Create app.py

app.py

@@ -0,0 +1,49 @@
+import pandas as pd
+from PIL import Image
+import streamlit as st
+from streamlit_drawable_canvas import st_canvas
+
+from transformers import TrOCRProcessor, VisionEncoderDecoderModel
+processor = TrOCRProcessor.from_pretrained("UBC-NLP/ArOCR-Fonts-v2")
+model = VisionEncoderDecoderModel.from_pretrained("UBC-NLP/ArOCR-Fonts-v2")
+def predict(img):
+  # if img is None:
+  #   _,generated_text=main(image)
+  #   return generated_text
+  # else:
+
+    images = Image.open(img).convert("RGB")
+    pixel_values = processor(images, return_tensors="pt").pixel_values
+    # PIL_image = Image.fromarray(np.uint8(pixel_values.squeeze()[0,:,:])).convert('RGB')
+    generated_ids = model.generate(pixel_values,max_length=512)
+    generated_text = processor.batch_decode(
+            generated_ids, skip_special_tokens=True)[0]
+    return generated_text
+
+# Specify canvas parameters in application
+stroke_width = st.sidebar.slider("Stroke width: ", 1, 25, 3)
+stroke_color = st.sidebar.color_picker("Stroke color hex: ")
+bg_color = st.sidebar.color_picker("Background color hex: ", "#eee")
+bg_image = st.sidebar.file_uploader("Background image:", type=["png", "jpg"])
+
+realtime_update = st.sidebar.checkbox("Update in realtime", True)
+
+  
+# Create a canvas component
+canvas_result = st_canvas(
+    fill_color="rgba(255, 165, 0, 0.3)",  # Fixed fill color with some opacity
+    stroke_width=stroke_width,
+    stroke_color=stroke_color,
+    background_color=bg_color,
+    background_image=Image.open(bg_image) if bg_image else None,
+    update_streamlit=realtime_update,
+    height=200,
+    drawing_mode="freedraw",
+    display_toolbar=st.sidebar.checkbox("Display toolbar", True),
+    key="full_app",
+)
+
+# Do something interesting with the image data and paths
+if canvas_result.image_data is not None:
+    st.image(canvas_result.image_data)
+    st.text(predict(canvas_result.image_data))