Update app.py

app.py

@@ -1,9 +1,13 @@
 import os
-os.system('pip install detectron2 -f https://dl.fbaipublicfiles.com/detectron2/wheels/cu102/torch1.9/index.html')
+os.system('git clone https://github.com/facebookresearch/detectron2.git')
+os.system('pip install -e detectron2')
 os.system("git clone https://github.com/microsoft/unilm.git")
+os.system("sed -i 's/from collections import Iterable/from collections.abc import Iterable/' unilm/dit/object_detection/ditod/table_evaluation/data_structure.py")
+os.system("curl -LJ -o publaynet_dit-b_cascade.pth 'https://layoutlm.blob.core.windows.net/dit/dit-fts/publaynet_dit-b_cascade.pth?sv=2022-11-02&ss=b&srt=o&sp=r&se=2033-06-08T16:48:15Z&st=2023-06-08T08:48:15Z&spr=https&sig=a9VXrihTzbWyVfaIDlIT1Z0FoR1073VB0RLQUMuudD4%3D'")
 
 import sys
 sys.path.append("unilm")
+sys.path.append("detectron2")
 
 import cv2
 
@@ -26,7 +30,7 @@ add_vit_config(cfg)
 cfg.merge_from_file("cascade_dit_base.yml")
 
 # Step 2: add model weights URL to config
-cfg.MODEL.WEIGHTS = "https://layoutlm.blob.core.windows.net/dit/dit-fts/publaynet_dit-b_cascade.pth"
+cfg.MODEL.WEIGHTS = "publaynet_dit-b_cascade.pth"
 
 # Step 3: set device
 cfg.MODEL.DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
@@ -52,10 +56,10 @@ def analyze_image(img):
     
     return result_image
     
-title = "Document Layout Analysis"
-description = ""
-article = ""
-examples =[['publaynet_example.jpeg'] ,['russian.png'],['another.png']]
+title = "Interactive demo: Document Layout Analysis with DiT"
+description = "Demo for Microsoft's DiT, the Document Image Transformer for state-of-the-art document understanding tasks. This particular model is fine-tuned on PubLayNet, a large dataset for document layout analysis (read more at the links below). To use it, simply upload an image or use the example image below and click 'Submit'. Results will show up in a few seconds. If you want to make the output bigger, right-click on it and select 'Open image in new tab'."
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2203.02378' target='_blank'>Paper</a> | <a href='https://github.com/microsoft/unilm/tree/master/dit' target='_blank'>Github Repo</a></p> | <a href='https://huggingface.co/docs/transformers/master/en/model_doc/dit' target='_blank'>HuggingFace doc</a></p>"
+examples =[['publaynet_example.jpeg']]
 css = ".output-image, .input-image, .image-preview {height: 600px !important}"
 
 iface = gr.Interface(fn=analyze_image,