Create app.py

app.py

@@ -0,0 +1,33 @@
+import gradio as gr
+
+import cv2
+import pytesseract
+import numpy as np
+from PIL import Image
+import urllib
+
+def process_image(image):
+  image = np.array(image)
+  gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
+  gray, img_bin = cv2.threshold(gray,128,255,cv2.THRESH_BINARY | cv2.THRESH_OTSU)
+  gray = cv2.bitwise_not(img_bin)
+
+  kernel = np.ones((2, 1), np.uint8)
+  img = cv2.erode(gray, kernel, iterations=1)
+  img = cv2.dilate(img, kernel, iterations=1)
+  generated_text = pytesseract.image_to_string(img)
+
+  return generated_text
+
+title = "Interactive demo: TrOCR"
+description = "Demo for tesseract ocr"
+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"]]
+
+iface = gr.Interface(fn=process_image, 
+                     inputs=gr.inputs.Image(type="pil"), 
+                     outputs=gr.outputs.Textbox(),
+                     title=title,
+                     description=description,
+                     article=article)
+iface.launch(debug=True)