Update app.py

app.py

@@ -1,42 +1,12 @@
-# import gradio as gr
-# from transformers import pipeline
 from PIL import Image
 import pytesseract
 import easyocr
 import cv2
 import os
-
-# pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
-
-# def predict(input_img):
-#     predictions = pipeline(input_img)
-#     return input_img, {p["label"]: p["score"] for p in predictions} 
-
-# def recognize(input_img):
-#     text = pytesseract.image_to_string(Image.open("./data/" + filename))
-#     return input_img, text
-
-# gradio_app = gr.Interface(
-#     recognize,
-#     inputs=[gr.Image(label="Upload an Image", type="pil")],
-#     outputs=[gr.Textbox(label="Text in the Image")],
-    
-#     title="Extrate Text From Image",
-# )
-
-# if __name__ == "__main__":
-#     gradio_app.launch(server_port=8756)
-
-
-import os
+from io import BytesIO
 
 import matplotlib.pyplot as plt
-import streamlit as st 
-
-import cv2
-import tensorflow as tf
-from PIL import Image
-import pytesseract
+import streamlit as st
 
 DET_ARCHS = ["pytesseract", "easyocr"]
 
@@ -83,7 +53,7 @@ def main():
         else:
             with st.spinner(type(doc)):
                 if det_arch == 'pytesseract':
-                    predictor = pytesseract.image_to_string(doc)
+                    predictor = pytesseract.image_to_string(Image.open(BytesIO(doc)))
                 else:
                     reader = easyocr.Reader(['en'])
                     predictor = reader.readtext(doc, detail = 0)
@@ -97,4 +67,27 @@ def main():
 
                 
 if __name__ == '__main__':
-    main()
+    main()
+
+
+
+# pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
+
+# def predict(input_img):
+#     predictions = pipeline(input_img)
+#     return input_img, {p["label"]: p["score"] for p in predictions} 
+
+# def recognize(input_img):
+#     text = pytesseract.image_to_string(Image.open("./data/" + filename))
+#     return input_img, text
+
+# gradio_app = gr.Interface(
+#     recognize,
+#     inputs=[gr.Image(label="Upload an Image", type="pil")],
+#     outputs=[gr.Textbox(label="Text in the Image")],
+    
+#     title="Extrate Text From Image",
+# )
+
+# if __name__ == "__main__":
+#     gradio_app.launch(server_port=8756)