Update README.md

README.md

@@ -47,12 +47,21 @@ image = Image.open(requests.get(url, stream=True).raw)
 feature_extractor = DetrFeatureExtractor.from_pretrained('facebook/detr-resnet-101-panoptic')
 model = DetrForSegmentation.from_pretrained('facebook/detr-resnet-101-panoptic')
 
+# prepare inputs for the model
 inputs = feature_extractor(images=image, return_tensors="pt")
+
+# forward pass
 outputs = model(**inputs)
-# model predicts COCO classes, bounding boxes, and masks
-logits = outputs.logits
-bboxes = outputs.pred_boxes
-masks = outputs.pred_masks
+
+# use the `post_process_panoptic` method of `DetrFeatureExtractor` to convert to COCO format
+processed_sizes = torch.as_tensor(inputs["pixel_values"].shape[-2:]).unsqueeze(0)
+result = feature_extractor.post_process_panoptic(outputs, processed_sizes)[0]
+
+# the segmentation is stored in a special-format png
+panoptic_seg = Image.open(io.BytesIO(result["png_string"]))
+panoptic_seg = numpy.array(panoptic_seg, dtype=numpy.uint8)
+# retrieve the ids corresponding to each mask
+panoptic_seg_id = rgb_to_id(panoptic_seg)
 ```
 
 Currently, both the feature extractor and model support PyTorch.