Fix resolution

prismer/experts/model_bank.py

@@ -40,7 +40,7 @@ def load_expert_model(task=None):
         cfg = setup_cfg(args)
         model = DefaultPredictor(cfg).model
         transform = transforms.Compose([
-            transforms.Resize(size=479, max_size=480)
+            transforms.Resize([480, 480])
         ])
 
     elif task == 'seg_ade':
@@ -60,7 +60,7 @@ def load_expert_model(task=None):
         cfg = setup_cfg(args)
         model = DefaultPredictor(cfg).model
         transform = transforms.Compose([
-            transforms.Resize(size=479, max_size=480)
+            transforms.Resize([480, 480])
         ])
 
     elif task == 'obj_detection':
@@ -81,7 +81,7 @@ def load_expert_model(task=None):
         cfg = setup_cfg(args)
         model = DefaultPredictor(cfg).model
         transform = transforms.Compose([
-            transforms.Resize(size=479, max_size=480)
+            transforms.Resize([480, 480])
         ])
 
     elif task == 'ocr_detection':

prismer_model.py

@@ -63,12 +63,10 @@ def run_experts(image_path: str) -> tuple[str | None, ...]:
     out_path = image_dir / 'image.jpg'
     cv2.imwrite(out_path.as_posix(), cv2.imread(image_path))
 
+    expert_names = ['edge', 'normal', 'objdet', 'ocrdet', 'segmentation']
     run_expert('depth')
     with concurrent.futures.ProcessPoolExecutor() as executor:
-        executor.map(run_expert, ['edge', 'normal', 'objdet'])
-
-    with concurrent.futures.ProcessPoolExecutor() as executor:
-        executor.map(run_expert, ['ocrdet', 'segmentation'])
+        executor.map(run_expert, expert_names)
 
     keys = ['depth', 'edge', 'normal', 'seg_coco', 'obj_detection', 'ocr_detection']
     results = [pathlib.Path('prismer/helpers/labels') / key / 'helpers/images/image.png' for key in keys]