Update app.py

app.py

@@ -66,20 +66,20 @@ class Model(nn.Module):
   
 
 model = Model(confg='./configs/rtdetr/rtdetr_r101vd_6x_coco.yml',ckpt="./checkpoint_init.pth")
-model2 = Model(confg='./configs/rtdetr/rtdetr_r101vd_6x_coco_cope12.yml',ckpt="./checkpointcope12.pth",cope=False)
-model3 = Model(confg='./configs/rtdetr/rtdetr_r101vd_6x_coco_cope24.yml',ckpt="./checkpointcope24.pth",cope=False)
+model2 = Model(confg='./configs/rtdetr/rtdetr_r101vd_6x_cococope12.yml',ckpt="./checkpointcope12.pth",cope=False)
+model3 =  Model(confg='./configs/rtdetr/rtdetr_r101vd_6x_coco.yml',ckpt="./rtdetrCOCO.pth",cope=False)
 
 #img = cv2.imread('./j.jpg',cv2.IMREAD_GRAYSCALE)
 #img = Image.open('./a.jpg').convert('RGB').resize((640,640))
 
 
-def detect(img,thr=0.2,cope='none'):
+def detect(img,thr=0.2,cope='aitod'):
   #print(img)                    #ndarray
   img = Image.fromarray(img).resize((640,640))
   t_img = transformer(img).unsqueeze(0)#.unsqueeze(0)      #[1,1,640,640]
   size = torch.tensor([[t_img.shape[2], t_img.shape[3]]])
   #print(t_img.shape)
-  if cope == 'none':
+  if cope == 'aitod':
       labels, boxes, scores=model(t_img,size)
   elif cope == 'cope12':
       labels, boxes, scores=model2(t_img,size)
@@ -105,6 +105,6 @@ def detect(img,thr=0.2,cope='none'):
   #save_path = Path('./output') / img_path.name
   return img
 
-interface = gr.Interface(fn=detect,inputs=["image",gr.Slider(label="thr", value=0.2, maximum=1, minimum=0),gr.inputs.Radio(['none','cope12','cope24'])],outputs="image",title="rt-cope detect")
+interface = gr.Interface(fn=detect,inputs=["image",gr.Slider(label="thr", value=0.2, maximum=1, minimum=0),gr.inputs.Radio(['aitod','cope12','COCO'])],outputs="image",title="rt-cope detect")
   
 interface.launch()