Update README.md

README.md

@@ -66,9 +66,14 @@ model.cuda().eval()
 # prepare image for the model
 url = 'http://images.cocodataset.org/val2017/000000020247.jpg'
 image = Image.open(requests.get(url, stream=True).raw)
-input_resolution = (3, 224, 224)  # MambaVision supports any input resolutions but has been originally trained on (3, 224, 224)
+input_resolution = (3, 224, 224)  # MambaVision supports any input resolutions
 
-transform = create_transform(input_size=input_resolution, is_training=False, mean=model.config.mean, std=model.config.std, crop_mode=model.config.crop_mode, crop_pct=model.config.crop_pct)
+transform = create_transform(input_size=input_resolution,
+                             is_training=False,
+                             mean=model.config.mean,
+                             std=model.config.std,
+                             crop_mode=model.config.crop_mode,
+                             crop_pct=model.config.crop_pct)
 
 inputs = transform(image).unsqueeze(0).cuda()
 # model inference
@@ -102,10 +107,14 @@ model.cuda().eval()
 # prepare image for the model
 url = 'http://images.cocodataset.org/val2017/000000020247.jpg'
 image = Image.open(requests.get(url, stream=True).raw)
-input_resolution = (3, 224, 224)  # MambaVision supports any input resolutions but has been originally trained on (3, 224, 224)
-
-transform = create_transform(input_size=input_resolution, is_training=False, mean=model.config.mean, std=model.config.std, crop_mode=model.config.crop_mode, crop_pct=model.config.crop_pct)
-
+input_resolution = (3, 224, 224)  # MambaVision supports any input resolutions
+
+transform = create_transform(input_size=input_resolution,
+                             is_training=False,
+                             mean=model.config.mean,
+                             std=model.config.std,
+                             crop_mode=model.config.crop_mode,
+                             crop_pct=model.config.crop_pct)
 inputs = transform(image).unsqueeze(0).cuda()
 # model inference
 out_avg_pool, features = model(inputs)