Added mixed recognition

change suryaocr to paddleocr

src/web.py

@@ -1,5 +1,6 @@
 import os
 import io
+import re
 import base64
 import tempfile
 import shutil
@@ -8,6 +9,8 @@ import streamlit as st
 from PIL import Image
 from streamlit_paste_button import paste_image_button as pbutton
 from onnxruntime import InferenceSession
+from models.thrid_party.paddleocr.infer import predict_det, predict_rec
+from models.thrid_party.paddleocr.infer import utility
 
 from models.utils import mix_inference
 from models.det_model.inference import PredictConfig
@@ -16,9 +19,6 @@ from models.ocr_model.model.TexTeller import TexTeller
 from models.ocr_model.utils.inference import inference as latex_recognition
 from models.ocr_model.utils.to_katex import to_katex
 
-from surya.model.detection import segformer
-from surya.model.recognition.model import load_model
-from surya.model.recognition.processor import load_processor
 
 st.set_page_config(
     page_title="TexTeller",
@@ -64,11 +64,27 @@ def get_det_models():
     return infer_config, latex_det_model
 
 @st.cache_resource()
-def get_ocr_models():
+def get_ocr_models(accelerator):
-    det_processor, det_model = segformer.load_processor(), segformer.load_model()
+    use_gpu = accelerator == 'cuda'
-    rec_model, rec_processor = load_model(), load_processor()
+
-    lang_ocr_models = [det_model, det_processor, rec_model, rec_processor]
+    SIZE_LIMIT = 20 * 1024 * 1024
-    return lang_ocr_models
+    det_model_dir = "./models/thrid_party/paddleocr/checkpoints/det/default_model.onnx"
+    rec_model_dir = "./models/thrid_party/paddleocr/checkpoints/rec/default_model.onnx"
+    # The CPU inference of the detection model will be faster than the GPU inference (in onnxruntime)
+    det_use_gpu = False
+    rec_use_gpu = use_gpu and not (os.path.getsize(rec_model_dir) < SIZE_LIMIT)
+
+    paddleocr_args = utility.parse_args()
+    paddleocr_args.use_onnx = True
+    paddleocr_args.det_model_dir = det_model_dir
+    paddleocr_args.rec_model_dir = rec_model_dir
+
+    paddleocr_args.use_gpu = det_use_gpu
+    detector = predict_det.TextDetector(paddleocr_args)
+    paddleocr_args.use_gpu = rec_use_gpu
+    recognizer = predict_rec.TextRecognizer(paddleocr_args)
+    return [detector, recognizer]
+
 
 def get_image_base64(img_file):
     buffered = io.BytesIO()
@@ -111,16 +127,6 @@ with st.sidebar:
         on_change=change_side_bar
     )
 
-    if inf_mode == "Text formula mixed":
-        lang = st.selectbox(
-            "Language",
-            ("English", "Chinese")
-        )
-        if lang == "English":
-            lang = "en"
-        elif lang == "Chinese":
-            lang = "zh"
-
     num_beams = st.number_input(
         'Number of beams',
         min_value=1,
@@ -147,7 +153,7 @@ latex_rec_models = [texteller, tokenizer]
 
 if inf_mode == "Text formula mixed":
     infer_config, latex_det_model = get_det_models()
-    lang_ocr_models = get_ocr_models()
+    lang_ocr_models = get_ocr_models(accelerator)
 
 st.markdown(html_string, unsafe_allow_html=True)
 
@@ -225,7 +231,7 @@ elif uploaded_file or paste_result.image_data is not None:
             )[0]
             katex_res = to_katex(TexTeller_result)
         else:
-            katex_res = mix_inference(png_file_path, lang, infer_config, latex_det_model, lang_ocr_models, latex_rec_models, accelerator, num_beams)
+            katex_res = mix_inference(png_file_path, infer_config, latex_det_model, lang_ocr_models, latex_rec_models, accelerator, num_beams)
 
         st.success('Completed!', icon="✅")
         st.markdown(suc_gif_html, unsafe_allow_html=True)
@@ -234,7 +240,12 @@ elif uploaded_file or paste_result.image_data is not None:
         if inf_mode == "Formula only":
             st.latex(katex_res)
         elif inf_mode == "Text formula mixed":
-            st.markdown(katex_res)
+            mixed_res = re.split(r'(\n\$\$.*?\$\$\n)', katex_res)
+            for text in mixed_res:
+                if text.startswith('\n$$') and text.endswith('$$\n'):
+                    st.latex(text[3:-3])
+                else:
+                    st.markdown(text)
 
         st.write("")
         st.write("")