Update app.py

app.py

@@ -1,9 +1,9 @@
 import os
 os.system('!python -m pip install detectron2 -f https://dl.fbaipublicfiles.com/detectron2/wheels/cu113/torch1.10/index.html')
-os.system('!git clone -b add_dit_inference_bis https://github.com/NielsRogge/unilm.git')
 
 import cv2
-from unilm.dit.object_detection.ditod import add_vit_config
+
+from detectron2.config import CfgNode as CN
 from detectron2.config import get_cfg
 from detectron2.utils.visualizer import ColorMode, Visualizer
 from detectron2.data import MetadataCatalog
@@ -12,6 +12,37 @@ from detectron2.engine import DefaultPredictor
 import gradio as gr
 
 
+def add_vit_config(cfg):
+    """
+    Add config for VIT.
+    """
+    _C = cfg
+
+    _C.MODEL.VIT = CN()
+
+    # CoaT model name.
+    _C.MODEL.VIT.NAME = ""
+
+    # Output features from CoaT backbone.
+    _C.MODEL.VIT.OUT_FEATURES = ["layer3", "layer5", "layer7", "layer11"]
+
+    _C.MODEL.VIT.IMG_SIZE = [224, 224]
+
+    _C.MODEL.VIT.POS_TYPE = "shared_rel"
+
+    _C.MODEL.VIT.DROP_PATH = 0.
+
+    _C.MODEL.VIT.MODEL_KWARGS = "{}"
+
+    _C.SOLVER.OPTIMIZER = "ADAMW"
+
+    _C.SOLVER.BACKBONE_MULTIPLIER = 1.0
+
+    _C.AUG = CN()
+
+    _C.AUG.DETR = False
+
+
 # Step 1: instantiate config
 cfg = get_cfg()
 add_vit_config(cfg)