Add layout detection app.py

app.py

@@ -7,9 +7,8 @@ import PIL
 
 os.system('pip install "git+https://github.com/facebookresearch/[email protected]#egg=detectron2" ')
 
-model = lp.Detectron2LayoutModel('lp://PubLayNet/faster_rcnn_R_50_FPN_3x/config', 
-                                 extra_config=["MODEL.ROI_HEADS.SCORE_THRESH_TEST", 0.8],
-                                 label_map={0: "Text", 1: "Title", 2: "List", 3:"Table", 4:"Figure"})
+model = lp.AutoLayoutModel("lp://efficientdet/PubLayNet", label_map={0: "Text", 1: "Title", 2: "List", 3:"Table", 4:"Figure"})
+
 
 article="References<br>[1] Z. Shen, R. Zhang, M. Dell, B. C. G. Lee, J. Carlson, and W. Li, “LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis,” arXiv Prepr. arXiv2103.15348, 2021."
 description = "Layout Detection/Parsing is one of the important tasks of converting unstructured data into structured data. This task helps to automate, digitize and organize the data in a usable format. In this project, we utilize LayoutParser library (https://github.com/Layout-Parser/layout-parser) to perform Layout Detection using pre-trained Faster_rcnn_R_50_FPN model that can classify the layout based on Text, Title, List, Table and Figure. Upload an image of a document or click an example image to check this out."

requirements.txt

@@ -1,4 +1,6 @@
+effdet
 layoutparser==0.3.2
+layoutparser[effdet]
 torch
 torchvision
 torchaudio