_image(image):
 title = "Interactive demo: TrOCR"
 description = "Demo for Microsoft's TrOCR, an encoder-decoder model consisting of an image Transformer encoder and a text Transformer decoder for state-of-the-art optical character recognition (OCR) on single-text line images. This particular model is fine-tuned on SROIE Task 2, a dataset of annotated printed images. To use it, simply upload a (single-text line) image or use one of the example images below and click 'submit'. Results will show up in a few seconds."
 article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2109.10282'>TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models</a> | <a href='https://github.com/microsoft/unilm/tree/master/trocr'>Github Repo</a></p>"
-examples =[["image_0.png"], ["image_1.png"], ["image_2.png"]]
+#examples =[["image_0.png"], ["image_1.png"], ["image_2.png"]]
+examples = [["example-line-0.png"], ["example-line-1.png"],["example-line-2.png"]]
+
 
 #css = """.output_image, .input_image {height: 600px !important}"""