swtiched to YolosImageProcessor

README.md

@@ -35,18 +35,18 @@ You can use the raw model for object detection. See the [model hub](https://hugg
 Here is how to use this model:
 
 ```python
-from transformers import YolosFeatureExtractor, YolosForObjectDetection, AutoImageProcessor
+from transformers import YolosImageProcessor, YolosForObjectDetection
 from PIL import Image
+import torch
 import requests
 
-url = 'http://images.cocodataset.org/val2017/000000039769.jpg'
+url = "http://images.cocodataset.org/val2017/000000039769.jpg"
 image = Image.open(requests.get(url, stream=True).raw)
 
-feature_extractor = YolosFeatureExtractor.from_pretrained('hustvl/yolos-tiny')
 model = YolosForObjectDetection.from_pretrained('hustvl/yolos-tiny')
-image_processor = AutoImageProcessor.from_pretrained("hustvl/yolos-tiny")
+image_processor = YolosImageProcessor.from_pretrained("hustvl/yolos-tiny")
 
-inputs = feature_extractor(images=image, return_tensors="pt")
+inputs = image_processor(images=image, return_tensors="pt")
 outputs = model(**inputs)
 
 # model predicts bounding boxes and corresponding COCO classes