Add examples for detection models finetuning (#30422)

* Training script for object detection

* Evaluation script for object detection

* Training script for object detection with eval loop outside trainer

* Trainer DETR finetuning

* No trainer DETR finetuning

* Eval script

* Refine object detection example with trainer

* Remove commented code and enable telemetry

* No trainer example

* Add requirements for object detection examples

* Add test for trainer example

* Readme draft

* Fix uploading to HUB

* Readme improvements

* Update eval script

* Adding tests for object-detection examples

* Add object-detection example

* Add object-detection resources to docs

* Update README with custom dataset instructions

* Update year

* Replace valid with validation

* Update instructions for custom dataset

* Remove eval script

* Remove use_auth_token

* Add copied from and telemetry

* Fixup

* Update readme

* Fix id2label

* Fix links in docs

* Update examples/pytorch/object-detection/run_object_detection.py

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update examples/pytorch/object-detection/run_object_detection.py

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Move description to the top

* Fix Trainer example

* Update no trainer example

* Update albumentations version

---------

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

examples/pytorch/test_pytorch_examples.py

@@ -48,6 +48,7 @@ SRC_DIRS = [
         "speech-pretraining",
         "image-pretraining",
         "semantic-segmentation",
+        "object-detection",
     ]
 ]
 sys.path.extend(SRC_DIRS)
@@ -62,6 +63,7 @@ if SRC_DIRS is not None:
     import run_mae
     import run_mlm
     import run_ner
+    import run_object_detection
     import run_qa as run_squad
     import run_semantic_segmentation
     import run_seq2seq_qa as run_squad_seq2seq
@@ -609,3 +611,31 @@ class ExamplesTests(TestCasePlus):
             run_semantic_segmentation.main()
             result = get_results(tmp_dir)
             self.assertGreaterEqual(result["eval_overall_accuracy"], 0.1)
+
+    @patch.dict(os.environ, {"WANDB_DISABLED": "true"})
+    def test_run_object_detection(self):
+        tmp_dir = self.get_auto_remove_tmp_dir()
+        testargs = f"""
+            run_object_detection.py
+            --model_name_or_path qubvel-hf/detr-resnet-50-finetuned-10k-cppe5
+            --output_dir {tmp_dir}
+            --dataset_name qubvel-hf/cppe-5-sample
+            --do_train
+            --do_eval
+            --remove_unused_columns False
+            --overwrite_output_dir True
+            --eval_do_concat_batches False
+            --max_steps 10
+            --learning_rate=1e-6
+            --per_device_train_batch_size=2
+            --per_device_eval_batch_size=1
+            --seed 32
+        """.split()
+
+        if is_torch_fp16_available_on_device(torch_device):
+            testargs.append("--fp16")
+
+        with patch.object(sys, "argv", testargs):
+            run_object_detection.main()
+            result = get_results(tmp_dir)
+            self.assertGreaterEqual(result["test_map"], 0.1)