Update app.py

app.py

@@ -1,26 +1,41 @@
 from PIL import Image
-import sys, os, distutils.core
-sys.path.insert(0, os.path.abspath('./detectron2-main'))
-import gradio as gr
-import torch, detectron2
+import sys
+import os
+import distutils.core
 import pandas as pd
+import numpy as np
+import torch
+import torch.nn as nn
+from torchvision import transforms, models
+import gradio as gr
+
+
+sys.path.insert(0, os.path.abspath('./detectron2-main'))
+import detectron2
 from detectron2.utils.logger import setup_logger
 setup_logger()
-import numpy as np
-# import os, json, cv2, random
 from detectron2 import model_zoo
 from detectron2.engine import DefaultPredictor
 from detectron2.config import get_cfg
-# from detectron2.utils.visualizer import Visualizer
-# from detectron2.data import MetadataCatalog, DatasetCatalog
-import numpy
-# import torch.optim as optim
-import torch.nn as nn
-# from tqdm.notebook import tqdm, trange
-from torchvision import transforms,models #, datasets
-SEED = 1234
+import os, json, cv2, random
+from detectron2.utils.visualizer import Visualizer
+from detectron2.data import MetadataCatalog, DatasetCatalog
+
+
+# Example of setting up detectron2 configuration
+cfg = get_cfg()
+cfg.MODEL.DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
+cfg.MODEL.WEIGHTS = model_zoo.get_checkpoint_url("COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml")
+cfg.MODEL.ROI_HEADS.NUM_CLASSES = 80
+# Example of creating a default predictor with detectron2
+predictor = DefaultPredictor(cfg)
+
+
+
+SEED = 2024
+torch.manual_seed(SEED)
+np.random.seed(SEED)
 
-print("hello world")
 
 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 num_classes = 15