Update model.py

model.py

@@ -162,8 +162,6 @@ class Model:
         subprocess.run(shlex.split(f'wget {pose_checkpoint_file} -O models/hrnet_w48_coco_256x192-b9e0b3ab_20200708.pth'))
         pose_checkpoint = 'models/hrnet_w48_coco_256x192-b9e0b3ab_20200708.pth'
         
-        det_cat_id = 1
-        bbox_thr = 0.2
         ## detector
         det_config_mmcv = mmcv.Config.fromfile(det_config)
         self.det_model = init_detector(det_config_mmcv, det_checkpoint, device=device)
@@ -280,6 +278,8 @@ class Model:
     @torch.inference_mode()
     def process_pose(self, input_img, prompt, neg_prompt, fix_sample, scale, con_strength, base_model):    
         global current_base
+        det_cat_id = 1
+        bbox_thr = 0.2
         device = 'cuda'
         if base_model == 'sd-v1-4.ckpt':
             model = self.model
@@ -302,7 +302,7 @@ class Model:
 
         image = im.copy()
         im = img2tensor(im).unsqueeze(0)/255.
-        mmdet_results = inference_detector(det_model, image)
+        mmdet_results = inference_detector(self.det_model, image)
         # keep the person class bounding boxes.
         person_results = process_mmdet_results(mmdet_results, det_cat_id)
 
@@ -313,7 +313,7 @@ class Model:
         # e.g. use ('backbone', ) to return backbone feature
         output_layer_names = None
         pose_results, returned_outputs = inference_top_down_pose_model(
-            pose_model,
+            self.pose_model,
             image,
             person_results,
             bbox_thr=bbox_thr,