[Conditional, Deformable DETR] Add postprocessing methods (#19709)

* Add postprocessing methods

* Update docs

* Add fix

* Add test

* Add test for deformable detr postprocessing

* Add post processing methods for segmentation

* Update code examples

* Add post_process to make the pipeline work

* Apply updates

Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

tests/models/deformable_detr/test_modeling_deformable_detr.py

@@ -565,6 +565,19 @@ class DeformableDetrModelIntegrationTests(unittest.TestCase):
         self.assertEqual(outputs.pred_boxes.shape, expected_shape_boxes)
         self.assertTrue(torch.allclose(outputs.pred_boxes[0, :3, :3], expected_boxes, atol=1e-4))
 
+        # verify postprocessing
+        results = feature_extractor.post_process_object_detection(
+            outputs, threshold=0.3, target_sizes=[image.size[::-1]]
+        )[0]
+        expected_scores = torch.tensor([0.7999, 0.7894, 0.6331, 0.4720, 0.4382])
+        expected_labels = [17, 17, 75, 75, 63]
+        expected_slice_boxes = torch.tensor([16.5028, 52.8390, 318.2544, 470.7841])
+
+        self.assertEqual(len(results["scores"]), 5)
+        self.assertTrue(torch.allclose(results["scores"], expected_scores, atol=1e-4))
+        self.assertSequenceEqual(results["labels"].tolist(), expected_labels)
+        self.assertTrue(torch.allclose(results["boxes"][0, :], expected_slice_boxes))
+
     def test_inference_object_detection_head_with_box_refine_two_stage(self):
         model = DeformableDetrForObjectDetection.from_pretrained(
             "SenseTime/deformable-detr-with-box-refine-two-stage"